67 lines
2.6 KiB
Python
67 lines
2.6 KiB
Python
from copy import deepcopy
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from dataclasses import dataclass
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from typing import Union
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from numpy import ndarray
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from qibo.config import raise_error
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from qibotn.backends.abstract import QibotnBackend
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@dataclass
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class TensorNetworkResult:
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"""
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Object to store and process the output of a Tensor Network simulation of a quantum circuit.
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Args:
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nqubits (int): number of qubits involved in the simulation;
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backend (QibotnBackend): specific backend on which the simulation has been performed;
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measures (dict): measures (if performed) during the tensor network simulation;
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measured_probabilities (Union[dict, ndarray]): probabilities of the final state
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according to the simulation;
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prob_type (str): string identifying the method used to compute the probabilities.
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Especially useful in case the `QmatchateaBackend` is selected.
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statevector (ndarray): if computed, the reconstructed statevector.
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"""
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nqubits: int
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backend: QibotnBackend
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measures: dict
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measured_probabilities: Union[dict, ndarray]
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prob_type: str
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statevector: ndarray
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def __post_init__(self):
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# TODO: define the general convention when using backends different from qmatchatea
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if self.measured_probabilities is None:
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self.measured_probabilities = {"default": self.measured_probabilities}
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def probabilities(self):
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"""Return calculated probabilities according to the given method."""
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if self.prob_type == "U":
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measured_probabilities = deepcopy(self.measured_probabilities)
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for bitstring, prob in self.measured_probabilities[self.prob_type].items():
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measured_probabilities[self.prob_type][bitstring] = prob[1] - prob[0]
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probabilities = measured_probabilities[self.prob_type]
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else:
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probabilities = self.measured_probabilities
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return probabilities
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def frequencies(self):
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"""Return frequencies if a certain number of shots has been set."""
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if self.measures is None:
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raise_error(
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ValueError,
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f"To access frequencies, circuit has to be executed with a given number of shots != None",
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)
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return self.measures
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def state(self):
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"""Return the statevector if the number of qubits is less than 20."""
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if self.nqubits < 20:
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return self.statevector
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raise_error(
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NotImplementedError,
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f"Tensor network simulation cannot be used to reconstruct statevector for >= 20 .",
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)
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