repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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partitioning-with-cliffords | partitioning-with-cliffords-main/code/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/code/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/code/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/code/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/code/h_vqe.py | import tequila as tq
from openfermion import QubitOperator
from vqe_utils import *
from scipy_optimizer import *
import time
def run_optimization(unitary, Hamiltonian, initial_values):
"""
This function takes the Hamiltonian and breaks it into ExpectationValues so that
it can be simulated using tequila
... | 6,902 | 37.138122 | 125 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/code/get_final_plots.py | import tequila as tq
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from mutation_options import *
from typing import List, Tuple
import sys
sys.path.append('/h/292/philipps/Documents/qcss/tenerq/qcss-lanl-tenerq/tn_update')
from my_mpo import *
increase_mode = 1
export_fig = False
def ge... | 11,380 | 37.843003 | 142 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/code/main_heisenberg.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,407 | 40.617978 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/plot.py | import matplotlib
from matplotlib import pyplot as plt
import os
# import seaborn as sns
bond_l = []
c_bond_l = []
data_ref = []
data_cliff = []
data_ncliff = []
data_fci = []
folder_str = "h2_bl_{0}"
for bl in range(5, 31):
b_l = bl/10.
bond_l.append(b_l)
folder = folder_str.format(b_l)
for file in o... | 4,359 | 33.0625 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/my_mpo.py | import numpy as np
import tensornetwork as tn
from tensornetwork.backends.abstract_backend import AbstractBackend
tn.set_default_backend("pytorch")
#tn.set_default_backend("numpy")
from typing import List, Union, Text, Optional, Any, Type
Tensor = Any
import tequila as tq
import torch
EPS = 1e-12
class SubOperator... | 14,354 | 36.480418 | 99 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/do_annealing.py | import tequila as tq
import numpy as np
import pickle
from pathos.multiprocessing import ProcessingPool as Pool
from parallel_annealing import *
#from dummy_par import *
from mutation_options import *
from single_thread_annealing import *
def find_best_instructions(instructions_dict):
"""
This function finds... | 13,155 | 46.154122 | 187 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/scipy_optimizer.py | import numpy, copy, scipy, typing, numbers
from tequila import BitString, BitNumbering, BitStringLSB
from tequila.utils.keymap import KeyMapRegisterToSubregister
from tequila.circuit.compiler import change_basis
from tequila.utils import to_float
import tequila as tq
from tequila.objective import Objective
from tequi... | 24,489 | 42.732143 | 144 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/energy_optimization.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
... | 12,457 | 43.021201 | 225 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/parallel_annealing.py | import tequila as tq
import multiprocessing
import copy
from time import sleep
from mutation_options import *
from pathos.multiprocessing import ProcessingPool as Pool
def evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
process_id,
... | 6,456 | 38.371951 | 146 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/single_thread_annealing.py | import tequila as tq
import copy
from mutation_options import *
def st_evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
num_offsprings,
actions_ratio,
tasks):
"""
This function carrie... | 4,005 | 40.298969 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/mutation_options.py | import argparse
import numpy as np
import random
import copy
import tequila as tq
from typing import Union
from collections import Counter
from time import time
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import minimi... | 26,497 | 34.096689 | 191 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/hacked_openfermion_qubit_operator.py | import tequila as tq
