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fea727eb36c7086d269d7ae000c2362dfa892df5
baidu/Quanlse
Quanlse/remoteOptimizer.py
[ "Apache-2.0" ]
Python
remoteOptimize1QubitGRAPE
Union[Tuple[QJob, float], Tuple[List[QJob], List[float]]]
def remoteOptimize1QubitGRAPE(ham: QHam, uGoal: Union[ndarray, List[ndarray]], tg: int = 20, iterate: int = 150, xyzPulses: List[int] = None) -> Union[Tuple[QJob, float], Tuple[List[QJob], List[float]]]: """ Optimize a single-qubit gate using Gradient Ascent Pulse Engineering. ...
Optimize a single-qubit gate using Gradient Ascent Pulse Engineering. :param ham: the QHamiltonian object. :param uGoal: the target unitary. :param tg: gate time. :param iterate: max number of iteration. :param xyzPulses: a list of three integers indicating the numbers of ...
Optimize a single-qubit gate using Gradient Ascent Pulse Engineering.
[ "Optimize", "a", "single", "-", "qubit", "gate", "using", "Gradient", "Ascent", "Pulse", "Engineering", "." ]
def remoteOptimize1QubitGRAPE(ham: QHam, uGoal: Union[ndarray, List[ndarray]], tg: int = 20, iterate: int = 150, xyzPulses: List[int] = None) -> Union[Tuple[QJob, float], Tuple[List[QJob], List[float]]]: args = [ham.dump(), numpyMatrixToDictMatrix(uGoal)] kwargs = { "tg": t...
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Optimize a single-qubit gate using Gradient Ascent Pulse Engineering.
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[ "\"\"\"\n Optimize a single-qubit gate using Gradient Ascent Pulse Engineering.\n\n :param ham: the QHamiltonian object.\n :param uGoal: the target unitary.\n :param tg: gate time.\n :param iterate: max number of iteration.\n :param xyzPulses: a list of three integers indicating the numbers of\n ...
[ { "param": "ham", "type": "QHam" }, { "param": "uGoal", "type": "Union[ndarray, List[ndarray]]" }, { "param": "tg", "type": "int" }, { "param": "iterate", "type": "int" }, { "param": "xyzPulses", "type": "List[int]" } ]
{ "returns": [ { "docstring": "a tuple containing the QJob list and infidelity list.", "docstring_tokens": [ "a", "tuple", "containing", "the", "QJob", "list", "and", "infidelity", "list", "." ], "type": null ...
fea727eb36c7086d269d7ae000c2362dfa892df5
baidu/Quanlse
Quanlse/remoteOptimizer.py
[ "Apache-2.0" ]
Python
remoteOptimizeCr
Tuple[QJob, float]
def remoteOptimizeCr(ham: QHam, aBound: Tuple[float, float] = None, tg: float = 200, maxIter: int = 5, targetInfidelity: float = 0.01) -> Tuple[QJob, float]: """ Optimize a superconducting Cross-Resonance gate by Quanlse Cloud Service. :param ham: the QHamiltonian object. :param aB...
Optimize a superconducting Cross-Resonance gate by Quanlse Cloud Service. :param ham: the QHamiltonian object. :param aBound: the optimization bound of pulse amplitude. :param tg: gate time. :param maxIter: max number of iteration. :param targetInfidelity: the target infidelity. :return: a...
Optimize a superconducting Cross-Resonance gate by Quanlse Cloud Service.
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def remoteOptimizeCr(ham: QHam, aBound: Tuple[float, float] = None, tg: float = 200, maxIter: int = 5, targetInfidelity: float = 0.01) -> Tuple[QJob, float]: args = [ham.dump()] kwargs = { "aBound": aBound, "tg": tg, "maxIter": maxIter, "targetInfidelity": ta...
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Optimize a superconducting Cross-Resonance gate by Quanlse Cloud Service.
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[ "\"\"\"\n Optimize a superconducting Cross-Resonance gate by Quanlse Cloud Service.\n\n :param ham: the QHamiltonian object.\n :param aBound: the optimization bound of pulse amplitude.\n :param tg: gate time.\n :param maxIter: max number of iteration.\n :param targetInfidelity: the target infideli...
[ { "param": "ham", "type": "QHam" }, { "param": "aBound", "type": "Tuple[float, float]" }, { "param": "tg", "type": "float" }, { "param": "maxIter", "type": "int" }, { "param": "targetInfidelity", "type": "float" } ]
{ "returns": [ { "docstring": "a tuple containing the return Hamiltonian and infidelity.", "docstring_tokens": [ "a", "tuple", "containing", "the", "return", "Hamiltonian", "and", "infidelity", "." ], "type": null ...
fea727eb36c7086d269d7ae000c2362dfa892df5
baidu/Quanlse
Quanlse/remoteOptimizer.py
[ "Apache-2.0" ]
Python
remoteOptimizeCz
Tuple[QJob, float]
def remoteOptimizeCz(ham: QHam, aBound: Tuple[float, float] = None, tg: float = 200, maxIter: int = 5, targetInfidelity: float = 0.01) -> Tuple[QJob, float]: """ Optimize a superconducting Controlled-Z gate by Quanlse Cloud Service. :param ham: the QHamiltonian object. :param aBoun...
Optimize a superconducting Controlled-Z gate by Quanlse Cloud Service. :param ham: the QHamiltonian object. :param aBound: the optimization bound of pulse amplitude. :param tg: gate time. :param maxIter: max number of iteration. :param targetInfidelity: the target infidelity. :return: a tu...
Optimize a superconducting Controlled-Z gate by Quanlse Cloud Service.
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def remoteOptimizeCz(ham: QHam, aBound: Tuple[float, float] = None, tg: float = 200, maxIter: int = 5, targetInfidelity: float = 0.01) -> Tuple[QJob, float]: args = [ham.dump()] kwargs = { "aBound": aBound, "tg": tg, "maxIter": maxIter, "targetInfidelity": ta...
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Optimize a superconducting Controlled-Z gate by Quanlse Cloud Service.
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[ "\"\"\"\n Optimize a superconducting Controlled-Z gate by Quanlse Cloud Service.\n\n :param ham: the QHamiltonian object.\n :param aBound: the optimization bound of pulse amplitude.\n :param tg: gate time.\n :param maxIter: max number of iteration.\n :param targetInfidelity: the target infidelity....
[ { "param": "ham", "type": "QHam" }, { "param": "aBound", "type": "Tuple[float, float]" }, { "param": "tg", "type": "float" }, { "param": "maxIter", "type": "int" }, { "param": "targetInfidelity", "type": "float" } ]
{ "returns": [ { "docstring": "a tuple containing the return Hamiltonian and infidelity.", "docstring_tokens": [ "a", "tuple", "containing", "the", "return", "Hamiltonian", "and", "infidelity", "." ], "type": null ...
fea727eb36c7086d269d7ae000c2362dfa892df5
baidu/Quanlse
Quanlse/remoteOptimizer.py
[ "Apache-2.0" ]
Python
remoteOptimizeISWAP
Tuple[QJob, float]
def remoteOptimizeISWAP(ham: QHam, aBound: Tuple[float, float] = None, tg: float = 200, maxIter: int = 5, targetInfidelity: float = 0.01) -> Tuple[QJob, float]: """ Optimize a superconducting iSWAP gate by Quanlse cloud service. :param ham: the QHamiltonian object. :param aBound...
Optimize a superconducting iSWAP gate by Quanlse cloud service. :param ham: the QHamiltonian object. :param aBound: the optimization bound of pulse amplitude. :param tg: gate time. :param maxIter: max number of iteration. :param targetInfidelity: the target infidelity. :return: a tuple con...
Optimize a superconducting iSWAP gate by Quanlse cloud service.
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def remoteOptimizeISWAP(ham: QHam, aBound: Tuple[float, float] = None, tg: float = 200, maxIter: int = 5, targetInfidelity: float = 0.01) -> Tuple[QJob, float]: args = [ham.dump()] kwargs = { "aBound": aBound, "tg": tg, "maxIter": maxIter, "targetInfidelit...
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Optimize a superconducting iSWAP gate by Quanlse cloud service.
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[ { "param": "ham", "type": "QHam" }, { "param": "aBound", "type": "Tuple[float, float]" }, { "param": "tg", "type": "float" }, { "param": "maxIter", "type": "int" }, { "param": "targetInfidelity", "type": "float" } ]
{ "returns": [ { "docstring": "a tuple containing the return Hamiltonian and infidelity.", "docstring_tokens": [ "a", "tuple", "containing", "the", "return", "Hamiltonian", "and", "infidelity", "." ], "type": null ...
fea727eb36c7086d269d7ae000c2362dfa892df5
baidu/Quanlse
Quanlse/remoteOptimizer.py
[ "Apache-2.0" ]
Python
remoteIonOptimize1Qubit
Tuple[float, float, ndarray]
def remoteIonOptimize1Qubit(axial: str, theta: float, tg: float) -> Tuple[float, float, ndarray]: """ Optimize a superconducting iSWAP gate by Quanlse cloud service. :param axial: the rotating axial, 'ionRx' or 'ionRy'. :param theta: the angle of the rotation operation. :param tg: gate time. :r...
Optimize a superconducting iSWAP gate by Quanlse cloud service. :param axial: the rotating axial, 'ionRx' or 'ionRy'. :param theta: the angle of the rotation operation. :param tg: gate time. :return: a tuple containing the return Hamiltonian and infidelity.
Optimize a superconducting iSWAP gate by Quanlse cloud service.
[ "Optimize", "a", "superconducting", "iSWAP", "gate", "by", "Quanlse", "cloud", "service", "." ]
def remoteIonOptimize1Qubit(axial: str, theta: float, tg: float) -> Tuple[float, float, ndarray]: args = [axial, theta, tg] kwargs = {} origin = rpcCall("Ion1Qubit", args, kwargs) return origin["a"], origin["b"], dictMatrixToNumpyMatrix(origin["qam"], complex)
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Optimize a superconducting iSWAP gate by Quanlse cloud service.
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{ "returns": [ { "docstring": "a tuple containing the return Hamiltonian and infidelity.", "docstring_tokens": [ "a", "tuple", "containing", "the", "return", "Hamiltonian", "and", "infidelity", "." ], "type": null ...
fea727eb36c7086d269d7ae000c2362dfa892df5
baidu/Quanlse
Quanlse/remoteOptimizer.py
[ "Apache-2.0" ]
Python
remoteIonMS
Tuple[Any, Any]
def remoteIonMS(ionNumber: int, atomMass: int, tg: float, omega: Tuple[float, float], ionIndex: Tuple[int, int], phononMode: str = 'axial', pulseWave: str = 'squareWave') -> Tuple[Any, Any]: """ Generate the Molmer-Sorensen gate in trapped ion :param ionNumber: the number of ions. :para...
Generate the Molmer-Sorensen gate in trapped ion :param ionNumber: the number of ions. :param atomMass: the atomic mass of the ion. :param tg: gate time. :param omega: 1-dimensional angular frequency of the potential trap. :param ionIndex: the index of the two ions. :param phononMode: the ...
Generate the Molmer-Sorensen gate in trapped ion
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def remoteIonMS(ionNumber: int, atomMass: int, tg: float, omega: Tuple[float, float], ionIndex: Tuple[int, int], phononMode: str = 'axial', pulseWave: str = 'squareWave') -> Tuple[Any, Any]: args = [ionNumber, atomMass, tg, omega, ionIndex] kwargs = { "phononMode": phononMode, "p...
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Generate the Molmer-Sorensen gate in trapped ion
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[ { "param": "ionNumber", "type": "int" }, { "param": "atomMass", "type": "int" }, { "param": "tg", "type": "float" }, { "param": "omega", "type": "Tuple[float, float]" }, { "param": "ionIndex", "type": "Tuple[int, int]" }, { "param": "phononMode", "...
{ "returns": [ { "docstring": "dict type result and ndarray type unitary.", "docstring_tokens": [ "dict", "type", "result", "and", "ndarray", "type", "unitary", "." ], "type": null } ], "raises": [], "params": [ ...
fea727eb36c7086d269d7ae000c2362dfa892df5
baidu/Quanlse
Quanlse/remoteOptimizer.py
[ "Apache-2.0" ]
Python
remoteIonGeneralMS
Tuple[Dict[str, Any], ndarray]
def remoteIonGeneralMS(gatePair: List[List[int]], args1: Tuple[int, int, float, float, str], args2: Tuple[int, float, float]) -> Tuple[Dict[str, Any], ndarray]: """ Generate general Molmer-Sorensen gate and GHZ state in trapped ion :param gatePair: the gate pair in ion chain. :pa...
Generate general Molmer-Sorensen gate and GHZ state in trapped ion :param gatePair: the gate pair in ion chain. :param args1: args1[0]: the number of ions; args1[1]: the atom mass or atom specie; args1[2]: the XY trapped potential frequency; args1[3]: the Z trapped potential frequency;...
Generate general Molmer-Sorensen gate and GHZ state in trapped ion
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def remoteIonGeneralMS(gatePair: List[List[int]], args1: Tuple[int, int, float, float, str], args2: Tuple[int, float, float]) -> Tuple[Dict[str, Any], ndarray]: args = [gatePair, args1, args2] kwargs = {} origin = rpcCall("IonGeneralMS", args, kwargs) return origin['result'], dict...
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Generate general Molmer-Sorensen gate and GHZ state in trapped ion
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[ "\"\"\"\n Generate general Molmer-Sorensen gate and GHZ state in trapped ion\n\n :param gatePair: the gate pair in ion chain.\n :param args1:\n args1[0]: the number of ions;\n args1[1]: the atom mass or atom specie;\n args1[2]: the XY trapped potential frequency;\n args1[3]: the Z trapped p...
[ { "param": "gatePair", "type": "List[List[int]]" }, { "param": "args1", "type": "Tuple[int, int, float, float, str]" }, { "param": "args2", "type": "Tuple[int, float, float]" } ]
{ "returns": [ { "docstring": "dict type result and ndarray type unitary.", "docstring_tokens": [ "dict", "type", "result", "and", "ndarray", "type", "unitary", "." ], "type": null } ], "raises": [], "params": [ ...
b6328962b069ad388c64ff90fcc2e95c0bda0e5f
baidu/Quanlse
Quanlse/ErrorMitigation/Utils/Visualization.py
[ "Apache-2.0" ]
Python
polarVectorToState
np.ndarray
def polarVectorToState(vec) -> np.ndarray: """ From the polar vector representation to the state representation. :param vec: polar vector, array_like, (3,) :return: density matrix: ndarray, (2, 2) """ ops = [FixedGate.X.getMatrix(), FixedGate.Y.getMatrix(), FixedGate.Z.getMatrix()] return (...
From the polar vector representation to the state representation. :param vec: polar vector, array_like, (3,) :return: density matrix: ndarray, (2, 2)
From the polar vector representation to the state representation.
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def polarVectorToState(vec) -> np.ndarray: ops = [FixedGate.X.getMatrix(), FixedGate.Y.getMatrix(), FixedGate.Z.getMatrix()] return (np.identity(2) + vec[0] * ops[0] + vec[1] * ops[1] + vec[2] * ops[2]) / 2
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From the polar vector representation to the state representation.
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[ "\"\"\"\n From the polar vector representation to the state representation.\n\n :param vec: polar vector, array_like, (3,)\n :return: density matrix: ndarray, (2, 2)\n \"\"\"" ]
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b6328962b069ad388c64ff90fcc2e95c0bda0e5f
baidu/Quanlse
Quanlse/ErrorMitigation/Utils/Visualization.py
[ "Apache-2.0" ]
Python
stateToPolarVector
List
def stateToPolarVector(state) -> List: """ From the state representation to the polar vector representation. :param state: state vector or density matrix :return: polar vector """ ops = [FixedGate.X.getMatrix(), FixedGate.Y.getMatrix(), FixedGate.Z.getMatrix()] return [expect(ops[i], state)...
