qiskit.quantum_info.SparsePauliOp.sort¶
- SparsePauliOp.sort(weight=False)[source]¶
Sort the rows of the table.
After sorting the coefficients using numpy’s argsort, sort by Pauli. Pauli sort takes precedence. If Pauli is the same, it will be sorted by coefficient. By using the weight kwarg the output can additionally be sorted by the number of non-identity terms in the Pauli, where the set of all Pauli’s of a given weight are still ordered lexicographically.
Example
Here is an example of how to use SparsePauliOp sort.
import numpy as np from qiskit.quantum_info import SparsePauliOp # 2-qubit labels labels = ["XX", "XX", "XX", "YI", "II", "XZ", "XY", "XI"] # coeffs coeffs = [2.+1.j, 2.+2.j, 3.+0.j, 3.+0.j, 4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j] # init spo = SparsePauliOp(labels, coeffs) print('Initial Ordering') print(spo) # Lexicographic Ordering srt = spo.sort() print('Lexicographically sorted') print(srt) # Lexicographic Ordering srt = spo.sort(weight=False) print('Lexicographically sorted') print(srt) # Weight Ordering srt = spo.sort(weight=True) print('Weight sorted') print(srt)
Initial Ordering SparsePauliOp(['XX', 'XX', 'XX', 'YI', 'II', 'XZ', 'XY', 'XI'], coeffs=[2.+1.j, 2.+2.j, 3.+0.j, 3.+0.j, 4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j]) Lexicographically sorted SparsePauliOp(['II', 'XI', 'XX', 'XX', 'XX', 'XY', 'XZ', 'YI'], coeffs=[4.+0.j, 7.+0.j, 2.+1.j, 2.+2.j, 3.+0.j, 6.+0.j, 5.+0.j, 3.+0.j]) Lexicographically sorted SparsePauliOp(['II', 'XI', 'XX', 'XX', 'XX', 'XY', 'XZ', 'YI'], coeffs=[4.+0.j, 7.+0.j, 2.+1.j, 2.+2.j, 3.+0.j, 6.+0.j, 5.+0.j, 3.+0.j]) Weight sorted SparsePauliOp(['II', 'XI', 'YI', 'XX', 'XX', 'XX', 'XY', 'XZ'], coeffs=[4.+0.j, 7.+0.j, 3.+0.j, 2.+1.j, 2.+2.j, 3.+0.j, 6.+0.j, 5.+0.j])
- Paramètres
weight (bool) – optionally sort by weight if True (Default: False).
sorted (By using the weight kwarg the output can additionally be) –
Pauli. (by the number of non-identity terms in the) –
- Renvoie
a sorted copy of the original table.
- Type renvoyé