Projeter des opérateurs de Pauli sur des sous-espaces de Hilbert
Nous présentons différentes façons de projeter une combinaison linéaire pondérée de chaînes de Pauli
dans un sous-espace défini par un sous-ensemble de états de la base computationnelle. L'
opérateur projeté est stocké sous la forme d'une scipy.sparse.coo_matrix de taille .
À titre d'exemple, nous considérons le hamiltonien du modèle de Heisenberg unidimensionnel avec conditions aux limites périodiques et spins :
Ce package fournit deux outils pour effectuer cette projection :
-
qiskit_addon_sqd.qubit.matrix_elements_from_pauli(): une fonction de plus bas niveau qui renvoie les éléments de matrice non nuls d'une chaîne de Pauli ainsi que les indices correspondants de ces éléments non nuls. -
qiskit_addon_sqd.qubit.project_operator_to_subspace(): a higher-level function that directly returns ascipy.sparsematrix.
Ce guide montre comment utiliser ces deux outils pour produire le même opérateur creux.
Définition du sous-espace
Pour cet exemple, nous générons des chaînes de bits aléatoires de longueur 22. Pour que les fonctions de projection fonctionnent comme prévu, il est essentiel que les chaînes de bits qui définissent le sous-espace soient uniques et triées par ordre croissant selon leur représentation entière non signée.
Cela peut être réalisé avec la fonction qiskit_addon_sqd.qubit.sort_and_remove_duplicates().
# Added by doQumentation — installs the packages this notebook needs if they are missing
import importlib.util
_needed = {"numpy": "numpy", "qiskit": "qiskit", "qiskit_addon_sqd": "qiskit-addon-sqd", "qiskit_addon_utils": "qiskit-addon-utils", "scipy": "scipy"}
_missing = [pip for module, pip in _needed.items()
if importlib.util.find_spec(module) is None]
# One at a time, so a package that fails to install does not block the others
for _pip in _missing:
%pip install -q {_pip}
if not _missing:
print("\u2713 All required packages are installed")
import numpy as np
from qiskit_addon_sqd.qubit import sort_and_remove_duplicates
num_spins = 22
rand_seed = 22
np.random.seed(rand_seed)
def random_bitstrings(n_samples, n_qubits):
return (
np.round(np.random.rand(n_samples, n_qubits))
.astype("int")
.astype("bool")
)
bitstring_matrix = random_bitstrings(50_000, num_spins)
# NOTE: It is essential for the projection code to have the bitstrings sorted!
bitstring_matrix = sort_and_remove_duplicates(bitstring_matrix)
print("Subspace dimension: " + str(bitstring_matrix.shape[0]))
print("Full Hilbert space dimension: " + str(2**num_spins))
Subspace dimension: 49718
Full Hilbert space dimension: 4194304
Première méthode : éléments de matrice non nuls et indices
from qiskit.transpiler import CouplingMap
from qiskit_addon_utils.problem_generators import generate_xyz_hamiltonian
coupling_map = CouplingMap.from_ring(num_spins)
hamiltonian = generate_xyz_hamiltonian(coupling_map)
print(hamiltonian)