From the state representation to the polar vector representation. :param state: state vector or density matrix :return: polar vector
From the state representation to the polar vector representation.
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def stateToPolarVector(state) -> List: ops = [FixedGate.X.getMatrix(), FixedGate.Y.getMatrix(), FixedGate.Z.getMatrix()] return [expect(ops[i], state) for i in range(3)]
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From the state representation to the polar vector representation.
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[ "\"\"\"\n From the state representation to the polar vector representation.\n\n :param state: state vector or density matrix\n :return: polar vector\n \"\"\"" ]
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b6328962b069ad388c64ff90fcc2e95c0bda0e5f
baidu/Quanlse
Quanlse/ErrorMitigation/Utils/Visualization.py
[ "Apache-2.0" ]
Python
plotZNESequences
null
def plotZNESequences(expectationsRescaled: List[List], expectationsExtrapolated: List[List], expectationsIdeal: List, fileName: str = None): """ Plot a figure that shows the extrapolated results and noise-rescaling results, with the X-axis representing the size of quantum gate sequences...
Plot a figure that shows the extrapolated results and noise-rescaling results, with the X-axis representing the size of quantum gate sequences and the Y-axis representing the expectation values of the given mechanical quantity. :param expectationsRescaled: a series of noise-rescaling expectation value...
Plot a figure that shows the extrapolated results and noise-rescaling results, with the X-axis representing the size of quantum gate sequences and the Y-axis representing the expectation values of the given mechanical quantity.
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def plotZNESequences(expectationsRescaled: List[List], expectationsExtrapolated: List[List], expectationsIdeal: List, fileName: str = None): expectationsRescaled = np.array(expectationsRescaled).transpose() expectationsExtrapolated = np.array(expectationsExtrapolated).transpose() numSeq...
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Plot a figure that shows the extrapolated results and noise-rescaling results, with the X-axis representing the size of quantum gate sequences and the Y-axis representing the expectation values of the given mechanical quantity.
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[ "\"\"\"\n Plot a figure that shows the extrapolated results and noise-rescaling results, with the X-axis\n representing the size of quantum gate sequences and the Y-axis representing the expectation\n values of the given mechanical quantity.\n\n :param expectationsRescaled: a series of noise-rescaling e...
[ { "param": "expectationsRescaled", "type": "List[List]" }, { "param": "expectationsExtrapolated", "type": "List[List]" }, { "param": "expectationsIdeal", "type": "List" }, { "param": "fileName", "type": "str" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "expectationsRescaled", "type": "List[List]", "docstring": "a series of noise-rescaling expectation values with shape [n, ...
b6328962b069ad388c64ff90fcc2e95c0bda0e5f
baidu/Quanlse
Quanlse/ErrorMitigation/Utils/Visualization.py
[ "Apache-2.0" ]
Python
plotRescaleHamiltonianPulse
<not_specific>
def plotRescaleHamiltonianPulse(rescaleCoes: List[float], hamList: List[QHamiltonian], numChannel: int, figsize: tuple = (12, 6), title=None): """ Plot each pulse channel of a series of time-rescaling Hamiltonians. Suppose len(rescaleCoes)=r and numChannel=n, this function wi...
Plot each pulse channel of a series of time-rescaling Hamiltonians. Suppose len(rescaleCoes)=r and numChannel=n, this function will show a figure including r*c subfigures which are arranged in "r" rows and "c" columns. :param rescaleCoes: rescaling coefficients :param hamList: Hamiltonian list who...
Plot each pulse channel of a series of time-rescaling Hamiltonians. Suppose len(rescaleCoes)=r and numChannel=n, this function will show a figure including r*c subfigures which are arranged in "r" rows and "c" columns.
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def plotRescaleHamiltonianPulse(rescaleCoes: List[float], hamList: List[QHamiltonian], numChannel: int, figsize: tuple = (12, 6), title=None): fig = plt.figure(figsize=figsize) axes = [] colorList = plt.rcParams['axes.prop_cycle'].by_key()['color'] if len(rescaleCoes) != ...
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Plot each pulse channel of a series of time-rescaling Hamiltonians.
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[ "\"\"\"\n Plot each pulse channel of a series of time-rescaling Hamiltonians. Suppose len(rescaleCoes)=r and numChannel=n,\n this function will show a figure including r*c subfigures which are\n arranged in \"r\" rows and \"c\" columns.\n\n :param rescaleCoes: rescaling coefficients\n :param hamList:...
[ { "param": "rescaleCoes", "type": "List[float]" }, { "param": "hamList", "type": "List[QHamiltonian]" }, { "param": "numChannel", "type": "int" }, { "param": "figsize", "type": "tuple" }, { "param": "title", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "rescaleCoes", "type": "List[float]", "docstring": null, "docstring_tokens": [ "None" ], "defaul...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
dim
int
def dim(self) -> int: """ Return the dimension of the Hilbert space. """ _dim = 1 if isinstance(self.sysLevel, int): _dim = self.sysLevel ** self.subSysNum elif isinstance(self.sysLevel, list): _dim = 1 for level in self.sysLevel: ...
Return the dimension of the Hilbert space.
Return the dimension of the Hilbert space.
[ "Return", "the", "dimension", "of", "the", "Hilbert", "space", "." ]
def dim(self) -> int: _dim = 1 if isinstance(self.sysLevel, int): _dim = self.sysLevel ** self.subSysNum elif isinstance(self.sysLevel, list): _dim = 1 for level in self.sysLevel: _dim = _dim * level return _dim
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Return the dimension of the Hilbert space.
[ "Return", "the", "dimension", "of", "the", "Hilbert", "space", "." ]
[ "\"\"\"\n Return the dimension of the Hilbert space.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
qubitFreq
Dict[int, Union[int, float]]
def qubitFreq(self) -> Dict[int, Union[int, float]]: """ Return the eigenfrequency of each qubit in the system. """ return self._qubitFreq
Return the eigenfrequency of each qubit in the system.
Return the eigenfrequency of each qubit in the system.
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def qubitFreq(self) -> Dict[int, Union[int, float]]: return self._qubitFreq
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Return the eigenfrequency of each qubit in the system.
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[ "\"\"\"\n Return the eigenfrequency of each qubit in the system.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
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18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
qubitFreq
null
def qubitFreq(self, value: Dict[int, Union[int, float]]): """ Return the eigen frequency of each qubit in the system, in 2 * pi * GHz. """ if len(value) != self.subSysNum: raise Error.ArgumentError("The number of the frequencies and the number of qubits are not the same.") ...
Return the eigen frequency of each qubit in the system, in 2 * pi * GHz.
Return the eigen frequency of each qubit in the system, in 2 * pi * GHz.
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def qubitFreq(self, value: Dict[int, Union[int, float]]): if len(value) != self.subSysNum: raise Error.ArgumentError("The number of the frequencies and the number of qubits are not the same.") self._qubitFreq = value self.createQHamiltonian(frameMode=self.frameMode)
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Return the eigen frequency of each qubit in the system, in 2 * pi * GHz.
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[ "\"\"\"\n Return the eigen frequency of each qubit in the system, in 2 * pi * GHz.\n \"\"\"" ]
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18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
driveFreq
Dict[int, Union[int, float]]
def driveFreq(self) -> Dict[int, Union[int, float]]: """ Return the drive frequency of each qubit in the system. """ return self._qubitFreq
Return the drive frequency of each qubit in the system.
Return the drive frequency of each qubit in the system.
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def driveFreq(self) -> Dict[int, Union[int, float]]: return self._qubitFreq
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Return the drive frequency of each qubit in the system.
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[ "\"\"\"\n Return the drive frequency of each qubit in the system.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
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18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
driveFreq
null
def driveFreq(self, value: Dict[int, Union[int, float]]): """ Return the drive frequency of each qubit in the system, in 2 * pi * GHz. """ if len(value) != self.subSysNum: raise Error.ArgumentError("The number of the frequencies and the number of qubits are not the same.") ...
Return the drive frequency of each qubit in the system, in 2 * pi * GHz.
Return the drive frequency of each qubit in the system, in 2 * pi * GHz.
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def driveFreq(self, value: Dict[int, Union[int, float]]): if len(value) != self.subSysNum: raise Error.ArgumentError("The number of the frequencies and the number of qubits are not the same.") self._driveFreq = value self.createQHamiltonian(frameMode=self.frameMode)
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Return the drive frequency of each qubit in the system, in 2 * pi * GHz.
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[ "\"\"\"\n Return the drive frequency of each qubit in the system, in 2 * pi * GHz.\n \"\"\"" ]
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18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
qubitAnharm
Dict[int, Union[int, float]]
def qubitAnharm(self) -> Dict[int, Union[int, float]]: """ Return the anharmonicity of each qubit in the system. """ return self._qubitAnharm
Return the anharmonicity of each qubit in the system.
Return the anharmonicity of each qubit in the system.
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def qubitAnharm(self) -> Dict[int, Union[int, float]]: return self._qubitAnharm
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Return the anharmonicity of each qubit in the system.
[ "Return", "the", "anharmonicity", "of", "each", "qubit", "in", "the", "system", "." ]
[ "\"\"\"\n Return the anharmonicity of each qubit in the system.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
couplingMap
null
def couplingMap(self, value: Optional[Dict[Tuple, Union[int, float]]]): """ Return the coupling structure of the system. """ if self.couplingMap is not None: indexList = [index for pair in value for index in pair] for index in indexList: if index n...
Return the coupling structure of the system.
Return the coupling structure of the system.
[ "Return", "the", "coupling", "structure", "of", "the", "system", "." ]
def couplingMap(self, value: Optional[Dict[Tuple, Union[int, float]]]): if self.couplingMap is not None: indexList = [index for pair in value for index in pair] for index in indexList: if index not in range(self.subSysNum+1): raise Error.ArgumentError(...
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Return the coupling structure of the system.
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[ "\"\"\"\n Return the coupling structure of the system.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "Optional[Dict[Tuple, Union[int, float]]]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "Optional[Dict[Tuple, Union[int, float]]]", "docstr...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
T1
Optional[Dict[int, Union[int, float, None]]]
def T1(self) -> Optional[Dict[int, Union[int, float, None]]]: """ Return the relaxation time T1 for each qubit. """ return self._T1
Return the relaxation time T1 for each qubit.
Return the relaxation time T1 for each qubit.
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def T1(self) -> Optional[Dict[int, Union[int, float, None]]]: return self._T1
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Return the relaxation time T1 for each qubit.
[ "Return", "the", "relaxation", "time", "T1", "for", "each", "qubit", "." ]
[ "\"\"\"\n Return the relaxation time T1 for each qubit.\n \"\"\"" ]
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18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
T1
null
def T1(self, value: Optional[Dict[int, Union[int, float, None]]]): """ Setter for the relaxation time T1 for each qubit. """ if value is not None: for index, t1 in value.items(): if t1 < 0: raise Error.ArgumentError("The value of T1 should ...
Setter for the relaxation time T1 for each qubit.
Setter for the relaxation time T1 for each qubit.
[ "Setter", "for", "the", "relaxation", "time", "T1", "for", "each", "qubit", "." ]
def T1(self, value: Optional[Dict[int, Union[int, float, None]]]): if value is not None: for index, t1 in value.items(): if t1 < 0: raise Error.ArgumentError("The value of T1 should be a positive real number.") if index not in range(self.subSysNum)...
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Setter for the relaxation time T1 for each qubit.
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[ "\"\"\"\n Setter for the relaxation time T1 for each qubit.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "Optional[Dict[int, Union[int, float, None]]]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "Optional[Dict[int, Union[int, float, None]]]", "do...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
T2
Optional[Dict[int, Union[int, float, None]]]
def T2(self) -> Optional[Dict[int, Union[int, float, None]]]: """ Return the relaxation time T2 for each qubit. """ return self._T2
Return the relaxation time T2 for each qubit.
Return the relaxation time T2 for each qubit.
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def T2(self) -> Optional[Dict[int, Union[int, float, None]]]: return self._T2
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Return the relaxation time T2 for each qubit.
[ "Return", "the", "relaxation", "time", "T2", "for", "each", "qubit", "." ]
[ "\"\"\"\n Return the relaxation time T2 for each qubit.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
T2
null
def T2(self, value: Optional[Dict[int, Union[int, float, None]]]): """ Setter for the relaxation time T2 for each qubit. """ if value is not None: for index, t2 in value.items(): if t2 < 0: raise Error.ArgumentError("The value of T1 should ...
Setter for the relaxation time T2 for each qubit.
Setter for the relaxation time T2 for each qubit.
[ "Setter", "for", "the", "relaxation", "time", "T2", "for", "each", "qubit", "." ]
def T2(self, value: Optional[Dict[int, Union[int, float, None]]]): if value is not None: for index, t2 in value.items(): if t2 < 0: raise Error.ArgumentError("The value of T1 should be a positive real number.") if index not in range(self.subSysNum)...
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Setter for the relaxation time T2 for each qubit.
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[ "\"\"\"\n Setter for the relaxation time T2 for each qubit.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "Optional[Dict[int, Union[int, float, None]]]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "Optional[Dict[int, Union[int, float, None]]]", "do...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
diagMat
ndarray
def diagMat(self) -> ndarray: """ Return the diagonal matrix of the Hamiltonian. :return: a diagonal matrix """ levelList = [] identityList = [] # Define the list of different identity matrix for each subsystem if isinstance(self.sysLevel, int): ...
Return the diagonal matrix of the Hamiltonian. :return: a diagonal matrix
Return the diagonal matrix of the Hamiltonian.
[ "Return", "the", "diagonal", "matrix", "of", "the", "Hamiltonian", "." ]
def diagMat(self) -> ndarray: levelList = [] identityList = [] if isinstance(self.sysLevel, int): levelList = [self.sysLevel for _ in range(self.subSysNum)] identityList = [identity(self.sysLevel) for _ in range(self.subSysNum)] elif isinstance(self.sysLevel, list...
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Return the diagonal matrix of the Hamiltonian.
[ "Return", "the", "diagonal", "matrix", "of", "the", "Hamiltonian", "." ]
[ "\"\"\"\n Return the diagonal matrix of the Hamiltonian.\n\n :return: a diagonal matrix\n \"\"\"", "# Define the list of different identity matrix for each subsystem", "# Initialize the diagonal term", "# Add drift terms to the diagonal term" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "a diagonal matrix", "docstring_tokens": [ "a", "diagonal", "matrix" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], ...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
_generateTimeIndepCoupTerm
None
def _generateTimeIndepCoupTerm(self, ham: QHamiltonian) -> None: r""" Generate time-independent coupling terms for ith qubit and jth qubit. :math:`H_{coup} = a_{i} a_{j}^\dagger + a_{i}^\dagger a_j` :param ham: The QHamiltonian object. :return: None """ # Generat...
r""" Generate time-independent coupling terms for ith qubit and jth qubit. :math:`H_{coup} = a_{i} a_{j}^\dagger + a_{i}^\dagger a_j` :param ham: The QHamiltonian object. :return: None
r""" Generate time-independent coupling terms for ith qubit and jth qubit.
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def _generateTimeIndepCoupTerm(self, ham: QHamiltonian) -> None: for index, value in self.couplingMap.items(): ham.addCoupling(onSubSys=[index[0], index[1]], g=value)
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r""" Generate time-independent coupling terms for ith qubit and jth qubit.
