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qiskit.quantum_info.states.random의 소스 코드

# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.

"""
Random state generation.
"""

import warnings
import numpy as np
from numpy.random import default_rng

from qiskit.exceptions import QiskitError
from qiskit.quantum_info.operators.random import random_unitary
from .statevector import Statevector
from .densitymatrix import DensityMatrix


[문서]def random_statevector(dims, seed=None): """Generator a random Statevector. The statevector is sampled from the uniform (Haar) measure. Args: dims (int or tuple): the dimensions of the state. seed (int or np.random.Generator): Optional. Set a fixed seed or generator for RNG. Returns: Statevector: the random statevector. """ if seed is None: rng = np.random.default_rng() elif isinstance(seed, np.random.Generator): rng = seed else: rng = default_rng(seed) dim = np.product(dims) # Random array over interval (0, 1] x = rng.random(dim) x += x == 0 x = -np.log(x) sumx = sum(x) phases = rng.random(dim) * 2.0 * np.pi return Statevector(np.sqrt(x / sumx) * np.exp(1j * phases), dims=dims)
[문서]def random_state(dim, seed=None): """ DEPRECATED Return a random quantum state. Args: dim (int): the dim of the state space seed (int or np.random.Generator): Optional. Set a fixed seed or generator for RNG. Returns: ndarray: state(2**num) a random quantum state. """ warnings.warn( 'The `random_state` function is deprecated as of 0.13.0,' ' and will be removed no earlier than 3 months after that ' 'release date. You should use the `random_statevector`' ' function instead.', DeprecationWarning, stacklevel=2) return random_statevector(dim, seed=seed).data
[문서]def random_density_matrix(dims, rank=None, method='Hilbert-Schmidt', seed=None): """Generator a random DensityMatrix. Args: dims (int or tuple): the dimensions of the DensityMatrix. rank (int or None): Optional, the rank of the density matrix. The default value is full-rank. method (string): Optional. The method to use. 'Hilbert-Schmidt': (Default) sample from the Hilbert-Schmidt metric. 'Bures': sample from the Bures metric. seed (int or np.random.Generator): Optional. Set a fixed seed or generator for RNG. Returns: DensityMatrix: the random density matrix. Raises: QiskitError: if the method is not valid. """ # Flatten dimensions dim = np.product(dims) if rank is None: rank = dim # Use full rank if method == 'Hilbert-Schmidt': rho = _random_density_hs(dim, rank, seed) elif method == 'Bures': rho = _random_density_bures(dim, rank, seed) else: raise QiskitError('Error: unrecognized method {}'.format(method)) return DensityMatrix(rho, dims=dims)
def _ginibre_matrix(nrow, ncol, seed): """Return a normally distributed complex random matrix. Args: nrow (int): number of rows in output matrix. ncol (int): number of columns in output matrix. seed(int or np.random.Generator): default rng. Returns: ndarray: A complex rectangular matrix where each real and imaginary entry is sampled from the normal distribution. """ if seed is None: rng = np.random.default_rng() elif isinstance(seed, np.random.Generator): rng = seed else: rng = default_rng(seed) ginibre = rng.normal( size=(nrow, ncol)) + rng.normal(size=(nrow, ncol)) * 1j return ginibre def _random_density_hs(dim, rank, seed): """ Generate a random density matrix from the Hilbert-Schmidt metric. Args: dim (int): the dimensions of the density matrix. rank (int or None): the rank of the density matrix. The default value is full-rank. seed (int or np.random.Generator): default rng. Returns: ndarray: rho (N,N) a density matrix. """ mat = _ginibre_matrix(dim, rank, seed) mat = mat.dot(mat.conj().T) return mat / np.trace(mat) def _random_density_bures(dim, rank, seed): """Generate a random density matrix from the Bures metric. Args: dim (int): the length of the density matrix. rank (int or None): the rank of the density matrix. The default value is full-rank. seed (int or np.random.Generator): default rng. Returns: ndarray: rho (N,N) a density matrix. """ density = np.eye(dim) + random_unitary(dim, seed=seed).data mat = density.dot(_ginibre_matrix(dim, rank, seed)) mat = mat.dot(mat.conj().T) return mat / np.trace(mat)

© Copyright 2020, Qiskit Development Team. 최종 업데이트: 2021/01/17

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