import sympy
import copy
#from param_hamiltonian import get_geometry, generate_ucc_ansatz
from hacked_openfermion_symbolic_operator import SymbolicOperator
# Define products of all Pauli operators for symbolic multiplication.
_PAULI_OPERATOR_PRODUCTS = {
('I', 'I'): (1., 'I'),
('I', 'X')... | 9,918 | 29.614198 | 85 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.4/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/my_mpo.py | import numpy as np
import tensornetwork as tn
from tensornetwork.backends.abstract_backend import AbstractBackend
tn.set_default_backend("pytorch")
#tn.set_default_backend("numpy")
from typing import List, Union, Text, Optional, Any, Type
Tensor = Any
import tequila as tq
import torch
EPS = 1e-12
class SubOperator... | 14,354 | 36.480418 | 99 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/do_annealing.py | import tequila as tq
import numpy as np
import pickle
from pathos.multiprocessing import ProcessingPool as Pool
from parallel_annealing import *
#from dummy_par import *
from mutation_options import *
from single_thread_annealing import *
def find_best_instructions(instructions_dict):
"""
This function finds... | 13,155 | 46.154122 | 187 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/scipy_optimizer.py | import numpy, copy, scipy, typing, numbers
from tequila import BitString, BitNumbering, BitStringLSB
from tequila.utils.keymap import KeyMapRegisterToSubregister
from tequila.circuit.compiler import change_basis
from tequila.utils import to_float
import tequila as tq
from tequila.objective import Objective
from tequi... | 24,489 | 42.732143 | 144 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/energy_optimization.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
... | 12,457 | 43.021201 | 225 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/parallel_annealing.py | import tequila as tq
import multiprocessing
import copy
from time import sleep
from mutation_options import *
from pathos.multiprocessing import ProcessingPool as Pool
def evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
process_id,
... | 6,456 | 38.371951 | 146 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/single_thread_annealing.py | import tequila as tq
import copy
from mutation_options import *
def st_evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
num_offsprings,
actions_ratio,
tasks):
"""
This function carrie... | 4,005 | 40.298969 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/mutation_options.py | import argparse
import numpy as np
import random
import copy
import tequila as tq
from typing import Union
from collections import Counter
from time import time
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import minimi... | 26,497 | 34.096689 | 191 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/hacked_openfermion_qubit_operator.py | import tequila as tq
import sympy
import copy
#from param_hamiltonian import get_geometry, generate_ucc_ansatz
from hacked_openfermion_symbolic_operator import SymbolicOperator
# Define products of all Pauli operators for symbolic multiplication.
_PAULI_OPERATOR_PRODUCTS = {
('I', 'I'): (1., 'I'),
('I', 'X')... | 9,918 | 29.614198 | 85 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.3/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/my_mpo.py | import numpy as np
import tensornetwork as tn
from tensornetwork.backends.abstract_backend import AbstractBackend
tn.set_default_backend("pytorch")
#tn.set_default_backend("numpy")
from typing import List, Union, Text, Optional, Any, Type
Tensor = Any
import tequila as tq
import torch
EPS = 1e-12
class SubOperator... | 14,354 | 36.480418 | 99 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/do_annealing.py | import tequila as tq
import numpy as np
import pickle
from pathos.multiprocessing import ProcessingPool as Pool
from parallel_annealing import *
#from dummy_par import *
from mutation_options import *
from single_thread_annealing import *
def find_best_instructions(instructions_dict):
"""
This function finds... | 13,155 | 46.154122 | 187 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/scipy_optimizer.py | import numpy, copy, scipy, typing, numbers
from tequila import BitString, BitNumbering, BitStringLSB
from tequila.utils.keymap import KeyMapRegisterToSubregister
from tequila.circuit.compiler import change_basis
from tequila.utils import to_float
import tequila as tq
from tequila.objective import Objective
from tequi... | 24,489 | 42.732143 | 144 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/energy_optimization.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
... | 12,457 | 43.021201 | 225 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/parallel_annealing.py | import tequila as tq
import multiprocessing
import copy
from time import sleep
from mutation_options import *
from pathos.multiprocessing import ProcessingPool as Pool
def evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
process_id,
... | 6,456 | 38.371951 | 146 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/single_thread_annealing.py | import tequila as tq
import copy
from mutation_options import *
def st_evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
num_offsprings,
actions_ratio,
tasks):
"""
This function carrie... | 4,005 | 40.298969 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/mutation_options.py | import argparse
import numpy as np
import random
import copy
import tequila as tq
from typing import Union
from collections import Counter
from time import time
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import minimi... | 26,497 | 34.096689 | 191 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/hacked_openfermion_qubit_operator.py | import tequila as tq