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[ "r\"\"\"\n Generate time-independent coupling terms for ith qubit and jth qubit.\n :math:`H_{coup} = a_{i} a_{j}^\\dagger + a_{i}^\\dagger a_j`\n\n :param ham: The QHamiltonian object.\n :return: None\n \"\"\"", "# Generate the time independent coupling terms" ]
[ { "param": "self", "type": null }, { "param": "ham", "type": "QHamiltonian" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
_generateCoupTerm
None
def _generateCoupTerm(self, ham: QHamiltonian) -> None: r""" Return the time-dependent coupling terms of ith qubit and jth qubit. :math:`H_{coup} = (a_i^\dagger a_j + a_i a_j^\dagger) \cos(\omega_{qi} - \omega_{qj})t + (a_i^\dagger a_j - a_i a_j^\dagger) i \sin(\omega_{qi} - \omega_...
r""" Return the time-dependent coupling terms of ith qubit and jth qubit. :math:`H_{coup} = (a_i^\dagger a_j + a_i a_j^\dagger) \cos(\omega_{qi} - \omega_{qj})t + (a_i^\dagger a_j - a_i a_j^\dagger) i \sin(\omega_{qi} - \omega_{qj})t` :param ham: a QHamiltonian object. :ret...
r""" Return the time-dependent coupling terms of ith qubit and jth qubit.
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def _generateCoupTerm(self, ham: QHamiltonian) -> None: for index, value in self.couplingMap.items(): deltaOmega = self.qubitFreq[index[0]] - self.qubitFreq[index[1]] ai = QOperator('ai') aj = QOperator('aj') adagi = QOperator('adagi') adagj = QOperato...
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r""" Return the time-dependent coupling terms of ith qubit and jth qubit.
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[ "r\"\"\"\n Return the time-dependent coupling terms of ith qubit and jth qubit.\n\n :math:`H_{coup} = (a_i^\\dagger a_j + a_i a_j^\\dagger) \\cos(\\omega_{qi} - \\omega_{qj})t\n + (a_i^\\dagger a_j - a_i a_j^\\dagger) i \\sin(\\omega_{qi} - \\omega_{qj})t`\n\n :param ham: a QHamilton...
[ { "param": "self", "type": null }, { "param": "ham", "type": "QHamiltonian" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
_setDecoherence
None
def _setDecoherence(self, ham: QHamiltonian) -> None: r""" Define the collapse operators accounts for the decoherence noise for solving Lindblad master equation of the open system evolution. :math:`C_{\rm relaxation} = \frac{1}{\sqrt{T1}} a` :math:`C_{\rm dephasing} = \frac{1}{\...
r""" Define the collapse operators accounts for the decoherence noise for solving Lindblad master equation of the open system evolution. :math:`C_{\rm relaxation} = \frac{1}{\sqrt{T1}} a` :math:`C_{\rm dephasing} = \frac{1}{\sqrt{T2}} a^\dagger a` :param ham: The QHamiltonian o...
r""" Define the collapse operators accounts for the decoherence noise for solving Lindblad master equation of the open system evolution.
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def _setDecoherence(self, ham: QHamiltonian) -> None: levelList = [] if isinstance(self.sysLevel, list): levelList = self.sysLevel elif isinstance(self.sysLevel, int): levelList = [self.sysLevel for _ in range(self.subSysNum)] if self.T1 is None and self.T2 is Non...
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r""" Define the collapse operators accounts for the decoherence noise for solving Lindblad master equation of the open system evolution.
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[ "r\"\"\"\n Define the collapse operators accounts for the decoherence noise\n for solving Lindblad master equation of the open system evolution.\n\n :math:`C_{\\rm relaxation} = \\frac{1}{\\sqrt{T1}} a`\n :math:`C_{\\rm dephasing} = \\frac{1}{\\sqrt{T2}} a^\\dagger a`\n\n :param h...
[ { "param": "self", "type": null }, { "param": "ham", "type": "QHamiltonian" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
createQHamiltonian
QHamiltonian
def createQHamiltonian(self, frameMode: str = "rot") -> QHamiltonian: r""" Generate a QHamiltonian object based on the physics model and a QJob object. :param frameMode: the rotating frame we choose. The default setting is rotating frame being in the qubits frequencies. :ret...
r""" Generate a QHamiltonian object based on the physics model and a QJob object. :param frameMode: the rotating frame we choose. The default setting is rotating frame being in the qubits frequencies. :return: a QHamiltonian object.
r""" Generate a QHamiltonian object based on the physics model and a QJob object.
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def createQHamiltonian(self, frameMode: str = "rot") -> QHamiltonian: ham = QHamiltonian(subSysNum=self.subSysNum, sysLevel=self.sysLevel, dt=self.dt) if frameMode == "lab": self._generateDrift(ham, frameMode='lab') if self.couplingMap is not None: self._generateT...
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r""" Generate a QHamiltonian object based on the physics model and a QJob object.
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[ "r\"\"\"\n Generate a QHamiltonian object based on the physics model and a QJob object.\n\n :param frameMode: the rotating frame we choose. The default setting is rotating frame being in the qubits\n frequencies.\n :return: a QHamiltonian object.\n \"\"\"", "# Initialize the...
[ { "param": "self", "type": null }, { "param": "frameMode", "type": "str" } ]
{ "returns": [ { "docstring": "a QHamiltonian object.", "docstring_tokens": [ "a", "QHamiltonian", "object", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "do...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
simulate
QResult
def simulate(self, job: QJob = None, state0: ndarray = None, jobList: QJobList = None, measure: List[int] = None, shot: int = None, options: Any = None) -> QResult: """ Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and ...
Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and batch-job processing. :param job: the QJob object to simulate. :param state0: the initial state vector. If None is given, this function will return the time-ordered ...
Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and batch-job processing.
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def simulate(self, job: QJob = None, state0: ndarray = None, jobList: QJobList = None, measure: List[int] = None, shot: int = None, options: Any = None) -> QResult: if self.frameMode == 'lab': if state0 is None: state0 = basis(self.dim, 0) if shot is None...
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Calculate the unitary evolution operator with a given Hamiltonian.
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[ "\"\"\"\n Calculate the unitary evolution operator with a given Hamiltonian. This function supports\n both single-job and batch-job processing.\n\n :param job: the QJob object to simulate.\n :param state0: the initial state vector. If None is given, this function will return the time-ord...
[ { "param": "self", "type": null }, { "param": "job", "type": "QJob" }, { "param": "state0", "type": "ndarray" }, { "param": "jobList", "type": "QJobList" }, { "param": "measure", "type": "List[int]" }, { "param": "shot", "type": "int" }, { ...
{ "returns": [ { "docstring": "result dictionary (or a list of result dictionaries when ``jobList`` is provided)\nThis function does provide the option of simulating on local devices. However, Quanlse also provides\ncloud computing services which are significantly faster.\n\nExample 1** (single-job processi...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
driveStrength
Dict[int, Any]
def driveStrength(self) -> Dict[int, Any]: """ Drive strength of readout pulse. """ return self._driveStrength
Drive strength of readout pulse.
Drive strength of readout pulse.
[ "Drive", "strength", "of", "readout", "pulse", "." ]
def driveStrength(self) -> Dict[int, Any]: return self._driveStrength
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Drive strength of readout pulse.
[ "Drive", "strength", "of", "readout", "pulse", "." ]
[ "\"\"\"\n Drive strength of readout pulse.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
driveStrength
null
def driveStrength(self, value: Dict[int, Any]): """ Define the drive strength of readout pulse. """ self._driveStrength = value
Define the drive strength of readout pulse.
Define the drive strength of readout pulse.
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def driveStrength(self, value: Dict[int, Any]): self._driveStrength = value
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Define the drive strength of readout pulse.
[ "Define", "the", "drive", "strength", "of", "readout", "pulse", "." ]
[ "\"\"\"\n Define the drive strength of readout pulse.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "Dict[int, Any]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "Dict[int, Any]", "docstring": null, "docstri...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
driveFreq
null
def driveFreq(self, value: Dict[int, float]): """ Define the drive frequencies of readout pulse. """ self._driveFreq = value
Define the drive frequencies of readout pulse.
Define the drive frequencies of readout pulse.
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def driveFreq(self, value: Dict[int, float]): self._driveFreq = value
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Define the drive frequencies of readout pulse.
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[ "\"\"\"\n Define the drive frequencies of readout pulse.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "Dict[int, float]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "Dict[int, float]", "docstring": null, "docst...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
loFreq
<not_specific>
def loFreq(self): """ Carrier frequency generated by the local oscillator of signal demodulation. """ return self._loFreq
Carrier frequency generated by the local oscillator of signal demodulation.
Carrier frequency generated by the local oscillator of signal demodulation.
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def loFreq(self): return self._loFreq
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Carrier frequency generated by the local oscillator of signal demodulation.
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[ "\"\"\"\n Carrier frequency generated by the local oscillator of signal demodulation.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
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18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
loFreq
null
def loFreq(self, value: float): """ Set the carrier frequency generated by the local oscillator for signal demodulation. """ self._loFreq = value
Set the carrier frequency generated by the local oscillator for signal demodulation.
Set the carrier frequency generated by the local oscillator for signal demodulation.
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def loFreq(self, value: float): self._loFreq = value
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Set the carrier frequency generated by the local oscillator for signal demodulation.
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[ "\"\"\"\n Set the carrier frequency generated by the local oscillator for signal demodulation.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "float" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "float", "docstring": null, "docstring_tokens...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
readoutPulse
ReadoutPulse
def readoutPulse(self) -> ReadoutPulse: """ The multiplexing pulse data for qubit readout. """ return self._readoutPulse
The multiplexing pulse data for qubit readout.
The multiplexing pulse data for qubit readout.
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def readoutPulse(self) -> ReadoutPulse: return self._readoutPulse
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The multiplexing pulse data for qubit readout.
[ "The", "multiplexing", "pulse", "data", "for", "qubit", "readout", "." ]
[ "\"\"\"\n The multiplexing pulse data for qubit readout.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
readoutPulse
null
def readoutPulse(self, value: ReadoutPulse): """ Set the measure channel for the readout """ self._readoutPulse = value
Set the measure channel for the readout
Set the measure channel for the readout
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def readoutPulse(self, value: ReadoutPulse): self._readoutPulse = value
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Set the measure channel for the readout
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[ "\"\"\"\n Set the measure channel for the readout\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "ReadoutPulse" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "ReadoutPulse", "docstring": null, "docstring...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
_createHam
QHamiltonian
def _createHam(self, idx: int, driveFreq: Union[int, float]) -> QHamiltonian: """ Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency. :param idx: index of the qubit. :param driveFreq: drive frequency. :return: QHamiltonian i...
Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency. :param idx: index of the qubit. :param driveFreq: drive frequency. :return: QHamiltonian in the rotating frame.
Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency.
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def _createHam(self, idx: int, driveFreq: Union[int, float]) -> QHamiltonian: qubitFreq = self.pulseModel.qubitFreq qubitAnharm = self.pulseModel.qubitAnharm resonatorFreq = self.resonatorFreq qubitLevel = self.pulseModel.sysLevel cList = {1: [sqrt(self.dissipation) * a(self.leve...
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Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency.
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[ "\"\"\"\n Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency.\n\n :param idx: index of the qubit.\n :param driveFreq: drive frequency.\n\n :return: QHamiltonian in the rotating frame.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "idx", "type": "int" }, { "param": "driveFreq", "type": "Union[int, float]" } ]
{ "returns": [ { "docstring": "QHamiltonian in the rotating frame.", "docstring_tokens": [ "QHamiltonian", "in", "the", "rotating", "frame", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "self", ...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
_createHamLab
QHamiltonian
def _createHamLab(self, idx: int) -> QHamiltonian: """ Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency. :param idx: index of the qubit. :return: QHamiltonian in the lab frame. """ # Extract information from Pulse...
Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency. :param idx: index of the qubit. :return: QHamiltonian in the lab frame.
Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency.
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def _createHamLab(self, idx: int) -> QHamiltonian: qubitFreq = self.pulseModel.qubitFreq qubitAnharm = self.pulseModel.qubitAnharm resonatorFreq = self.resonatorFreq qubitLevel = self.pulseModel.sysLevel cList = {1: [sqrt(self.dissipation) * a(self.level)]} ham = QHamilto...
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Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency.
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[ "\"\"\"\n Return the hamiltonian of qubit-resonator circuit model according to the qubit index and drive frequency.\n\n :param idx: index of the qubit.\n\n :return: QHamiltonian in the lab frame.\n \"\"\"", "# Extract information from PulseModel object", "# Create lab frame QHamilton...
[ { "param": "self", "type": null }, { "param": "idx", "type": "int" } ]
{ "returns": [ { "docstring": "QHamiltonian in the lab frame.", "docstring_tokens": [ "QHamiltonian", "in", "the", "lab", "frame", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": nu...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
_readoutJob
QJob
def _readoutJob(self, amp: Union[int, float], duration: Union[int, float]) -> QJob: """ Return readout pulse in rotating frame at driving frequency. :param amp: amplitude of the readout job. :param duration: the duration of the pulse. :return: QJob. """ qubitLev...
Return readout pulse in rotating frame at driving frequency. :param amp: amplitude of the readout job. :param duration: the duration of the pulse. :return: QJob.
Return readout pulse in rotating frame at driving frequency.
[ "Return", "readout", "pulse", "in", "rotating", "frame", "at", "driving", "frequency", "." ]
def _readoutJob(self, amp: Union[int, float], duration: Union[int, float]) -> QJob: qubitLevel = self.pulseModel.sysLevel job = QJob(subSysNum=2, sysLevel=[qubitLevel, self.level], dt=self.dt) wave = square(t=duration, a=amp) job.addWave(operators=driveX, onSubSys=1, waves=wave, t0=0.) ...
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Return readout pulse in rotating frame at driving frequency.
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[ "\"\"\"\n Return readout pulse in rotating frame at driving frequency.\n\n :param amp: amplitude of the readout job.\n :param duration: the duration of the pulse.\n\n :return: QJob.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "amp", "type": "Union[int, float]" }, { "param": "duration", "type": "Union[int, float]" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
18c9d5c0881de60689cb0d4dcf0e74418d41f043
baidu/Quanlse
Quanlse/Simulator/__init__.py
[ "Apache-2.0" ]
Python
simulate
Dict
def simulate(self, duration: Union[int, float], resIdx: Optional[List[int]] = None, state: 'str' = 'ground') -> Dict: """ Simulate the state evolution of the qubit-resonator system using Jaynes-Cumming model. :param duration: pulse duration of the measurement. :param re...
Simulate the state evolution of the qubit-resonator system using Jaynes-Cumming model. :param duration: pulse duration of the measurement. :param resIdx: indexes of the resonator the pulse acted on. :param state: qubit state prepared in ground state or in excited state, Optional parame...
Simulate the state evolution of the qubit-resonator system using Jaynes-Cumming model.
[ "Simulate", "the", "state", "evolution", "of", "the", "qubit", "-", "resonator", "system", "using", "Jaynes", "-", "Cumming", "model", "." ]
def simulate(self, duration: Union[int, float], resIdx: Optional[List[int]] = None, state: 'str' = 'ground') -> Dict: if self._readoutPulse is None: raise Error.ArgumentError("You need to define object of class: ReadoutPulse") k = self.conversionLoss kappa = self.dis...
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Simulate the state evolution of the qubit-resonator system using Jaynes-Cumming model.
[ "Simulate", "the", "state", "evolution", "of", "the", "qubit", "-", "resonator", "system", "using", "Jaynes", "-", "Cumming", "model", "." ]
[ "\"\"\"\n Simulate the state evolution of the qubit-resonator system using Jaynes-Cumming model.\n\n :param duration: pulse duration of the measurement.\n :param resIdx: indexes of the resonator the pulse acted on.\n :param state: qubit state prepared in ground state or in excited state,...
[ { "param": "self", "type": null }, { "param": "duration", "type": "Union[int, float]" }, { "param": "resIdx", "type": "Optional[List[int]]" }, { "param": "state", "type": "'str'" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
f63c8add1e51320a2ccf4e51a96545cf900c9ffa
baidu/Quanlse
Quanlse/Scheduler/Ion/DefaultPulseGenerator.py
[ "Apache-2.0" ]
Python
generateIon1Qubit
QJob
def generateIon1Qubit(cirLine: CircuitLine = None, scheduler: 'SchedulerIon' = None) -> QJob: """ Default generator for ion single-qubit gates. :param cirLine: input circuit line object :param scheduler: input scheduler object :return: a returned QJob object """ job = QJob(subSysNum=schedul...