SparsePauliOp(['IIIIIIIIIIIIIIIIIIIIXX', 'IIIIIIIIIIIIIIIIIIIIYY', 'IIIIIIIIIIIIIIIIIIIIZZ', 'IIIIIIIIIIIIIIIIIIXXII', 'IIIIIIIIIIIIIIIIIIYYII', 'IIIIIIIIIIIIIIIIIIZZII', 'IIIIIIIIIIIIIIIIXXIIII', 'IIIIIIIIIIIIIIIIYYIIII', 'IIIIIIIIIIIIIIIIZZIIII', 'IIIIIIIIIIIIIIXXIIIIII', 'IIIIIIIIIIIIIIYYIIIIII', 'IIIIIIIIIIIIIIZZIIIIII', 'IIIIIIIIIIIIXXIIIIIIII', 'IIIIIIIIIIIIYYIIIIIIII', 'IIIIIIIIIIIIZZIIIIIIII', 'IIIIIIIIIIXXIIIIIIIIII', 'IIIIIIIIIIYYIIIIIIIIII', 'IIIIIIIIIIZZIIIIIIIIII', 'IIIIIIIIXXIIIIIIIIIIII', 'IIIIIIIIYYIIIIIIIIIIII', 'IIIIIIIIZZIIIIIIIIIIII', 'IIIIIIXXIIIIIIIIIIIIII', 'IIIIIIYYIIIIIIIIIIIIII', 'IIIIIIZZIIIIIIIIIIIIII', 'IIIIXXIIIIIIIIIIIIIIII', 'IIIIYYIIIIIIIIIIIIIIII', 'IIIIZZIIIIIIIIIIIIIIII', 'IIXXIIIIIIIIIIIIIIIIII', 'IIYYIIIIIIIIIIIIIIIIII', 'IIZZIIIIIIIIIIIIIIIIII', 'XXIIIIIIIIIIIIIIIIIIII', 'YYIIIIIIIIIIIIIIIIIIII', 'ZZIIIIIIIIIIIIIIIIIIII', 'XIIIIIIIIIIIIIIIIIIIIX', 'YIIIIIIIIIIIIIIIIIIIIY', 'ZIIIIIIIIIIIIIIIIIIIIZ', 'IIIIIIIIIIIIIIIIIIIXXI', 'IIIIIIIIIIIIIIIIIIIYYI', 'IIIIIIIIIIIIIIIIIIIZZI', 'IIIIIIIIIIIIIIIIIXXIII', 'IIIIIIIIIIIIIIIIIYYIII', 'IIIIIIIIIIIIIIIIIZZIII', 'IIIIIIIIIIIIIIIXXIIIII', 'IIIIIIIIIIIIIIIYYIIIII', 'IIIIIIIIIIIIIIIZZIIIII', 'IIIIIIIIIIIIIXXIIIIIII', 'IIIIIIIIIIIIIYYIIIIIII', 'IIIIIIIIIIIIIZZIIIIIII', 'IIIIIIIIIIIXXIIIIIIIII', 'IIIIIIIIIIIYYIIIIIIIII', 'IIIIIIIIIIIZZIIIIIIIII', 'IIIIIIIIIXXIIIIIIIIIII', 'IIIIIIIIIYYIIIIIIIIIII', 'IIIIIIIIIZZIIIIIIIIIII', 'IIIIIIIXXIIIIIIIIIIIII', 'IIIIIIIYYIIIIIIIIIIIII', 'IIIIIIIZZIIIIIIIIIIIII', 'IIIIIXXIIIIIIIIIIIIIII', 'IIIIIYYIIIIIIIIIIIIIII', 'IIIIIZZIIIIIIIIIIIIIII', 'IIIXXIIIIIIIIIIIIIIIII', 'IIIYYIIIIIIIIIIIIIIIII', 'IIIZZIIIIIIIIIIIIIIIII', 'IXXIIIIIIIIIIIIIIIIIII', 'IYYIIIIIIIIIIIIIIIIIII', 'IZZIIIIIIIIIIIIIIIIIII'],
coeffs=[1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j, 1.+0.j,
1.+0.j, 1.+0.j, 1.+0.j])
from qiskit_addon_sqd.qubit import matrix_elements_from_pauli
from scipy.sparse import coo_matrix
d = bitstring_matrix.shape[0]
# Initialize the coo_matrix object
operator_from_matrix_elements = coo_matrix((d, d), dtype="complex128")
for pauli in hamiltonian.paulis:
matrix_elements, row_indices, col_indices = matrix_elements_from_pauli(
bitstring_matrix, pauli
)
operator_from_matrix_elements += coo_matrix(
(matrix_elements, (row_indices, col_indices)), (d, d)
)
Implémentation de plus haut niveau
from qiskit_addon_sqd.qubit import project_operator_to_subspace
operator = project_operator_to_subspace(
bitstring_matrix, hamiltonian, verbose=True
)
Projecting term 1 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIIIXX ...
Projecting term 2 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIIIYY ...
Projecting term 3 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIIIZZ ...
Projecting term 4 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIXXII ...
Projecting term 5 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIYYII ...
Projecting term 6 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIZZII ...
Projecting term 7 out of 66: (1+0j) * IIIIIIIIIIIIIIIIXXIIII ...
Projecting term 8 out of 66: (1+0j) * IIIIIIIIIIIIIIIIYYIIII ...
Projecting term 9 out of 66: (1+0j) * IIIIIIIIIIIIIIIIZZIIII ...
Projecting term 10 out of 66: (1+0j) * IIIIIIIIIIIIIIXXIIIIII ...
Projecting term 11 out of 66: (1+0j) * IIIIIIIIIIIIIIYYIIIIII ...
Projecting term 12 out of 66: (1+0j) * IIIIIIIIIIIIIIZZIIIIII ...
Projecting term 13 out of 66: (1+0j) * IIIIIIIIIIIIXXIIIIIIII ...
Projecting term 14 out of 66: (1+0j) * IIIIIIIIIIIIYYIIIIIIII ...
Projecting term 15 out of 66: (1+0j) * IIIIIIIIIIIIZZIIIIIIII ...
Projecting term 16 out of 66: (1+0j) * IIIIIIIIIIXXIIIIIIIIII ...
Projecting term 17 out of 66: (1+0j) * IIIIIIIIIIYYIIIIIIIIII ...
Projecting term 18 out of 66: (1+0j) * IIIIIIIIIIZZIIIIIIIIII ...
Projecting term 19 out of 66: (1+0j) * IIIIIIIIXXIIIIIIIIIIII ...
Projecting term 20 out of 66: (1+0j) * IIIIIIIIYYIIIIIIIIIIII ...