import sympy
import copy
#from param_hamiltonian import get_geometry, generate_ucc_ansatz
from hacked_openfermion_symbolic_operator import SymbolicOperator
# Define products of all Pauli operators for symbolic multiplication.
_PAULI_OPERATOR_PRODUCTS = {
('I', 'I'): (1., 'I'),
('I', 'X')... | 9,918 | 29.614198 | 85 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.3/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/my_mpo.py | import numpy as np
import tensornetwork as tn
from tensornetwork.backends.abstract_backend import AbstractBackend
tn.set_default_backend("pytorch")
#tn.set_default_backend("numpy")
from typing import List, Union, Text, Optional, Any, Type
Tensor = Any
import tequila as tq
import torch
EPS = 1e-12
class SubOperator... | 14,354 | 36.480418 | 99 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/do_annealing.py | import tequila as tq
import numpy as np
import pickle
from pathos.multiprocessing import ProcessingPool as Pool
from parallel_annealing import *
#from dummy_par import *
from mutation_options import *
from single_thread_annealing import *
def find_best_instructions(instructions_dict):
"""
This function finds... | 13,155 | 46.154122 | 187 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/scipy_optimizer.py | import numpy, copy, scipy, typing, numbers
from tequila import BitString, BitNumbering, BitStringLSB
from tequila.utils.keymap import KeyMapRegisterToSubregister
from tequila.circuit.compiler import change_basis
from tequila.utils import to_float
import tequila as tq
from tequila.objective import Objective
from tequi... | 24,489 | 42.732143 | 144 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/energy_optimization.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
... | 12,457 | 43.021201 | 225 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/parallel_annealing.py | import tequila as tq
import multiprocessing
import copy
from time import sleep
from mutation_options import *
from pathos.multiprocessing import ProcessingPool as Pool
def evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
process_id,
... | 6,456 | 38.371951 | 146 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/single_thread_annealing.py | import tequila as tq
import copy
from mutation_options import *
def st_evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
num_offsprings,
actions_ratio,
tasks):
"""
This function carrie... | 4,005 | 40.298969 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/mutation_options.py | import argparse
import numpy as np
import random
import copy
import tequila as tq
from typing import Union
from collections import Counter
from time import time
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import minimi... | 26,497 | 34.096689 | 191 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/hacked_openfermion_qubit_operator.py | import tequila as tq
import sympy
import copy
#from param_hamiltonian import get_geometry, generate_ucc_ansatz
from hacked_openfermion_symbolic_operator import SymbolicOperator
# Define products of all Pauli operators for symbolic multiplication.
_PAULI_OPERATOR_PRODUCTS = {
('I', 'I'): (1., 'I'),
('I', 'X')... | 9,918 | 29.614198 | 85 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.2/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/my_mpo.py | import numpy as np
import tensornetwork as tn
from tensornetwork.backends.abstract_backend import AbstractBackend
tn.set_default_backend("pytorch")
#tn.set_default_backend("numpy")
from typing import List, Union, Text, Optional, Any, Type
Tensor = Any
import tequila as tq
import torch
EPS = 1e-12
class SubOperator... | 14,354 | 36.480418 | 99 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/do_annealing.py | import tequila as tq
import numpy as np
import pickle
from pathos.multiprocessing import ProcessingPool as Pool
from parallel_annealing import *
#from dummy_par import *
from mutation_options import *
from single_thread_annealing import *
def find_best_instructions(instructions_dict):
"""
This function finds... | 13,155 | 46.154122 | 187 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/scipy_optimizer.py | import numpy, copy, scipy, typing, numbers
from tequila import BitString, BitNumbering, BitStringLSB
from tequila.utils.keymap import KeyMapRegisterToSubregister
from tequila.circuit.compiler import change_basis
from tequila.utils import to_float
import tequila as tq
from tequila.objective import Objective
from tequi... | 24,489 | 42.732143 | 144 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/energy_optimization.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
... | 12,457 | 43.021201 | 225 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/parallel_annealing.py | import tequila as tq
import multiprocessing
import copy
from time import sleep
from mutation_options import *
from pathos.multiprocessing import ProcessingPool as Pool
def evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
process_id,
... | 6,456 | 38.371951 | 146 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/single_thread_annealing.py | import tequila as tq
import copy
from mutation_options import *
def st_evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
num_offsprings,
actions_ratio,
tasks):
"""
This function carrie... | 4,005 | 40.298969 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/mutation_options.py | import argparse
import numpy as np
import random
import copy
import tequila as tq
from typing import Union
from collections import Counter
from time import time
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import minimi... | 26,497 | 34.096689 | 191 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/hacked_openfermion_qubit_operator.py | import tequila as tq