Default generator for ion single-qubit gates. :param cirLine: input circuit line object :param scheduler: input scheduler object :return: a returned QJob object
Default generator for ion single-qubit gates.
[ "Default", "generator", "for", "ion", "single", "-", "qubit", "gates", "." ]
def generateIon1Qubit(cirLine: CircuitLine = None, scheduler: 'SchedulerIon' = None) -> QJob: job = QJob(subSysNum=scheduler.subSysNum, sysLevel=2, dt=scheduler.dt) qLabel = cirLine.qRegIndexList matrixNumber = cirLine.data.getMatrix() theta = arccos(matrixNumber[0][0]) theta = theta.real if cir...
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Default generator for ion single-qubit gates.
[ "Default", "generator", "for", "ion", "single", "-", "qubit", "gates", "." ]
[ "\"\"\"\n Default generator for ion single-qubit gates.\n\n :param cirLine: input circuit line object\n :param scheduler: input scheduler object\n :return: a returned QJob object\n \"\"\"" ]
[ { "param": "cirLine", "type": "CircuitLine" }, { "param": "scheduler", "type": "'SchedulerIon'" } ]
{ "returns": [ { "docstring": "a returned QJob object", "docstring_tokens": [ "a", "returned", "QJob", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "cirLine", "type": "CircuitLine", "docstring": "inp...
f63c8add1e51320a2ccf4e51a96545cf900c9ffa
baidu/Quanlse
Quanlse/Scheduler/Ion/DefaultPulseGenerator.py
[ "Apache-2.0" ]
Python
generateMS
QJob
def generateMS(cirLine: CircuitLine = None, scheduler: 'SchedulerIon' = None) -> QJob: """ Default generator for M-S gate. :param cirLine: input circuit line object :param scheduler: input scheduler object :return: a returned QJob object """ if 5 < scheduler.dt < 15: job = QJob(subS...
Default generator for M-S gate. :param cirLine: input circuit line object :param scheduler: input scheduler object :return: a returned QJob object
Default generator for M-S gate.
[ "Default", "generator", "for", "M", "-", "S", "gate", "." ]
def generateMS(cirLine: CircuitLine = None, scheduler: 'SchedulerIon' = None) -> QJob: if 5 < scheduler.dt < 15: job = QJob(subSysNum=scheduler.subSysNum, sysLevel=2, dt=scheduler.dt) qLabel = cirLine.qRegIndexList gatePair = [[qLabel[0], qLabel[1]]] args1 = (scheduler.subSysNum, 171...
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Default generator for M-S gate.
[ "Default", "generator", "for", "M", "-", "S", "gate", "." ]
[ "\"\"\"\n Default generator for M-S gate.\n\n :param cirLine: input circuit line object\n :param scheduler: input scheduler object\n :return: a returned QJob object\n \"\"\"", "\"\"\"\n For parameter args1, scheduler.subSysNum is the total ion in chain.\n And simply, we fix the trappe...
[ { "param": "cirLine", "type": "CircuitLine" }, { "param": "scheduler", "type": "'SchedulerIon'" } ]
{ "returns": [ { "docstring": "a returned QJob object", "docstring_tokens": [ "a", "returned", "QJob", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "cirLine", "type": "CircuitLine", "docstring": "inp...
f63c8add1e51320a2ccf4e51a96545cf900c9ffa
baidu/Quanlse
Quanlse/Scheduler/Ion/DefaultPulseGenerator.py
[ "Apache-2.0" ]
Python
defaultPulseGenerator
SchedulerPulseGenerator
def defaultPulseGenerator() -> SchedulerPulseGenerator: """ Default pulse generator for ion-trap qubit :return: returned generator object """ generator = SchedulerPulseGenerator() # Add the generator for single qubit gates gateList1q = ['X', 'Y', 'RX', 'RY'] generator.addGenerator(gate...
Default pulse generator for ion-trap qubit :return: returned generator object
Default pulse generator for ion-trap qubit
[ "Default", "pulse", "generator", "for", "ion", "-", "trap", "qubit" ]
def defaultPulseGenerator() -> SchedulerPulseGenerator: generator = SchedulerPulseGenerator() gateList1q = ['X', 'Y', 'RX', 'RY'] generator.addGenerator(gateList1q, generateIon1Qubit) generator.addGenerator(['MS'], generateMS) return generator
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Default pulse generator for ion-trap qubit
[ "Default", "pulse", "generator", "for", "ion", "-", "trap", "qubit" ]
[ "\"\"\"\n Default pulse generator for ion-trap qubit\n\n :return: returned generator object\n \"\"\"", "# Add the generator for single qubit gates", "# Add the generator for MS gates" ]
[]
{ "returns": [ { "docstring": "returned generator object", "docstring_tokens": [ "returned", "generator", "object" ], "type": null } ], "raises": [], "params": [], "outlier_params": [], "others": [] }
8b41f6c09e1559adb48ca222975ba46d59b49a30
baidu/Quanlse
Quanlse/QOperator.py
[ "Apache-2.0" ]
Python
name
null
def name(self, name: str): """ Modify the name of the operator. :param name: name to be changed to """ if not isinstance(name, str): raise Error.ArgumentError("name must be a str!") self._name = name
Modify the name of the operator. :param name: name to be changed to
Modify the name of the operator.
[ "Modify", "the", "name", "of", "the", "operator", "." ]
def name(self, name: str): if not isinstance(name, str): raise Error.ArgumentError("name must be a str!") self._name = name
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Modify the name of the operator.
[ "Modify", "the", "name", "of", "the", "operator", "." ]
[ "\"\"\"\n Modify the name of the operator.\n\n :param name: name to be changed to\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "name", "type": "str" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "name", "type": "str", "docstring": "name to be changed to", "...
8b41f6c09e1559adb48ca222975ba46d59b49a30
baidu/Quanlse
Quanlse/QOperator.py
[ "Apache-2.0" ]
Python
onSubSys
<not_specific>
def onSubSys(self): """ Return the corresponding subsystem number of the operator. """ return self._onSubSys
Return the corresponding subsystem number of the operator.
Return the corresponding subsystem number of the operator.
[ "Return", "the", "corresponding", "subsystem", "number", "of", "the", "operator", "." ]
def onSubSys(self): return self._onSubSys
[ "def", "onSubSys", "(", "self", ")", ":", "return", "self", ".", "_onSubSys" ]
Return the corresponding subsystem number of the operator.
[ "Return", "the", "corresponding", "subsystem", "number", "of", "the", "operator", "." ]
[ "\"\"\"\n Return the corresponding subsystem number of the operator.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
8b41f6c09e1559adb48ca222975ba46d59b49a30
baidu/Quanlse
Quanlse/QOperator.py
[ "Apache-2.0" ]
Python
onSubSys
null
def onSubSys(self, onSubSys: int): """ Modify the corresponding subsystem of the operator. :param onSubSys: subsystem to be changed to """ if onSubSys is None: self._onSubSys = None else: if not isinstance(onSubSys, int): raise Err...
Modify the corresponding subsystem of the operator. :param onSubSys: subsystem to be changed to
Modify the corresponding subsystem of the operator.
[ "Modify", "the", "corresponding", "subsystem", "of", "the", "operator", "." ]
def onSubSys(self, onSubSys: int): if onSubSys is None: self._onSubSys = None else: if not isinstance(onSubSys, int): raise Error.ArgumentError(f"onSubSys must be an integer, instead of {type(onSubSys)}!") self._onSubSys = onSubSys
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Modify the corresponding subsystem of the operator.
[ "Modify", "the", "corresponding", "subsystem", "of", "the", "operator", "." ]
[ "\"\"\"\n Modify the corresponding subsystem of the operator.\n\n :param onSubSys: subsystem to be changed to\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "onSubSys", "type": "int" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "onSubSys", "type": "int", "docstring": "subsystem to be changed to"...
8b41f6c09e1559adb48ca222975ba46d59b49a30
baidu/Quanlse
Quanlse/QOperator.py
[ "Apache-2.0" ]
Python
coef
null
def coef(self, coef: Union[float, complex] = 1.0): """ Setter for the coefficient :param: coefficient to be set to """ if coef is None: self._coef = 1.0 else: if not (isinstance(coef, float) or isinstance(coef, complex)): raise Err...
Setter for the coefficient :param: coefficient to be set to
Setter for the coefficient :param: coefficient to be set to
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def coef(self, coef: Union[float, complex] = 1.0): if coef is None: self._coef = 1.0 else: if not (isinstance(coef, float) or isinstance(coef, complex)): raise Error.ArgumentError(f"coef must be a float or complex, instead of {type(coef)}!") self._coef...
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Setter for the coefficient :param: coefficient to be set to
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[ "\"\"\"\n Setter for the coefficient\n\n :param: coefficient to be set to\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "coef", "type": "Union[float, complex]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "coef", "type": "Union[float, complex]", "docstring": null, "d...
8b41f6c09e1559adb48ca222975ba46d59b49a30
baidu/Quanlse
Quanlse/QOperator.py
[ "Apache-2.0" ]
Python
load
'QOperator'
def load(base64Str: str) -> 'QOperator': """ Create object from base64 encoded string. :return: a QOperator object """ byteStr = base64.b64decode(base64Str.encode()) obj = pickle.loads(byteStr) # type: QOperator return obj
Create object from base64 encoded string. :return: a QOperator object
Create object from base64 encoded string.
[ "Create", "object", "from", "base64", "encoded", "string", "." ]
def load(base64Str: str) -> 'QOperator': byteStr = base64.b64decode(base64Str.encode()) obj = pickle.loads(byteStr) return obj
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Create object from base64 encoded string.
[ "Create", "object", "from", "base64", "encoded", "string", "." ]
[ "\"\"\"\n Create object from base64 encoded string.\n\n :return: a QOperator object\n \"\"\"", "# type: QOperator" ]
[ { "param": "base64Str", "type": "str" } ]
{ "returns": [ { "docstring": "a QOperator object", "docstring_tokens": [ "a", "QOperator", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "base64Str", "type": "str", "docstring": null, "docstring_tokens...
8b41f6c09e1559adb48ca222975ba46d59b49a30
baidu/Quanlse
Quanlse/QOperator.py
[ "Apache-2.0" ]
Python
dagger
ndarray
def dagger(matrix: ndarray) -> ndarray: """ Return the conjugate transpose of a given matrix. :param matrix: the given matrix :return: the conjugate transposed matrix """ return array(conjugate(transpose(matrix)), order="C")
Return the conjugate transpose of a given matrix. :param matrix: the given matrix :return: the conjugate transposed matrix
Return the conjugate transpose of a given matrix.
[ "Return", "the", "conjugate", "transpose", "of", "a", "given", "matrix", "." ]
def dagger(matrix: ndarray) -> ndarray: return array(conjugate(transpose(matrix)), order="C")
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Return the conjugate transpose of a given matrix.
[ "Return", "the", "conjugate", "transpose", "of", "a", "given", "matrix", "." ]
[ "\"\"\"\n Return the conjugate transpose of a given matrix.\n\n :param matrix: the given matrix\n :return: the conjugate transposed matrix\n \"\"\"" ]
[ { "param": "matrix", "type": "ndarray" } ]
{ "returns": [ { "docstring": "the conjugate transposed matrix", "docstring_tokens": [ "the", "conjugate", "transposed", "matrix" ], "type": null } ], "raises": [], "params": [ { "identifier": "matrix", "type": "ndarray", "doc...
8b41f6c09e1559adb48ca222975ba46d59b49a30
baidu/Quanlse
Quanlse/QOperator.py
[ "Apache-2.0" ]
Python
a
ndarray
def a(d: int = 2) -> ndarray: """ Return the numpy matrix of destroy operator. :return: a numpy matrix """ mat = zeros((d, d), dtype=complex, order="C") for i in range(0, d - 1): mat[i, i + 1] = sqrt(i + 1) + 0 * 1j return mat
Return the numpy matrix of destroy operator. :return: a numpy matrix
Return the numpy matrix of destroy operator.
[ "Return", "the", "numpy", "matrix", "of", "destroy", "operator", "." ]
def a(d: int = 2) -> ndarray: mat = zeros((d, d), dtype=complex, order="C") for i in range(0, d - 1): mat[i, i + 1] = sqrt(i + 1) + 0 * 1j return mat
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Return the numpy matrix of destroy operator.
[ "Return", "the", "numpy", "matrix", "of", "destroy", "operator", "." ]
[ "\"\"\"\n Return the numpy matrix of destroy operator.\n\n :return: a numpy matrix\n \"\"\"" ]
[ { "param": "d", "type": "int" } ]
{ "returns": [ { "docstring": "a numpy matrix", "docstring_tokens": [ "a", "numpy", "matrix" ], "type": null } ], "raises": [], "params": [ { "identifier": "d", "type": "int", "docstring": null, "docstring_tokens": [], "de...
719dcfb1e50c1814c3e8941e887c9ec43b8671a0
baidu/Quanlse
Quanlse/Scheduler/Superconduct/GeneratorCloud.py
[ "Apache-2.0" ]
Python
generate1Q
QJob
def generate1Q(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: """ Default generator for single qubit gates. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate inf...
Default generator for single qubit gates. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate information :param scheduler: the instance of Quanlse Scheduler Superconducting :return: returned QJob object
Default generator for single qubit gates.
[ "Default", "generator", "for", "single", "qubit", "gates", "." ]
def generate1Q(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: subHam = ham.subSystem(cirLine.qRegIndexList) if cirLine.data.name in ['X', 'RX']: job, inf = opt1q(subHam, cirLine.data.getMatrix(), depth=2, targetInfid=0.0001) ...
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Default generator for single qubit gates.
[ "Default", "generator", "for", "single", "qubit", "gates", "." ]
[ "\"\"\"\n Default generator for single qubit gates.\n\n :param ham: QHam object containing the system information\n :param cirLine: a CircuitLine object containing the gate information\n :param scheduler: the instance of Quanlse Scheduler Superconducting\n :return: returned QJob object\n \"\"\"" ]
[ { "param": "ham", "type": "'QHamiltonian'" }, { "param": "cirLine", "type": "CircuitLine" }, { "param": "scheduler", "type": "'SchedulerSuperconduct'" } ]
{ "returns": [ { "docstring": "returned QJob object", "docstring_tokens": [ "returned", "QJob", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "ham", "type": "'QHamiltonian'", "docstring": "QHam object contain...
719dcfb1e50c1814c3e8941e887c9ec43b8671a0
baidu/Quanlse
Quanlse/Scheduler/Superconduct/GeneratorCloud.py
[ "Apache-2.0" ]
Python
generateCr
QJob
def generateCr(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: """ Default generator for Cross-resonance gate. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate i...
Default generator for Cross-resonance gate. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate information :param scheduler: the instance of Quanlse Scheduler Superconducting :return: returned QJob object
Default generator for Cross-resonance gate.
[ "Default", "generator", "for", "Cross", "-", "resonance", "gate", "." ]
def generateCr(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: subHam = ham.subSystem(cirLine.qRegIndexList) job, inf = optCr(subHam, (-3.0, 3.0), maxIter=1) print(f"Infidelity of {cirLine.data.name} on qubit {cirLine.qRegIndexList}...
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Default generator for Cross-resonance gate.
[ "Default", "generator", "for", "Cross", "-", "resonance", "gate", "." ]
[ "\"\"\"\n Default generator for Cross-resonance gate.\n\n :param ham: QHam object containing the system information\n :param cirLine: a CircuitLine object containing the gate information\n :param scheduler: the instance of Quanlse Scheduler Superconducting\n :return: returned QJob object\n \"\"\""...
