Source code for qiskit_algorithms.time_evolvers.time_evolution_result

# This code is part of a Qiskit project.
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# (C) Copyright IBM 2021, 2023.
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# This code is licensed under the Apache License, Version 2.0. You may
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"""Class for holding time evolution result."""
from __future__ import annotations
import numpy as np

from qiskit import QuantumCircuit
from qiskit.quantum_info import Statevector
from qiskit_algorithms.list_or_dict import ListOrDict
from ..algorithm_result import AlgorithmResult


[docs]class TimeEvolutionResult(AlgorithmResult): """ Class for holding time evolution result. Attributes: evolved_state (QuantumCircuit|Statevector): An evolved quantum state. aux_ops_evaluated (ListOrDict[tuple[complex, complex]] | None): Optional list of observables for which expected values on an evolved state are calculated. These values are in fact tuples formatted as (mean, standard deviation). observables (ListOrDict[tuple[np.ndarray, np.ndarray]] | None): Optional list of observables for which expected on an evolved state are calculated at each timestep. These values are in fact lists of tuples formatted as (mean, standard deviation). times (np.array | None): Optional list of times at which each observable has been evaluated. """ def __init__( self, evolved_state: QuantumCircuit | Statevector, aux_ops_evaluated: ListOrDict[tuple[complex, dict[str, complex]]] | None = None, observables: list[ListOrDict[tuple[complex, dict[str, complex]]]] | None = None, times: np.ndarray | None = None, ): """ Args: evolved_state: An evolved quantum state. aux_ops_evaluated: Optional list of observables for which expected values on an evolved state are calculated. These values are in fact tuples formatted as (mean, standard deviation). observables: Optional list of observables for which expected values are calculated for each timestep. These values are in fact tuples formatted as (mean array, standard deviation array). times: Optional list of times at which each observable has been evaluated. """ self.evolved_state = evolved_state self.aux_ops_evaluated = aux_ops_evaluated self.observables = observables self.times = times