import sympy
import copy
#from param_hamiltonian import get_geometry, generate_ucc_ansatz
from hacked_openfermion_symbolic_operator import SymbolicOperator
# Define products of all Pauli operators for symbolic multiplication.
_PAULI_OPERATOR_PRODUCTS = {
('I', 'I'): (1., 'I'),
('I', 'X')... | 9,918 | 29.614198 | 85 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.1/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/my_mpo.py | import numpy as np
import tensornetwork as tn
from tensornetwork.backends.abstract_backend import AbstractBackend
tn.set_default_backend("pytorch")
#tn.set_default_backend("numpy")
from typing import List, Union, Text, Optional, Any, Type
Tensor = Any
import tequila as tq
import torch
EPS = 1e-12
class SubOperator... | 14,354 | 36.480418 | 99 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/do_annealing.py | import tequila as tq
import numpy as np
import pickle
from pathos.multiprocessing import ProcessingPool as Pool
from parallel_annealing import *
#from dummy_par import *
from mutation_options import *
from single_thread_annealing import *
def find_best_instructions(instructions_dict):
"""
This function finds... | 13,155 | 46.154122 | 187 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/scipy_optimizer.py | import numpy, copy, scipy, typing, numbers
from tequila import BitString, BitNumbering, BitStringLSB
from tequila.utils.keymap import KeyMapRegisterToSubregister
from tequila.circuit.compiler import change_basis
from tequila.utils import to_float
import tequila as tq
from tequila.objective import Objective
from tequi... | 24,489 | 42.732143 | 144 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/energy_optimization.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
... | 12,457 | 43.021201 | 225 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/parallel_annealing.py | import tequila as tq
import multiprocessing
import copy
from time import sleep
from mutation_options import *
from pathos.multiprocessing import ProcessingPool as Pool
def evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
process_id,
... | 6,456 | 38.371951 | 146 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/single_thread_annealing.py | import tequila as tq
import copy
from mutation_options import *
def st_evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
num_offsprings,
actions_ratio,
tasks):
"""
This function carrie... | 4,005 | 40.298969 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/mutation_options.py | import argparse
import numpy as np
import random
import copy
import tequila as tq
from typing import Union
from collections import Counter
from time import time
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import minimi... | 26,497 | 34.096689 | 191 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/hacked_openfermion_qubit_operator.py | import tequila as tq