[ { "param": "ham", "type": "'QHamiltonian'" }, { "param": "cirLine", "type": "CircuitLine" }, { "param": "scheduler", "type": "'SchedulerSuperconduct'" } ]
{ "returns": [ { "docstring": "returned QJob object", "docstring_tokens": [ "returned", "QJob", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "ham", "type": "'QHamiltonian'", "docstring": "QHam object contain...
719dcfb1e50c1814c3e8941e887c9ec43b8671a0
baidu/Quanlse
Quanlse/Scheduler/Superconduct/GeneratorCloud.py
[ "Apache-2.0" ]
Python
generateCz
QJob
def generateCz(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: """ Default generator for controlled-Z gate. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate info...
Default generator for controlled-Z gate. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate information :param scheduler: the instance of Quanlse Scheduler Superconducting :return: returned QJob object
Default generator for controlled-Z gate.
[ "Default", "generator", "for", "controlled", "-", "Z", "gate", "." ]
def generateCz(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: subHam = ham.subSystem(cirLine.qRegIndexList) job, inf = optCz(subHam, tg=40, targetInfidelity=0.01) print(f"Infidelity of {cirLine.data.name} on qubit {cirLine.qRegInde...
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Default generator for controlled-Z gate.
[ "Default", "generator", "for", "controlled", "-", "Z", "gate", "." ]
[ "\"\"\"\n Default generator for controlled-Z gate.\n\n :param ham: QHam object containing the system information\n :param cirLine: a CircuitLine object containing the gate information\n :param scheduler: the instance of Quanlse Scheduler Superconducting\n :return: returned QJob object\n \"\"\"" ]
[ { "param": "ham", "type": "'QHamiltonian'" }, { "param": "cirLine", "type": "CircuitLine" }, { "param": "scheduler", "type": "'SchedulerSuperconduct'" } ]
{ "returns": [ { "docstring": "returned QJob object", "docstring_tokens": [ "returned", "QJob", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "ham", "type": "'QHamiltonian'", "docstring": "QHam object contain...
719dcfb1e50c1814c3e8941e887c9ec43b8671a0
baidu/Quanlse
Quanlse/Scheduler/Superconduct/GeneratorCloud.py
[ "Apache-2.0" ]
Python
generateISWAP
QJob
def generateISWAP(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: """ Default generator for ISWAP gate. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate infor...
Default generator for ISWAP gate. :param ham: QHam object containing the system information :param cirLine: a CircuitLine object containing the gate information :param scheduler: the instance of Quanlse Scheduler Superconducting :return: returned QJob object
Default generator for ISWAP gate.
[ "Default", "generator", "for", "ISWAP", "gate", "." ]
def generateISWAP(ham: 'QHamiltonian' = None, cirLine: CircuitLine = None, scheduler: 'SchedulerSuperconduct' = None) -> QJob: subHam = ham.subSystem(cirLine.qRegIndexList) job, inf = optISWAP(subHam, tg=50, targetInfidelity=0.01) print(f"Infidelity of {cirLine.data.name} on qubit {cirLine...
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Default generator for ISWAP gate.
[ "Default", "generator", "for", "ISWAP", "gate", "." ]
[ "\"\"\"\n Default generator for ISWAP gate.\n\n :param ham: QHam object containing the system information\n :param cirLine: a CircuitLine object containing the gate information\n :param scheduler: the instance of Quanlse Scheduler Superconducting\n :return: returned QJob object\n \"\"\"" ]
[ { "param": "ham", "type": "'QHamiltonian'" }, { "param": "cirLine", "type": "CircuitLine" }, { "param": "scheduler", "type": "'SchedulerSuperconduct'" } ]
{ "returns": [ { "docstring": "returned QJob object", "docstring_tokens": [ "returned", "QJob", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "ham", "type": "'QHamiltonian'", "docstring": "QHam object contain...
719dcfb1e50c1814c3e8941e887c9ec43b8671a0
baidu/Quanlse
Quanlse/Scheduler/Superconduct/GeneratorCloud.py
[ "Apache-2.0" ]
Python
generatorCloud
SchedulerPulseGenerator
def generatorCloud(ham: 'QHamiltonian') -> SchedulerPulseGenerator: """ Return a default pulse SchedulerPulseGenerator instance for the scheduler. :param ham: a Hamiltonian object :return: returned generator object """ generator = SchedulerPulseGenerator(ham) # Add the generator for singl...
Return a default pulse SchedulerPulseGenerator instance for the scheduler. :param ham: a Hamiltonian object :return: returned generator object
Return a default pulse SchedulerPulseGenerator instance for the scheduler.
[ "Return", "a", "default", "pulse", "SchedulerPulseGenerator", "instance", "for", "the", "scheduler", "." ]
def generatorCloud(ham: 'QHamiltonian') -> SchedulerPulseGenerator: generator = SchedulerPulseGenerator(ham) gateList1q = ['X', 'Y', 'Z', 'H', 'S', 'T', 'RX', 'RY', 'RZ', 'W', 'SQRTW', 'U'] generator.addGenerator(gateList1q, generate1Q) generator.addGenerator(['CR'], generateCr) generator.addGenerat...
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Return a default pulse SchedulerPulseGenerator instance for the scheduler.
[ "Return", "a", "default", "pulse", "SchedulerPulseGenerator", "instance", "for", "the", "scheduler", "." ]
[ "\"\"\"\n Return a default pulse SchedulerPulseGenerator instance for the scheduler.\n\n :param ham: a Hamiltonian object\n :return: returned generator object\n \"\"\"", "# Add the generator for single qubit gates", "# Add the generator for two-qubit gates" ]
[ { "param": "ham", "type": "'QHamiltonian'" } ]
{ "returns": [ { "docstring": "returned generator object", "docstring_tokens": [ "returned", "generator", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "ham", "type": "'QHamiltonian'", "docstring": "a Hamilto...
5cb55272ccde412ba14a1122bdb931ad98a7d233
baidu/Quanlse
Quanlse/QRpc.py
[ "Apache-2.0" ]
Python
_createTask
<not_specific>
def _createTask(token, circuitId, optimizer, backendParam=None, modules=[], debug=False, taskType="quanlse_optimizer"): """ Create a task from the code """ task = { "token": token, "circuitId": circuitId, "taskType": taskType, "sdkVersion": sdkVersion, "source": ...
Create a task from the code
Create a task from the code
[ "Create", "a", "task", "from", "the", "code" ]
def _createTask(token, circuitId, optimizer, backendParam=None, modules=[], debug=False, taskType="quanlse_optimizer"): task = { "token": token, "circuitId": circuitId, "taskType": taskType, "sdkVersion": sdkVersion, "source": taskSourceQuanlse, "optimizer": optimizer...
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Create a task from the code
[ "Create", "a", "task", "from", "the", "code" ]
[ "\"\"\"\n Create a task from the code\n \"\"\"" ]
[ { "param": "token", "type": null }, { "param": "circuitId", "type": null }, { "param": "optimizer", "type": null }, { "param": "backendParam", "type": null }, { "param": "modules", "type": null }, { "param": "debug", "type": null }, { "para...
{ "returns": [], "raises": [], "params": [ { "identifier": "token", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "circuitId", "type": null, "docstring": null, "docstring_toke...
8a09f227c937d7fe10782f496c74b930baff45a4
baidu/Quanlse
Quanlse/Scheduler/Superconduct/GeneratorPulseModel.py
[ "Apache-2.0" ]
Python
generateBasic1Q
QJob
def generateBasic1Q(ham, gate, onQubit, scheduler) -> QJob: """ Generate the single-qubit gates """ job = ham.createJob() # Generate the operator if gate.name in ['X', 'RX', 'Y', 'RY']: if "caliDataXY" not in scheduler.conf.keys(): raise ArgumentError(f"'cali...
Generate the single-qubit gates
Generate the single-qubit gates
[ "Generate", "the", "single", "-", "qubit", "gates" ]
def generateBasic1Q(ham, gate, onQubit, scheduler) -> QJob: job = ham.createJob() if gate.name in ['X', 'RX', 'Y', 'RY']: if "caliDataXY" not in scheduler.conf.keys(): raise ArgumentError(f"'caliDataXY' does not exist in scheduler.conf, " f...
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Generate the single-qubit gates
[ "Generate", "the", "single", "-", "qubit", "gates" ]
[ "\"\"\" Generate the single-qubit gates \"\"\"", "# Generate the operator", "# Pulse Parameters", "# Add the waveform to job", "# Pulse Parameters", "# Add the waveform to job" ]
[ { "param": "ham", "type": null }, { "param": "gate", "type": null }, { "param": "onQubit", "type": null }, { "param": "scheduler", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "ham", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "gate", "type": null, "docstring": null, "docstring_tokens": []...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
sysLevel
null
def sysLevel(self, value: Union[int, List[int]]): """ Set the level of subsystems. :param value: the number of subsystems - either an integer value or a list of integers. """ if not isinstance(value, int) and not isinstance(value, list): raise Error.ArgumentError("sy...
Set the level of subsystems. :param value: the number of subsystems - either an integer value or a list of integers.
Set the level of subsystems.
[ "Set", "the", "level", "of", "subsystems", "." ]
def sysLevel(self, value: Union[int, List[int]]): if not isinstance(value, int) and not isinstance(value, list): raise Error.ArgumentError("sysLevel must be an integer or a list!") if isinstance(value, list) and min(value) < 2: raise Error.ArgumentError("All items in sysSize must...
[ "def", "sysLevel", "(", "self", ",", "value", ":", "Union", "[", "int", ",", "List", "[", "int", "]", "]", ")", ":", "if", "not", "isinstance", "(", "value", ",", "int", ")", "and", "not", "isinstance", "(", "value", ",", "list", ")", ":", "raise...
Set the level of subsystems.
[ "Set", "the", "level", "of", "subsystems", "." ]
[ "\"\"\"\n Set the level of subsystems.\n\n :param value: the number of subsystems - either an integer value or a list of integers.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "value", "type": "Union[int, List[int]]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": "Union[int, List[int]]", "docstring": "the number o...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
ctrlCache
Dict[str, Any]
def ctrlCache(self) -> Dict[str, Any]: """ Return the cache of the control terms. """ return self._ctrlCache
Return the cache of the control terms.
Return the cache of the control terms.
[ "Return", "the", "cache", "of", "the", "control", "terms", "." ]
def ctrlCache(self) -> Dict[str, Any]: return self._ctrlCache
[ "def", "ctrlCache", "(", "self", ")", "->", "Dict", "[", "str", ",", "Any", "]", ":", "return", "self", ".", "_ctrlCache" ]
Return the cache of the control terms.
[ "Return", "the", "cache", "of", "the", "control", "terms", "." ]
[ "\"\"\"\n Return the cache of the control terms.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
ctrlCache
null
def ctrlCache(self): """ Delete the cache of the control terms. """ del self._ctrlCache
Delete the cache of the control terms.
Delete the cache of the control terms.
[ "Delete", "the", "cache", "of", "the", "control", "terms", "." ]
def ctrlCache(self): del self._ctrlCache
[ "def", "ctrlCache", "(", "self", ")", ":", "del", "self", ".", "_ctrlCache" ]
Delete the cache of the control terms.
[ "Delete", "the", "cache", "of", "the", "control", "terms", "." ]
[ "\"\"\"\n Delete the cache of the control terms.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
driftCache
ndarray
def driftCache(self) -> ndarray: """ Return the cache of the drift terms. """ return self._driftCache
Return the cache of the drift terms.
Return the cache of the drift terms.
[ "Return", "the", "cache", "of", "the", "drift", "terms", "." ]
def driftCache(self) -> ndarray: return self._driftCache
[ "def", "driftCache", "(", "self", ")", "->", "ndarray", ":", "return", "self", ".", "_driftCache" ]
Return the cache of the drift terms.
[ "Return", "the", "cache", "of", "the", "drift", "terms", "." ]
[ "\"\"\"\n Return the cache of the drift terms.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
driftCache
null
def driftCache(self): """ Delete the cache of the drift terms. """ del self._driftCache
Delete the cache of the drift terms.
Delete the cache of the drift terms.
[ "Delete", "the", "cache", "of", "the", "drift", "terms", "." ]
def driftCache(self): del self._driftCache
[ "def", "driftCache", "(", "self", ")", ":", "del", "self", ".", "_driftCache" ]
Delete the cache of the drift terms.
[ "Delete", "the", "cache", "of", "the", "drift", "terms", "." ]
[ "\"\"\"\n Delete the cache of the drift terms.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
waveCache
Dict[str, Any]
def waveCache(self) -> Dict[str, Any]: """ Return the cache of drift terms. """ return self._waveJob.waveCache
Return the cache of drift terms.
Return the cache of drift terms.
[ "Return", "the", "cache", "of", "drift", "terms", "." ]
def waveCache(self) -> Dict[str, Any]: return self._waveJob.waveCache
[ "def", "waveCache", "(", "self", ")", "->", "Dict", "[", "str", ",", "Any", "]", ":", "return", "self", ".", "_waveJob", ".", "waveCache" ]
Return the cache of drift terms.
[ "Return", "the", "cache", "of", "drift", "terms", "." ]
[ "\"\"\"\n Return the cache of drift terms.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
driftOperators
Dict[str, Union[QOperator, List[QOperator]]]
def driftOperators(self) -> Dict[str, Union[QOperator, List[QOperator]]]: """ Return the operators of the drift terms. """ return self._driftOperators
Return the operators of the drift terms.
Return the operators of the drift terms.
[ "Return", "the", "operators", "of", "the", "drift", "terms", "." ]
def driftOperators(self) -> Dict[str, Union[QOperator, List[QOperator]]]: return self._driftOperators
[ "def", "driftOperators", "(", "self", ")", "->", "Dict", "[", "str", ",", "Union", "[", "QOperator", ",", "List", "[", "QOperator", "]", "]", "]", ":", "return", "self", ".", "_driftOperators" ]
Return the operators of the drift terms.
[ "Return", "the", "operators", "of", "the", "drift", "terms", "." ]
[ "\"\"\"\n Return the operators of the drift terms.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
driftOperators
null
def driftOperators(self): """ Delete the operators of the drift terms. """ del self._driftOperators self._driftOperators = {}
Delete the operators of the drift terms.
Delete the operators of the drift terms.
[ "Delete", "the", "operators", "of", "the", "drift", "terms", "." ]
def driftOperators(self): del self._driftOperators self._driftOperators = {}
[ "def", "driftOperators", "(", "self", ")", ":", "del", "self", ".", "_driftOperators", "self", ".", "_driftOperators", "=", "{", "}" ]
Delete the operators of the drift terms.
[ "Delete", "the", "operators", "of", "the", "drift", "terms", "." ]
[ "\"\"\"\n Delete the operators of the drift terms.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
doNotClearFlagOperators
Dict[str, Union[QOperator, List[QOperator]]]
def doNotClearFlagOperators(self) -> Dict[str, Union[QOperator, List[QOperator]]]: """ Return operators with flag QWAVEFORM_FLAG_DO_NOT_CLEAR. """ return self._doNotClearFlagOperators
Return operators with flag QWAVEFORM_FLAG_DO_NOT_CLEAR.
Return operators with flag QWAVEFORM_FLAG_DO_NOT_CLEAR.
[ "Return", "operators", "with", "flag", "QWAVEFORM_FLAG_DO_NOT_CLEAR", "." ]
def doNotClearFlagOperators(self) -> Dict[str, Union[QOperator, List[QOperator]]]: return self._doNotClearFlagOperators
[ "def", "doNotClearFlagOperators", "(", "self", ")", "->", "Dict", "[", "str", ",", "Union", "[", "QOperator", ",", "List", "[", "QOperator", "]", "]", "]", ":", "return", "self", ".", "_doNotClearFlagOperators" ]
Return operators with flag QWAVEFORM_FLAG_DO_NOT_CLEAR.