Projecting term 21 out of 66: (1+0j) * IIIIIIIIZZIIIIIIIIIIII ...
Projecting term 22 out of 66: (1+0j) * IIIIIIXXIIIIIIIIIIIIII ...
Projecting term 23 out of 66: (1+0j) * IIIIIIYYIIIIIIIIIIIIII ...
Projecting term 24 out of 66: (1+0j) * IIIIIIZZIIIIIIIIIIIIII ...
Projecting term 25 out of 66: (1+0j) * IIIIXXIIIIIIIIIIIIIIII ...
Projecting term 26 out of 66: (1+0j) * IIIIYYIIIIIIIIIIIIIIII ...
Projecting term 27 out of 66: (1+0j) * IIIIZZIIIIIIIIIIIIIIII ...
Projecting term 28 out of 66: (1+0j) * IIXXIIIIIIIIIIIIIIIIII ...
Projecting term 29 out of 66: (1+0j) * IIYYIIIIIIIIIIIIIIIIII ...
Projecting term 30 out of 66: (1+0j) * IIZZIIIIIIIIIIIIIIIIII ...
Projecting term 31 out of 66: (1+0j) * XXIIIIIIIIIIIIIIIIIIII ...
Projecting term 32 out of 66: (1+0j) * YYIIIIIIIIIIIIIIIIIIII ...
Projecting term 33 out of 66: (1+0j) * ZZIIIIIIIIIIIIIIIIIIII ...
Projecting term 34 out of 66: (1+0j) * XIIIIIIIIIIIIIIIIIIIIX ...
Projecting term 35 out of 66: (1+0j) * YIIIIIIIIIIIIIIIIIIIIY ...
Projecting term 36 out of 66: (1+0j) * ZIIIIIIIIIIIIIIIIIIIIZ ...
Projecting term 37 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIIXXI ...
Projecting term 38 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIIYYI ...
Projecting term 39 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIIIZZI ...
Projecting term 40 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIXXIII ...
Projecting term 41 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIYYIII ...
Projecting term 42 out of 66: (1+0j) * IIIIIIIIIIIIIIIIIZZIII ...
Projecting term 43 out of 66: (1+0j) * IIIIIIIIIIIIIIIXXIIIII ...
Projecting term 44 out of 66: (1+0j) * IIIIIIIIIIIIIIIYYIIIII ...
Projecting term 45 out of 66: (1+0j) * IIIIIIIIIIIIIIIZZIIIII ...
Projecting term 46 out of 66: (1+0j) * IIIIIIIIIIIIIXXIIIIIII ...
Projecting term 47 out of 66: (1+0j) * IIIIIIIIIIIIIYYIIIIIII ...
Projecting term 48 out of 66: (1+0j) * IIIIIIIIIIIIIZZIIIIIII ...
Projecting term 49 out of 66: (1+0j) * IIIIIIIIIIIXXIIIIIIIII ...
Projecting term 50 out of 66: (1+0j) * IIIIIIIIIIIYYIIIIIIIII ...
Projecting term 51 out of 66: (1+0j) * IIIIIIIIIIIZZIIIIIIIII ...
Projecting term 52 out of 66: (1+0j) * IIIIIIIIIXXIIIIIIIIIII ...
Projecting term 53 out of 66: (1+0j) * IIIIIIIIIYYIIIIIIIIIII ...
Projecting term 54 out of 66: (1+0j) * IIIIIIIIIZZIIIIIIIIIII ...
Projecting term 55 out of 66: (1+0j) * IIIIIIIXXIIIIIIIIIIIII ...
Projecting term 56 out of 66: (1+0j) * IIIIIIIYYIIIIIIIIIIIII ...
Projecting term 57 out of 66: (1+0j) * IIIIIIIZZIIIIIIIIIIIII ...
Projecting term 58 out of 66: (1+0j) * IIIIIXXIIIIIIIIIIIIIII ...
Projecting term 59 out of 66: (1+0j) * IIIIIYYIIIIIIIIIIIIIII ...
Projecting term 60 out of 66: (1+0j) * IIIIIZZIIIIIIIIIIIIIII ...
Projecting term 61 out of 66: (1+0j) * IIIXXIIIIIIIIIIIIIIIII ...
Projecting term 62 out of 66: (1+0j) * IIIYYIIIIIIIIIIIIIIIII ...
Projecting term 63 out of 66: (1+0j) * IIIZZIIIIIIIIIIIIIIIII ...
Projecting term 64 out of 66: (1+0j) * IXXIIIIIIIIIIIIIIIIIII ...
Projecting term 65 out of 66: (1+0j) * IYYIIIIIIIIIIIIIIIIIII ...
Projecting term 66 out of 66: (1+0j) * IZZIIIIIIIIIIIIIIIIIII ...
Vérifie que les deux implémentations donnent la même coo_matrix :
print((operator.power(2) - operator_from_matrix_elements.power(2)).sum())
0j