import sympy
import copy
#from param_hamiltonian import get_geometry, generate_ucc_ansatz
from hacked_openfermion_symbolic_operator import SymbolicOperator
# Define products of all Pauli operators for symbolic multiplication.
_PAULI_OPERATOR_PRODUCTS = {
('I', 'I'): (1., 'I'),
('I', 'X')... | 9,918 | 29.614198 | 85 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.0/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/my_mpo.py | import numpy as np
import tensornetwork as tn
from tensornetwork.backends.abstract_backend import AbstractBackend
tn.set_default_backend("pytorch")
#tn.set_default_backend("numpy")
from typing import List, Union, Text, Optional, Any, Type
Tensor = Any
import tequila as tq
import torch
EPS = 1e-12
class SubOperator... | 14,354 | 36.480418 | 99 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/do_annealing.py | import tequila as tq
import numpy as np
import pickle
from pathos.multiprocessing import ProcessingPool as Pool
from parallel_annealing import *
#from dummy_par import *
from mutation_options import *
from single_thread_annealing import *
def find_best_instructions(instructions_dict):
"""
This function finds... | 13,155 | 46.154122 | 187 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/scipy_optimizer.py | import numpy, copy, scipy, typing, numbers
from tequila import BitString, BitNumbering, BitStringLSB
from tequila.utils.keymap import KeyMapRegisterToSubregister
from tequila.circuit.compiler import change_basis
from tequila.utils import to_float
import tequila as tq
from tequila.objective import Objective
from tequi... | 24,489 | 42.732143 | 144 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/energy_optimization.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
... | 12,457 | 43.021201 | 225 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/parallel_annealing.py | import tequila as tq
import multiprocessing
import copy
from time import sleep
from mutation_options import *
from pathos.multiprocessing import ProcessingPool as Pool
def evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
process_id,
... | 6,456 | 38.371951 | 146 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/single_thread_annealing.py | import tequila as tq
import copy
from mutation_options import *
def st_evolve_population(hamiltonian,
type_energy_eval,
cluster_circuit,
num_offsprings,
actions_ratio,
tasks):
"""
This function carrie... | 4,005 | 40.298969 | 138 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/mutation_options.py | import argparse
import numpy as np
import random
import copy
import tequila as tq
from typing import Union
from collections import Counter
from time import time
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import minimi... | 26,497 | 34.096689 | 191 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/hacked_openfermion_qubit_operator.py | import tequila as tq
import sympy
import copy
#from param_hamiltonian import get_geometry, generate_ucc_ansatz
from hacked_openfermion_symbolic_operator import SymbolicOperator
# Define products of all Pauli operators for symbolic multiplication.
_PAULI_OPERATOR_PRODUCTS = {
('I', 'I'): (1., 'I'),
('I', 'X')... | 9,918 | 29.614198 | 85 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/HEA.py | import tequila as tq
import numpy as np
from tequila import gates as tq_g
from tequila.objective.objective import Variable
def generate_HEA(num_qubits, circuit_id=11, num_layers=1):
"""
This function generates different types of hardware efficient
circuits as in this paper
https://onlinelibrary.wiley.... | 18,425 | 45.530303 | 172 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/grad_hacked.py | from tequila.circuit.compiler import CircuitCompiler
from tequila.objective.objective import Objective, ExpectationValueImpl, Variable, \
assign_variable, identity, FixedVariable
from tequila import TequilaException
from tequila.objective import QTensor
from tequila.simulators.simulator_api import compile
import ty... | 9,886 | 38.548 | 132 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/vqe_utils.py | import tequila as tq
import numpy as np
from hacked_openfermion_qubit_operator import ParamQubitHamiltonian
from openfermion import QubitOperator
from HEA import *
def get_ansatz_circuit(ansatz_type, geometry, basis_set=None, trotter_steps = 1, name=None, circuit_id=None,num_layers=1):
"""
This function gene... | 27,934 | 51.807183 | 162 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_2.6/hacked_openfermion_symbolic_operator.py | import abc
import copy
import itertools
import re
import warnings
import sympy
import tequila as tq
from tequila.objective.objective import Objective, Variable
from openfermion.config import EQ_TOLERANCE
COEFFICIENT_TYPES = (int, float, complex, sympy.Expr, Variable, Objective)
class SymbolicOperator(metaclass=ab... | 25,797 | 35.697013 | 97 | py |
partitioning-with-cliffords | partitioning-with-cliffords-main/data/h2/h2_bl_1.6/main.py | import tequila as tq
import numpy as np
from tequila.objective.objective import Variable
import openfermion
from typing import Union
from vqe_utils import convert_PQH_to_tq_QH, convert_tq_QH_to_PQH,\
fold_unitary_into_hamiltonian
from energy_optimization import *
from do_annealing import *
impor... | 7,368 | 40.869318 | 129 | py |
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