[ "Return", "operators", "with", "flag", "QWAVEFORM_FLAG_DO_NOT_CLEAR", "." ]
[ "\"\"\"\n Return operators with flag QWAVEFORM_FLAG_DO_NOT_CLEAR.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
ctrlOperators
Dict[str, Union[QOperator, List[QOperator]]]
def ctrlOperators(self) -> Dict[str, Union[QOperator, List[QOperator]]]: """ Return operators of the control term. """ return self._waveJob.ctrlOperators
Return operators of the control term.
Return operators of the control term.
[ "Return", "operators", "of", "the", "control", "term", "." ]
def ctrlOperators(self) -> Dict[str, Union[QOperator, List[QOperator]]]: return self._waveJob.ctrlOperators
[ "def", "ctrlOperators", "(", "self", ")", "->", "Dict", "[", "str", ",", "Union", "[", "QOperator", ",", "List", "[", "QOperator", "]", "]", "]", ":", "return", "self", ".", "_waveJob", ".", "ctrlOperators" ]
Return operators of the control term.
[ "Return", "operators", "of", "the", "control", "term", "." ]
[ "\"\"\"\n Return operators of the control term.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
collapseOperators
Optional[List[ndarray]]
def collapseOperators(self) -> Optional[List[ndarray]]: """ Return the list of the cache of the collapse operators for the Lindblad master equations. """ return self._collapseOperators
Return the list of the cache of the collapse operators for the Lindblad master equations.
Return the list of the cache of the collapse operators for the Lindblad master equations.
[ "Return", "the", "list", "of", "the", "cache", "of", "the", "collapse", "operators", "for", "the", "Lindblad", "master", "equations", "." ]
def collapseOperators(self) -> Optional[List[ndarray]]: return self._collapseOperators
[ "def", "collapseOperators", "(", "self", ")", "->", "Optional", "[", "List", "[", "ndarray", "]", "]", ":", "return", "self", ".", "_collapseOperators" ]
Return the list of the cache of the collapse operators for the Lindblad master equations.
[ "Return", "the", "list", "of", "the", "cache", "of", "the", "collapse", "operators", "for", "the", "Lindblad", "master", "equations", "." ]
[ "\"\"\"\n Return the list of the cache of the collapse operators for the Lindblad master equations.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
collapseOperators
null
def collapseOperators(self): """ Delete the list of the cache of the collapse operators for the Lindblad master equations. """ del self._collapseOperators self._collapseOperators = None
Delete the list of the cache of the collapse operators for the Lindblad master equations.
Delete the list of the cache of the collapse operators for the Lindblad master equations.
[ "Delete", "the", "list", "of", "the", "cache", "of", "the", "collapse", "operators", "for", "the", "Lindblad", "master", "equations", "." ]
def collapseOperators(self): del self._collapseOperators self._collapseOperators = None
[ "def", "collapseOperators", "(", "self", ")", ":", "del", "self", ".", "_collapseOperators", "self", ".", "_collapseOperators", "=", "None" ]
Delete the list of the cache of the collapse operators for the Lindblad master equations.
[ "Delete", "the", "list", "of", "the", "cache", "of", "the", "collapse", "operators", "for", "the", "Lindblad", "master", "equations", "." ]
[ "\"\"\"\n Delete the list of the cache of the collapse operators for the Lindblad master equations.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
dissipationSuperCache
<not_specific>
def dissipationSuperCache(self): """ Return the cache of dissipation super operator. """ return self._dissipationSuperCache
Return the cache of dissipation super operator.
Return the cache of dissipation super operator.
[ "Return", "the", "cache", "of", "dissipation", "super", "operator", "." ]
def dissipationSuperCache(self): return self._dissipationSuperCache
[ "def", "dissipationSuperCache", "(", "self", ")", ":", "return", "self", ".", "_dissipationSuperCache" ]
Return the cache of dissipation super operator.
[ "Return", "the", "cache", "of", "dissipation", "super", "operator", "." ]
[ "\"\"\"\n Return the cache of dissipation super operator.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
dissipationSuperCache
null
def dissipationSuperCache(self): """ Delete the cache of the dissipation super operators. """ del self._dissipationSuperCache
Delete the cache of the dissipation super operators.
Delete the cache of the dissipation super operators.
[ "Delete", "the", "cache", "of", "the", "dissipation", "super", "operators", "." ]
def dissipationSuperCache(self): del self._dissipationSuperCache
[ "def", "dissipationSuperCache", "(", "self", ")", ":", "del", "self", ".", "_dissipationSuperCache" ]
Delete the cache of the dissipation super operators.
[ "Delete", "the", "cache", "of", "the", "dissipation", "super", "operators", "." ]
[ "\"\"\"\n Delete the cache of the dissipation super operators.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
job
QJob
def job(self) -> QJob: """ Return a QJob object. The QJob object contains all the information regarding a quantum task. """ return self._waveJob
Return a QJob object. The QJob object contains all the information regarding a quantum task.
Return a QJob object. The QJob object contains all the information regarding a quantum task.
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def job(self) -> QJob: return self._waveJob
[ "def", "job", "(", "self", ")", "->", "QJob", ":", "return", "self", ".", "_waveJob" ]
Return a QJob object.
[ "Return", "a", "QJob", "object", "." ]
[ "\"\"\"\n Return a QJob object. The QJob object contains all the information regarding a quantum task.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
copy
"QHamiltonian"
def copy(self) -> "QHamiltonian": """ Return a copy of current object. """ return copy.deepcopy(self)
Return a copy of current object.
Return a copy of current object.
[ "Return", "a", "copy", "of", "current", "object", "." ]
def copy(self) -> "QHamiltonian": return copy.deepcopy(self)
[ "def", "copy", "(", "self", ")", "->", "\"QHamiltonian\"", ":", "return", "copy", ".", "deepcopy", "(", "self", ")" ]
Return a copy of current object.
[ "Return", "a", "copy", "of", "current", "object", "." ]
[ "\"\"\"\n Return a copy of current object.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
createJobList
QJobList
def createJobList(self) -> QJobList: """ Return an instance of a QJobList of the same system properties. """ newJobList = QJobList(subSysNum=self.subSysNum, sysLevel=self.sysLevel, dt=self.dt) newJobList.LO = self.job.LO return newJobList
Return an instance of a QJobList of the same system properties.
Return an instance of a QJobList of the same system properties.
[ "Return", "an", "instance", "of", "a", "QJobList", "of", "the", "same", "system", "properties", "." ]
def createJobList(self) -> QJobList: newJobList = QJobList(subSysNum=self.subSysNum, sysLevel=self.sysLevel, dt=self.dt) newJobList.LO = self.job.LO return newJobList
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Return an instance of a QJobList of the same system properties.
[ "Return", "an", "instance", "of", "a", "QJobList", "of", "the", "same", "system", "properties", "." ]
[ "\"\"\"\n Return an instance of a QJobList of the same system properties.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
createJob
QJob
def createJob(self) -> QJob: """ Return an instance of a QJob object of the same system properties. """ newJob = QJob(subSysNum=self.subSysNum, sysLevel=self.sysLevel, dt=self.dt) newJob.ctrlOperators = copy.deepcopy(self.job.ctrlOperators) newJob.LO = self.job.LO ...
Return an instance of a QJob object of the same system properties.
Return an instance of a QJob object of the same system properties.
[ "Return", "an", "instance", "of", "a", "QJob", "object", "of", "the", "same", "system", "properties", "." ]
def createJob(self) -> QJob: newJob = QJob(subSysNum=self.subSysNum, sysLevel=self.sysLevel, dt=self.dt) newJob.ctrlOperators = copy.deepcopy(self.job.ctrlOperators) newJob.LO = self.job.LO return newJob
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Return an instance of a QJob object of the same system properties.
[ "Return", "an", "instance", "of", "a", "QJob", "object", "of", "the", "same", "system", "properties", "." ]
[ "\"\"\"\n Return an instance of a QJob object of the same system properties.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
addWave
None
def addWave(self, operators: Union[QOperator, Callable, List[QOperator], List[Callable]] = None, onSubSys: Union[int, List[int]] = None, waves: Union[QWaveform, List[QWaveform]] = None, t0: Union[int, float] = None, strength: Union[int, float] = 1.0, freq: Optional[Union[...
r""" This method adds a control term to the Hamiltonian with a specified waveform. :param operators: wave operator :param onSubSys: what subsystem the wave is acting upon :param waves: a QWaveform object :param t0: start time :param strength: wave strength :param...
r""" This method adds a control term to the Hamiltonian with a specified waveform.
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def addWave(self, operators: Union[QOperator, Callable, List[QOperator], List[Callable]] = None, onSubSys: Union[int, List[int]] = None, waves: Union[QWaveform, List[QWaveform]] = None, t0: Union[int, float] = None, strength: Union[int, float] = 1.0, freq: Optional[Union[...
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r""" This method adds a control term to the Hamiltonian with a specified waveform.
[ "r", "\"", "\"", "\"", "This", "method", "adds", "a", "control", "term", "to", "the", "Hamiltonian", "with", "a", "specified", "waveform", "." ]
[ "r\"\"\"\n This method adds a control term to the Hamiltonian with a specified waveform.\n\n :param operators: wave operator\n :param onSubSys: what subsystem the wave is acting upon\n :param waves: a QWaveform object\n :param t0: start time\n :param strength: wave strength...
[ { "param": "self", "type": null }, { "param": "operators", "type": "Union[QOperator, Callable, List[QOperator], List[Callable]]" }, { "param": "onSubSys", "type": "Union[int, List[int]]" }, { "param": "waves", "type": "Union[QWaveform, List[QWaveform]]" }, { "para...
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
appendWave
null
def appendWave(self, operators: Union[QOperator, Callable, List[QOperator], List[Callable]] = None, onSubSys: Union[int, List[int]] = None, waves: Union[QWaveform, List[QWaveform]] = None, strength: Union[int, float] = 1.0, freq: Optional[Union[int, float]] = None, ...
This method appends control terms and waveforms to a QJob object. Unlike `addWave()`, this function will append the waveform in the end of the existing waveforms, hence ignore the `t0` parameter of rhe `QWaveform` object. :param operators: wave operator :param onSubSys: what subsystem ...
This method appends control terms and waveforms to a QJob object.
[ "This", "method", "appends", "control", "terms", "and", "waveforms", "to", "a", "QJob", "object", "." ]
def appendWave(self, operators: Union[QOperator, Callable, List[QOperator], List[Callable]] = None, onSubSys: Union[int, List[int]] = None, waves: Union[QWaveform, List[QWaveform]] = None, strength: Union[int, float] = 1.0, freq: Optional[Union[int, float]] = None, ...
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This method appends control terms and waveforms to a QJob object.
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[ "\"\"\"\n This method appends control terms and waveforms to a QJob object. Unlike `addWave()`, this function will append\n the waveform in the end of the existing waveforms, hence ignore the `t0` parameter of rhe `QWaveform` object.\n\n :param operators: wave operator\n :param onSubSys:...
[ { "param": "self", "type": null }, { "param": "operators", "type": "Union[QOperator, Callable, List[QOperator], List[Callable]]" }, { "param": "onSubSys", "type": "Union[int, List[int]]" }, { "param": "waves", "type": "Union[QWaveform, List[QWaveform]]" }, { "para...
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
clearWaves
None
def clearWaves(self, operators: Union[QOperator, Callable, List[QOperator], List[Callable]] = None, onSubSys: Union[int, List[int]] = None, names: Union[str, List[str]] = None, tag: str = None) -> None: """ This method removes all waveforms in the specified control ...
This method removes all waveforms in the specified control terms. If names is None, this method will remove waveforms in all control terms. :param operators: the corresponding operator(s) :param onSubSys: qubit indexes that the term acts upon :param names: the user-given name f...
This method removes all waveforms in the specified control terms. If names is None, this method will remove waveforms in all control terms.
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def clearWaves(self, operators: Union[QOperator, Callable, List[QOperator], List[Callable]] = None, onSubSys: Union[int, List[int]] = None, names: Union[str, List[str]] = None, tag: str = None) -> None: self.job.clearWaves(operators, onSubSys, names, tag)
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This method removes all waveforms in the specified control terms.
[ "This", "method", "removes", "all", "waveforms", "in", "the", "specified", "control", "terms", "." ]
[ "\"\"\"\n This method removes all waveforms in the specified control terms.\n If names is None, this method will remove waveforms in all control terms.\n\n :param operators: the corresponding operator(s)\n :param onSubSys: qubit indexes that the term acts upon\n :param names: the ...
[ { "param": "self", "type": null }, { "param": "operators", "type": "Union[QOperator, Callable, List[QOperator], List[Callable]]" }, { "param": "onSubSys", "type": "Union[int, List[int]]" }, { "param": "names", "type": "Union[str, List[str]]" }, { "param": "tag", ...
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
verifyWaveListObj
bool
def verifyWaveListObj(self, waveJob: QJob) -> bool: """ Check whether the QWaveList object is valid for this QHam object. :param waveJob: QWaveList to be checked :return: true of false indicating its validity """ for key in waveJob.ctrlOperators.keys(): if is...
Check whether the QWaveList object is valid for this QHam object. :param waveJob: QWaveList to be checked :return: true of false indicating its validity
Check whether the QWaveList object is valid for this QHam object.
[ "Check", "whether", "the", "QWaveList", "object", "is", "valid", "for", "this", "QHam", "object", "." ]
def verifyWaveListObj(self, waveJob: QJob) -> bool: for key in waveJob.ctrlOperators.keys(): if isinstance(waveJob.ctrlOperators[key], list): ops = waveJob.ctrlOperators[key] elif isinstance(waveJob.ctrlOperators[key], QOperator): ops = [waveJob.ctrlOperat...
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Check whether the QWaveList object is valid for this QHam object.
[ "Check", "whether", "the", "QWaveList", "object", "is", "valid", "for", "this", "QHam", "object", "." ]
[ "\"\"\"\n Check whether the QWaveList object is valid for this QHam object.\n\n :param waveJob: QWaveList to be checked\n :return: true of false indicating its validity\n \"\"\"", "# Check every operator" ]
[ { "param": "self", "type": null }, { "param": "waveJob", "type": "QJob" } ]
{ "returns": [ { "docstring": "true of false indicating its validity", "docstring_tokens": [ "true", "of", "false", "indicating", "its", "validity" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
buildCache
None
def buildCache(self) -> None: """ Build Cache for waveList and operators. :return: None """ self.clearCache() self.buildOperatorCache() self._waveJob.buildWaveCache() if self._collapseList is not None: self.buildCollapseCache() sel...
Build Cache for waveList and operators. :return: None
Build Cache for waveList and operators.
[ "Build", "Cache", "for", "waveList", "and", "operators", "." ]
def buildCache(self) -> None: self.clearCache() self.buildOperatorCache() self._waveJob.buildWaveCache() if self._collapseList is not None: self.buildCollapseCache() self.buildDissipationSuperCache()
[ "def", "buildCache", "(", "self", ")", "->", "None", ":", "self", ".", "clearCache", "(", ")", "self", ".", "buildOperatorCache", "(", ")", "self", ".", "_waveJob", ".", "buildWaveCache", "(", ")", "if", "self", ".", "_collapseList", "is", "not", "None",...
Build Cache for waveList and operators.
[ "Build", "Cache", "for", "waveList", "and", "operators", "." ]
[ "\"\"\"\n Build Cache for waveList and operators.\n\n :return: None\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
buildOperatorCache
None
def buildOperatorCache(self) -> None: r""" Save the drift/coupling/control terms in a more efficient way for further usage. Note that this function will recursively process all the terms added to drift/coupling/control terms and save them to cache. :return: None """ ...
r""" Save the drift/coupling/control terms in a more efficient way for further usage. Note that this function will recursively process all the terms added to drift/coupling/control terms and save them to cache. :return: None
r""" Save the drift/coupling/control terms in a more efficient way for further usage. Note that this function will recursively process all the terms added to drift/coupling/control terms and save them to cache.
