Second Quantized Hamiltonian¶

In [ ]:

import numpy as np

from classiq import Model, construct_chemistry_model, execute, show, synthesize
from classiq.applications.chemistry import (
    ChemistryExecutionParameters,
    FermionicOperator,
    HamiltonianProblem,
    HEAParameters,
    SummedFermionicOperator,
)
from classiq.builtin_functions import HardwareEfficientAnsatz
from classiq.execution import OptimizerType

import numpy as np from classiq import Model, construct_chemistry_model, execute, show, synthesize from classiq.applications.chemistry import ( ChemistryExecutionParameters, FermionicOperator, HamiltonianProblem, HEAParameters, SummedFermionicOperator, ) from classiq.builtin_functions import HardwareEfficientAnsatz from classiq.execution import OptimizerType

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hamiltonian = SummedFermionicOperator(
    op_list=[
        (FermionicOperator(op_list=[("+", 0), ("-", 0)]), 0.2),
        (FermionicOperator(op_list=[("-", 1), ("-", 1)]), 0.3),
        (FermionicOperator(op_list=[("-", 2), ("-", 2)]), 0.4),
        (FermionicOperator(op_list=[("-", 3), ("-", 3)]), 0.5),
        (FermionicOperator(op_list=[("+", 0), ("+", 1), ("-", 1), ("-", 0)]), -0.1),
        (FermionicOperator(op_list=[("+", 2), ("+", 3), ("-", 2), ("-", 3)]), -0.3),
    ]
)
ham_problem = HamiltonianProblem(hamiltonian=hamiltonian, num_particles=[1, 1])

print(ham_problem.hamiltonian)

hamiltonian = SummedFermionicOperator( op_list=[ (FermionicOperator(op_list=[("+", 0), ("-", 0)]), 0.2), (FermionicOperator(op_list=[("-", 1), ("-", 1)]), 0.3), (FermionicOperator(op_list=[("-", 2), ("-", 2)]), 0.4), (FermionicOperator(op_list=[("-", 3), ("-", 3)]), 0.5), (FermionicOperator(op_list=[("+", 0), ("+", 1), ("-", 1), ("-", 0)]), -0.1), (FermionicOperator(op_list=[("+", 2), ("+", 3), ("-", 2), ("-", 3)]), -0.3), ] ) ham_problem = HamiltonianProblem(hamiltonian=hamiltonian, num_particles=[1, 1]) print(ham_problem.hamiltonian)

In [ ]:

hwea_params = HEAParameters(
    num_qubits=4,
    connectivity_map=[(0, 1), (1, 2), (2, 3)],
    reps=3,
    one_qubit_gates=["x", "ry"],
    two_qubit_gates=["cx"],
)

qmod = construct_chemistry_model(
    chemistry_problem=ham_problem,
    use_hartree_fock=False,
    ansatz_parameters=hwea_params,
    execution_parameters=ChemistryExecutionParameters(
        optimizer=OptimizerType.COBYLA,
        max_iteration=100,
        initial_point=None,
    ),
)

hwea_params = HEAParameters( num_qubits=4, connectivity_map=[(0, 1), (1, 2), (2, 3)], reps=3, one_qubit_gates=["x", "ry"], two_qubit_gates=["cx"], ) qmod = construct_chemistry_model( chemistry_problem=ham_problem, use_hartree_fock=False, ansatz_parameters=hwea_params, execution_parameters=ChemistryExecutionParameters( optimizer=OptimizerType.COBYLA, max_iteration=100, initial_point=None, ), )

In [ ]:

with open("second_quantized_hamiltonian.qmod", "w") as f:
    f.write(qmod)

with open("second_quantized_hamiltonian.qmod", "w") as f: f.write(qmod)

In [ ]:

qprog = synthesize(qmod)
show(qprog)

qprog = synthesize(qmod) show(qprog)

In [ ]:

results = execute(qprog).result()
chemistry_result = results[0].value
chemistry_result.energy

results = execute(qprog).result() chemistry_result = results[0].value chemistry_result.energy