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def buildOperatorCache(self) -> None: sysLevel = self.sysLevel subSysNum = self.subSysNum driftMatList = [] for key in self._driftOperators.keys(): if isinstance(self._driftOperators[key], list): mat = self._driftOperators[key][0].coef * self._generateOperator...
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r""" Save the drift/coupling/control terms in a more efficient way for further usage.
[ "r", "\"", "\"", "\"", "Save", "the", "drift", "/", "coupling", "/", "control", "terms", "in", "a", "more", "efficient", "way", "for", "further", "usage", "." ]
[ "r\"\"\"\n Save the drift/coupling/control terms in a more efficient way for further usage.\n Note that this function will recursively process all the terms added to drift/coupling/control terms and\n save them to cache.\n\n :return: None\n \"\"\"", "# Generator the operator for...
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
buildCollapseCache
None
def buildCollapseCache(self) -> None: r""" Generate and save the cache of the collapse operators. :return: None """ levelList = [] if isinstance(self.sysLevel, list): levelList = self.sysLevel elif isinstance(self.sysLevel, int): levelL...
r""" Generate and save the cache of the collapse operators. :return: None
r""" Generate and save the cache of the collapse operators.
[ "r", "\"", "\"", "\"", "Generate", "and", "save", "the", "cache", "of", "the", "collapse", "operators", "." ]
def buildCollapseCache(self) -> None: levelList = [] if isinstance(self.sysLevel, list): levelList = self.sysLevel elif isinstance(self.sysLevel, int): levelList = [self.sysLevel for _ in range(self.subSysNum)] cList = self._collapseList cacheList = [] ...
[ "def", "buildCollapseCache", "(", "self", ")", "->", "None", ":", "levelList", "=", "[", "]", "if", "isinstance", "(", "self", ".", "sysLevel", ",", "list", ")", ":", "levelList", "=", "self", ".", "sysLevel", "elif", "isinstance", "(", "self", ".", "s...
r""" Generate and save the cache of the collapse operators.
[ "r", "\"", "\"", "\"", "Generate", "and", "save", "the", "cache", "of", "the", "collapse", "operators", "." ]
[ "r\"\"\"\n Generate and save the cache of the collapse operators.\n\n :return: None\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
buildDissipationSuperCache
None
def buildDissipationSuperCache(self) -> None: """ Generate the dissipation super operator in the Liouville form. """ cList = self._collapseOperators dim = None # Calculate the dimension of the Hilbert space if isinstance(self.sysLevel, int): dim = se...
Generate the dissipation super operator in the Liouville form.
Generate the dissipation super operator in the Liouville form.
[ "Generate", "the", "dissipation", "super", "operator", "in", "the", "Liouville", "form", "." ]
def buildDissipationSuperCache(self) -> None: cList = self._collapseOperators dim = None if isinstance(self.sysLevel, int): dim = self.sysLevel ** self.subSysNum elif isinstance(self.sysLevel, list): dim = 1 for i in self.sysLevel: dim ...
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Generate the dissipation super operator in the Liouville form.
[ "Generate", "the", "dissipation", "super", "operator", "in", "the", "Liouville", "form", "." ]
[ "\"\"\"\n Generate the dissipation super operator in the Liouville form.\n \"\"\"", "# Calculate the dimension of the Hilbert space" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
_generateOperator
ndarray
def _generateOperator(self, operator: Union[QOperator, List[QOperator]]) -> ndarray: """ Generate the operator of the system in the complete Hilbert space by taking tensor products. :param operator: a list of operator(s) :return: the operator after taking the tensor products of the inpu...
Generate the operator of the system in the complete Hilbert space by taking tensor products. :param operator: a list of operator(s) :return: the operator after taking the tensor products of the input operator
Generate the operator of the system in the complete Hilbert space by taking tensor products.
[ "Generate", "the", "operator", "of", "the", "system", "in", "the", "complete", "Hilbert", "space", "by", "taking", "tensor", "products", "." ]
def _generateOperator(self, operator: Union[QOperator, List[QOperator]]) -> ndarray: sysLevel = self.sysLevel subSysNum = self.subSysNum if isinstance(operator, list): matrices = [] for op in operator: matrices.append(op.matrix) else: m...
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Generate the operator of the system in the complete Hilbert space by taking tensor products.
[ "Generate", "the", "operator", "of", "the", "system", "in", "the", "complete", "Hilbert", "space", "by", "taking", "tensor", "products", "." ]
[ "\"\"\"\n Generate the operator of the system in the complete Hilbert space by taking tensor products.\n\n :param operator: a list of operator(s)\n :return: the operator after taking the tensor products of the input operator\n \"\"\"", "# Generate matrices", "# Each subsystem of the ...
[ { "param": "self", "type": null }, { "param": "operator", "type": "Union[QOperator, List[QOperator]]" } ]
{ "returns": [ { "docstring": "the operator after taking the tensor products of the input operator", "docstring_tokens": [ "the", "operator", "after", "taking", "the", "tensor", "products", "of", "the", "input", "o...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
subSystem
'QHamiltonian'
def subSystem(self, onSubSys: Union[int, List[int]]) -> 'QHamiltonian': """ This method extracts a subsystem from the target Hamiltonian. :param onSubSys: a list of qubit indexes :return: subsystem's QHamiltonian object """ subHam = copy.deepcopy(self) subHam.cle...
This method extracts a subsystem from the target Hamiltonian. :param onSubSys: a list of qubit indexes :return: subsystem's QHamiltonian object
This method extracts a subsystem from the target Hamiltonian.
[ "This", "method", "extracts", "a", "subsystem", "from", "the", "target", "Hamiltonian", "." ]
def subSystem(self, onSubSys: Union[int, List[int]]) -> 'QHamiltonian': subHam = copy.deepcopy(self) subHam.clearCache() if isinstance(onSubSys, int): subQubits = 1 indexMapping = {onSubSys: 0} if onSubSys >= self._subSysNum: raise Error.Argume...
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This method extracts a subsystem from the target Hamiltonian.
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[ "\"\"\"\n This method extracts a subsystem from the target Hamiltonian.\n\n :param onSubSys: a list of qubit indexes\n :return: subsystem's QHamiltonian object\n \"\"\"", "# Information about the sub system", "# qubit index mapping", "# Update the sysLevel property", "# Set the m...
[ { "param": "self", "type": null }, { "param": "onSubSys", "type": "Union[int, List[int]]" } ]
{ "returns": [ { "docstring": "subsystem's QHamiltonian object", "docstring_tokens": [ "subsystem", "'", "s", "QHamiltonian", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
mapping
Union[int, List[int]]
def mapping(index: Union[int, List[int]]) -> Union[int, List[int]]: """ Map the `onQubits` index(es) from the original Ham to the extracted Ham. :param index: 'onQubits' index(es) from the original Ham :return: mapped index(es) onto the extracted Ham """ ...
Map the `onQubits` index(es) from the original Ham to the extracted Ham. :param index: 'onQubits' index(es) from the original Ham :return: mapped index(es) onto the extracted Ham
Map the `onQubits` index(es) from the original Ham to the extracted Ham.
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def mapping(index: Union[int, List[int]]) -> Union[int, List[int]]: if isinstance(index, int): return indexMapping[index] else: mappedList = [] for item in index: mappedList.append(indexMapping[item]) return mapp...
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Map the `onQubits` index(es) from the original Ham to the extracted Ham.
[ "Map", "the", "`", "onQubits", "`", "index", "(", "es", ")", "from", "the", "original", "Ham", "to", "the", "extracted", "Ham", "." ]
[ "\"\"\"\n Map the `onQubits` index(es) from the original Ham to the extracted Ham.\n\n :param index: 'onQubits' index(es) from the original Ham\n :return: mapped index(es) onto the extracted Ham\n \"\"\"" ]
[ { "param": "index", "type": "Union[int, List[int]]" } ]
{ "returns": [ { "docstring": "mapped index(es) onto the extracted Ham", "docstring_tokens": [ "mapped", "index", "(", "es", ")", "onto", "the", "extracted", "Ham" ], "type": null } ], "raises": [], "params":...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
allIn
bool
def allIn(listA: Union[int, List[int]], listB: Union[int, List[int]]) -> bool: """ Check whether all the items in listB are in listA. :param listA: listA :param listB: listB :return: a bool value """ if isinstance(listA, int): ...
Check whether all the items in listB are in listA. :param listA: listA :param listB: listB :return: a bool value
Check whether all the items in listB are in listA.
[ "Check", "whether", "all", "the", "items", "in", "listB", "are", "in", "listA", "." ]
def allIn(listA: Union[int, List[int]], listB: Union[int, List[int]]) -> bool: if isinstance(listA, int): listA = [listA] if isinstance(listB, int): return listB in listA else: for item in listB: if item not in listA...
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Check whether all the items in listB are in listA.
[ "Check", "whether", "all", "the", "items", "in", "listB", "are", "in", "listA", "." ]
[ "\"\"\"\n Check whether all the items in listB are in listA.\n\n :param listA: listA\n :param listB: listB\n :return: a bool value\n \"\"\"" ]
[ { "param": "listA", "type": "Union[int, List[int]]" }, { "param": "listB", "type": "Union[int, List[int]]" } ]
{ "returns": [ { "docstring": "a bool value", "docstring_tokens": [ "a", "bool", "value" ], "type": null } ], "raises": [], "params": [ { "identifier": "listA", "type": "Union[int, List[int]]", "docstring": null, "docstring_toke...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
eigen
<not_specific>
def eigen(self, t: Optional[ndarray] = None): """ Calculate the eigenvalues and eigenvectors of the given Hamiltonian. :param t: The time at which the Hamiltonian's eigenvectors and eigenvalues are to compute. :return: If t is none, it returns (n, n) Hamiltonian's eigenvalues of shape (...
Calculate the eigenvalues and eigenvectors of the given Hamiltonian. :param t: The time at which the Hamiltonian's eigenvectors and eigenvalues are to compute. :return: If t is none, it returns (n, n) Hamiltonian's eigenvalues of shape (n, ) in the ascending order and the corresponding...
Calculate the eigenvalues and eigenvectors of the given Hamiltonian.
[ "Calculate", "the", "eigenvalues", "and", "eigenvectors", "of", "the", "given", "Hamiltonian", "." ]
def eigen(self, t: Optional[ndarray] = None): self.buildCache() drift = self.driftCache ctrl = self.ctrlCache wave = self.job.waveCache dt = self.dt maxDt = self.job.endTimeDt def _computeEigen(matrix): eigenVals, eigenVecs = eig(matrix) so...
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Calculate the eigenvalues and eigenvectors of the given Hamiltonian.
[ "Calculate", "the", "eigenvalues", "and", "eigenvectors", "of", "the", "given", "Hamiltonian", "." ]
[ "\"\"\"\n Calculate the eigenvalues and eigenvectors of the given Hamiltonian.\n\n :param t: The time at which the Hamiltonian's eigenvectors and eigenvalues are to compute.\n :return: If t is none, it returns (n, n) Hamiltonian's eigenvalues of shape (n, ) in the\n ascending order and t...
[ { "param": "self", "type": null }, { "param": "t", "type": "Optional[ndarray]" } ]
{ "returns": [ { "docstring": "If t is none, it returns (n, n) Hamiltonian's eigenvalues of shape (n, ) in the\nascending order and the corresponding eigenvectors matrix of shape (n, n); If t is an (m, ) array,\nit returns list of (m, n) eigenvalues and (m, n, n) eigenvectors.", "docstring_tokens": [ ...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
subSystemIndicesInverse
Dict[int, int]
def subSystemIndicesInverse(self) -> Dict[int, int]: """ In self.subSystem, users can extract a subsystem of the original system, thus, the qubit indices will change. For example, for a system with indices [0, 1, 2, 3], we extract the subsystem constituted by subsystems 1 and 3, then the...
In self.subSystem, users can extract a subsystem of the original system, thus, the qubit indices will change. For example, for a system with indices [0, 1, 2, 3], we extract the subsystem constituted by subsystems 1 and 3, then the index of subsystem 1 changes to 0; 3 changes to 1; the ...
In self.subSystem, users can extract a subsystem of the original system, thus, the qubit indices will change. For example, for a system with indices [0, 1, 2, 3], we extract the subsystem constituted by subsystems 1 and 3, then the index of subsystem 1 changes to 0; 3 changes to 1; the mapping in self.subSystemIndexMap...
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def subSystemIndicesInverse(self) -> Dict[int, int]: inverseMapping = {} for key in self.subSystemIndexMapping: inverseMapping[self.subSystemIndexMapping[key]] = key return inverseMapping
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In self.subSystem, users can extract a subsystem of the original system, thus, the qubit indices will change.
[ "In", "self", ".", "subSystem", "users", "can", "extract", "a", "subsystem", "of", "the", "original", "system", "thus", "the", "qubit", "indices", "will", "change", "." ]
[ "\"\"\"\n In self.subSystem, users can extract a subsystem of the original system,\n thus, the qubit indices will change. For example, for a system with indices [0, 1, 2, 3],\n we extract the subsystem constituted by subsystems 1 and 3, then the index of\n subsystem 1 changes to 0; 3 cha...
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "a dictionary containing the 'inverse mapping'", "docstring_tokens": [ "a", "dictionary", "containing", "the", "'", "inverse", "mapping", "'" ], "type": null } ], "raises": [], "params":...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
outputInverseJob
QJob
def outputInverseJob(self, subSysNum: int, sysLevel: int = None, dt: float = None) -> QJob: """ Return an inverse-mapped Job. (see subSystemIndicesInverse()) :param subSysNum: subsystem's size :param sysLevel: subsystem's energy level :param dt: time interval :return: re...
Return an inverse-mapped Job. (see subSystemIndicesInverse()) :param subSysNum: subsystem's size :param sysLevel: subsystem's energy level :param dt: time interval :return: returned QJob object
Return an inverse-mapped Job.
[ "Return", "an", "inverse", "-", "mapped", "Job", "." ]
def outputInverseJob(self, subSysNum: int, sysLevel: int = None, dt: float = None) -> QJob: inverseMapping = self.subSystemIndicesInverse() _sysLevel = self.sysLevel if sysLevel is None else sysLevel _dt = self.dt if dt is None else dt job = QJob(subSysNum, _sysLevel, _dt) for op...
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Return an inverse-mapped Job.
[ "Return", "an", "inverse", "-", "mapped", "Job", "." ]
[ "\"\"\"\n Return an inverse-mapped Job. (see subSystemIndicesInverse())\n\n :param subSysNum: subsystem's size\n :param sysLevel: subsystem's energy level\n :param dt: time interval\n :return: returned QJob object\n \"\"\"", "# Get the job", "# Add the waves into the ne...
[ { "param": "self", "type": null }, { "param": "subSysNum", "type": "int" }, { "param": "sysLevel", "type": "int" }, { "param": "dt", "type": "float" } ]
{ "returns": [ { "docstring": "returned QJob object", "docstring_tokens": [ "returned", "QJob", "object" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens":...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
simulate
QResult
def simulate(self, job: QJob = None, state0: ndarray = None, recordEvolution: bool = False, shot: int = None, isOpen: bool = False, jobList: QJobList = None, refreshCache: bool = True, accelerate: bool = False, adaptive: bool = False, tolerance: float = 0.01) -> QResult: """ ...
Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and batch-job processing. To activate acceleration, please install ``Numba`` JIT compiler, please visit its official website https://numba.pydata.org/ for more details. :p...
Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and batch-job processing.
[ "Calculate", "the", "unitary", "evolution", "operator", "with", "a", "given", "Hamiltonian", ".", "This", "function", "supports", "both", "single", "-", "job", "and", "batch", "-", "job", "processing", "." ]
def simulate(self, job: QJob = None, state0: ndarray = None, recordEvolution: bool = False, shot: int = None, isOpen: bool = False, jobList: QJobList = None, refreshCache: bool = True, accelerate: bool = False, adaptive: bool = False, tolerance: float = 0.01) -> QResult: result...
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Calculate the unitary evolution operator with a given Hamiltonian.
[ "Calculate", "the", "unitary", "evolution", "operator", "with", "a", "given", "Hamiltonian", "." ]
[ "\"\"\"\n Calculate the unitary evolution operator with a given Hamiltonian. This function supports\n both single-job and batch-job processing.\n\n To activate acceleration, please install ``Numba`` JIT compiler, please visit its official website\n https://numba.pydata.org/ for more deta...
[ { "param": "self", "type": null }, { "param": "job", "type": "QJob" }, { "param": "state0", "type": "ndarray" }, { "param": "recordEvolution", "type": "bool" }, { "param": "shot", "type": "int" }, { "param": "isOpen", "type": "bool" }, { "p...
{ "returns": [ { "docstring": "result dictionary (or a list of result dictionaries when ``jobList`` is provided)\nThis function does provide the option of simulating on local devices. However, Quanlse also provides\ncloud computing services which are significantly faster.\n\nExample 1** (single-job processi...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
doNotClearWaveFunctionsToSequences
Dict[str, List[QWaveform]]
def doNotClearWaveFunctionsToSequences(self, maxEndTime: float = None) -> Dict[str, List[QWaveform]]: """ Convert all functions into sequence (including the QWaveform objects) that is serializable. :param maxEndTime: maximum ending time :return: dictionary containing the converted funct...
Convert all functions into sequence (including the QWaveform objects) that is serializable. :param maxEndTime: maximum ending time :return: dictionary containing the converted functions
Convert all functions into sequence (including the QWaveform objects) that is serializable.
[ "Convert", "all", "functions", "into", "sequence", "(", "including", "the", "QWaveform", "objects", ")", "that", "is", "serializable", "." ]
def doNotClearWaveFunctionsToSequences(self, maxEndTime: float = None) -> Dict[str, List[QWaveform]]: newList = {} for waveKey in self._doNotClearFlagWaves: newList[waveKey] = [] for wave in self._doNotClearFlagWaves[waveKey]: seqWave = wave.waveFunctionToSequence...
[ "def", "doNotClearWaveFunctionsToSequences", "(", "self", ",", "maxEndTime", ":", "float", "=", "None", ")", "->", "Dict", "[", "str", ",", "List", "[", "QWaveform", "]", "]", ":", "newList", "=", "{", "}", "for", "waveKey", "in", "self", ".", "_doNotCle...
Convert all functions into sequence (including the QWaveform objects) that is serializable.
[ "Convert", "all", "functions", "into", "sequence", "(", "including", "the", "QWaveform", "objects", ")", "that", "is", "serializable", "." ]
[ "\"\"\"\n Convert all functions into sequence (including the QWaveform objects) that is serializable.\n\n :param maxEndTime: maximum ending time\n :return: dictionary containing the converted functions\n \"\"\"", "# Add QWaveform" ]
[ { "param": "self", "type": null }, { "param": "maxEndTime", "type": "float" } ]
{ "returns": [ { "docstring": "dictionary containing the converted functions", "docstring_tokens": [ "dictionary", "containing", "the", "converted", "functions" ], "type": null } ], "raises": [], "params": [ { "identifier": "self"...
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
clone
'QHamiltonian'
def clone(self) -> 'QHamiltonian': """ Return the copy of the object """ return copy.deepcopy(self)
Return the copy of the object
Return the copy of the object
[ "Return", "the", "copy", "of", "the", "object" ]
def clone(self) -> 'QHamiltonian': return copy.deepcopy(self)
[ "def", "clone", "(", "self", ")", "->", "'QHamiltonian'", ":", "return", "copy", ".", "deepcopy", "(", "self", ")" ]
Return the copy of the object
[ "Return", "the", "copy", "of", "the", "object" ]
[ "\"\"\"\n Return the copy of the object\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a0ea7aa1406ecbe5f3d196f05acbd1f4c08871c1
baidu/Quanlse
Quanlse/QHamiltonian.py
[ "Apache-2.0" ]
Python
load
'QHamiltonian'
def load(base64Str: str) -> 'QHamiltonian': """ Create object from base64 encoded string. :param base64Str: a base64 encoded string :return: QHam object """ byteStr = base64.b64decode(base64Str.encode()) obj = pickle.loads(byteStr) # type: QHamiltonian ...
Create object from base64 encoded string. :param base64Str: a base64 encoded string :return: QHam object
Create object from base64 encoded string.
[ "Create", "object", "from", "base64", "encoded", "string", "." ]
def load(base64Str: str) -> 'QHamiltonian': byteStr = base64.b64decode(base64Str.encode()) obj = pickle.loads(byteStr) if obj.job is not None: obj.job.parent = obj for opKey in obj.job.waves.keys(): for wave in obj.job.waves[opKey]: i...
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Create object from base64 encoded string.
[ "Create", "object", "from", "base64", "encoded", "string", "." ]
[ "\"\"\"\n Create object from base64 encoded string.\n\n :param base64Str: a base64 encoded string\n :return: QHam object\n \"\"\"", "# type: QHamiltonian", "# Set job's parent", "# For compatibility with previous versions" ]
[ { "param": "base64Str", "type": "str" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "base64Str", "type": "str", "docstring": "a base64 encoded string", "docstring_tokens": [ "a", "base...
f2b4181887398f97f74aeb5a0334bb228317a535
baidu/Quanlse
Quanlse/remoteSimulator.py
[ "Apache-2.0" ]
Python
remoteSimulatorRunHamiltonian
QResult
def remoteSimulatorRunHamiltonian(ham: QHam, state0: ndarray = None, job: QJob = None, jobList: QJobList = None, isOpen=False) -> QResult: """ Simulate the Hamiltonian using the Quanlse remote simulator. :param ham: the QHamiltonian object. :param state0: The initial s...
Simulate the Hamiltonian using the Quanlse remote simulator. :param ham: the QHamiltonian object. :param state0: The initial state. :param job: the QJob object. :param jobList: The QJobList object. :param isOpen: Run the simulation of open system using Lindblad master equation if true. :re...
Simulate the Hamiltonian using the Quanlse remote simulator.
[ "Simulate", "the", "Hamiltonian", "using", "the", "Quanlse", "remote", "simulator", "." ]
def remoteSimulatorRunHamiltonian(ham: QHam, state0: ndarray = None, job: QJob = None, jobList: QJobList = None, isOpen=False) -> QResult: maxEndTime = None kwargs = {} if state0 is not None: kwargs["state0"] = numpyMatrixToDictMatrix(state0) if job is not None:...
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Simulate the Hamiltonian using the Quanlse remote simulator.
[ "Simulate", "the", "Hamiltonian", "using", "the", "Quanlse", "remote", "simulator", "." ]
[ "\"\"\"\n Simulate the Hamiltonian using the Quanlse remote simulator.\n\n :param ham: the QHamiltonian object.\n :param state0: The initial state.\n :param job: the QJob object.\n :param jobList: The QJobList object.\n :param isOpen: Run the simulation of open system using Lindblad master equatio...
[ { "param": "ham", "type": "QHam" }, { "param": "state0", "type": "ndarray" }, { "param": "job", "type": "QJob" }, { "param": "jobList", "type": "QJobList" }, { "param": "isOpen", "type": null } ]
{ "returns": [ { "docstring": "the QResult object.", "docstring_tokens": [ "the", "QResult", "object", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "ham", "type": "QHam", "docstring": "the QHamiltonian ob...
c0b32108bce878d7f926a03fee3aad9f749f3d18
baidu/Quanlse
Quanlse/QOperation/RotationGate.py
[ "Apache-2.0" ]
Python
generateMatrix
numpy.ndarray
def generateMatrix(self) -> numpy.ndarray: """ Generate the matrix of rotation gate. """ self._generateUMatrix() return self._matrix
Generate the matrix of rotation gate.
Generate the matrix of rotation gate.
[ "Generate", "the", "matrix", "of", "rotation", "gate", "." ]
def generateMatrix(self) -> numpy.ndarray: self._generateUMatrix() return self._matrix
[ "def", "generateMatrix", "(", "self", ")", "->", "numpy", ".", "ndarray", ":", "self", ".", "_generateUMatrix", "(", ")", "return", "self", ".", "_matrix" ]
Generate the matrix of rotation gate.
[ "Generate", "the", "matrix", "of", "rotation", "gate", "." ]
[ "\"\"\"\n Generate the matrix of rotation gate.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
c0b32108bce878d7f926a03fee3aad9f749f3d18
baidu/Quanlse
Quanlse/QOperation/RotationGate.py
[ "Apache-2.0" ]
Python
_u3Matrix
numpy.ndarray
def _u3Matrix(self, theta: float, phi: float, lamda: float) -> numpy.ndarray: """ Generate a single-qubit rotation gate with 3 angles :param theta: angle :param phi: angle :param lamda: angle :return: U3 matrix """ self._matrix = numpy.array([[numpy.cos(...
Generate a single-qubit rotation gate with 3 angles :param theta: angle :param phi: angle :param lamda: angle :return: U3 matrix
Generate a single-qubit rotation gate with 3 angles
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def _u3Matrix(self, theta: float, phi: float, lamda: float) -> numpy.ndarray: self._matrix = numpy.array([[numpy.cos(theta / 2.0), -numpy.exp(1j * lamda) * numpy.sin(theta / 2.0)], [numpy.exp(1j * phi) * numpy.sin(theta / 2.0), numpy.exp(1...
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Generate a single-qubit rotation gate with 3 angles
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[ "\"\"\"\n Generate a single-qubit rotation gate with 3 angles\n\n :param theta: angle\n :param phi: angle\n :param lamda: angle\n :return: U3 matrix\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "theta", "type": "float" }, { "param": "phi", "type": "float" }, { "param": "lamda", "type": "float" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
c0b32108bce878d7f926a03fee3aad9f749f3d18
baidu/Quanlse
Quanlse/QOperation/RotationGate.py
[ "Apache-2.0" ]
Python
_u2Matrix
numpy.ndarray
def _u2Matrix(self, phi: float, lamda: float) -> numpy.ndarray: """ Generate a single-qubit rotation gate with 2 angles :param phi: angle :param lamda: angle :return: U2 matrix """ self._matrix = (1 / numpy.sqrt(2)) * numpy.array([[1, -numpy.exp(1j * lamda)], ...
Generate a single-qubit rotation gate with 2 angles :param phi: angle :param lamda: angle :return: U2 matrix
Generate a single-qubit rotation gate with 2 angles
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def _u2Matrix(self, phi: float, lamda: float) -> numpy.ndarray: self._matrix = (1 / numpy.sqrt(2)) * numpy.array([[1, -numpy.exp(1j * lamda)], [numpy.exp(1j * phi), numpy.exp(1j * (phi + lamda))]]) return self._matrix
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Generate a single-qubit rotation gate with 2 angles
[ "Generate", "a", "single", "-", "qubit", "rotation", "gate", "with", "2", "angles" ]
[ "\"\"\"\n Generate a single-qubit rotation gate with 2 angles\n\n :param phi: angle\n :param lamda: angle\n :return: U2 matrix\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "phi", "type": "float" }, { "param": "lamda", "type": "float" } ]
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c0b32108bce878d7f926a03fee3aad9f749f3d18
baidu/Quanlse
Quanlse/QOperation/RotationGate.py
[ "Apache-2.0" ]
Python
U
'OperationFunc'
def U(theta: 'RotationArgument', phi: Optional['RotationArgument'] = None, lamda: Optional['RotationArgument'] = None) -> 'OperationFunc': """ U Gate Generate a single-qubit U1 (or U2 or U3) gate according to the number of angles. """ uGateArgumentList = angleList = [value for value in ...
U Gate Generate a single-qubit U1 (or U2 or U3) gate according to the number of angles.
U Gate Generate a single-qubit U1 (or U2 or U3) gate according to the number of angles.
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def U(theta: 'RotationArgument', phi: Optional['RotationArgument'] = None, lamda: Optional['RotationArgument'] = None) -> 'OperationFunc': uGateArgumentList = angleList = [value for value in [theta, phi, lamda] if value is not None] gate = RotationGateOP('U', 1, angleList, uGateArgumentList) gat...
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U Gate Generate a single-qubit U1 (or U2 or U3) gate according to the number of angles.
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[ "\"\"\"\n U Gate\n\n Generate a single-qubit U1 (or U2 or U3) gate according to the number of angles.\n \"\"\"" ]
[ { "param": "theta", "type": "'RotationArgument'" }, { "param": "phi", "type": "Optional['RotationArgument']" }, { "param": "lamda", "type": "Optional['RotationArgument']" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "theta", "type": "'RotationArgument'", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "phi", "type": "Optional['RotationArgument']", "doc...
9a741ed1cb90a7d4c4d1cdf6a2855519a4f319fd
baidu/Quanlse
Quanlse/Utils/ODESolver.py
[ "Apache-2.0" ]
Python
_cacheDictToList
<not_specific>
def _cacheDictToList(ctrlCache: Dict[str, Any], waveCache: Dict[str, Any]): """ Convert the dict type cache to the list type. """ # Initialize ctrlList and waveList _ctrlList, _waveList = [], [] for ctrlKey in ctrlCache: _ctrlList.append(ctrlCache[ctrlKey]) _waveList.append(array...
Convert the dict type cache to the list type.
Convert the dict type cache to the list type.
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def _cacheDictToList(ctrlCache: Dict[str, Any], waveCache: Dict[str, Any]): _ctrlList, _waveList = [], [] for ctrlKey in ctrlCache: _ctrlList.append(ctrlCache[ctrlKey]) _waveList.append(array(waveCache[ctrlKey])) return _ctrlList, _waveList
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Convert the dict type cache to the list type.
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[ "\"\"\"\n Convert the dict type cache to the list type.\n \"\"\"", "# Initialize ctrlList and waveList" ]
[ { "param": "ctrlCache", "type": "Dict[str, Any]" }, { "param": "waveCache", "type": "Dict[str, Any]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "ctrlCache", "type": "Dict[str, Any]", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "waveCache", "type": "Dict[str, Any]", "docstring":...
9a741ed1cb90a7d4c4d1cdf6a2855519a4f319fd
baidu/Quanlse
Quanlse/Utils/ODESolver.py
[ "Apache-2.0" ]
Python
solverNormal
<not_specific>
def solverNormal(ham: 'QHamiltonian', state0=None, shot=None, recordEvolution=False, accelerate=False): """ Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and batch-job processing. :param ham: QHamiltonian object :param state0: the initial ...
Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and batch-job processing. :param ham: QHamiltonian object :param state0: the initial state vector. If None is given, this function will return the time-ordered evolution operato...
Calculate the unitary evolution operator with a given Hamiltonian. This function supports both single-job and batch-job processing.
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def solverNormal(ham: 'QHamiltonian', state0=None, shot=None, recordEvolution=False, accelerate=False): if accelerate: from Quanlse.Utils.NumbaSupport import expm else: from scipy.linalg import expm sysLevelLen = 1 if isinstance(ham.sysLevel, int) else len(ham.sysLevel) sysLevel = [ham.s...
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Calculate the unitary evolution operator with a given Hamiltonian.
[ "Calculate", "the", "unitary", "evolution", "operator", "with", "a", "given", "Hamiltonian", "." ]
[ "\"\"\"\n Calculate the unitary evolution operator with a given Hamiltonian. This function supports\n both single-job and batch-job processing.\n\n :param ham: QHamiltonian object\n :param state0: the initial state vector. If None is given, this function will return the time-ordered\n ...
[ { "param": "ham", "type": "'QHamiltonian'" }, { "param": "state0", "type": null }, { "param": "shot", "type": null }, { "param": "recordEvolution", "type": null }, { "param": "accelerate", "type": null } ]
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