.png){kind=icon}
Return
Random Sampling of Permutations Using Quantum Circuits
.png){kind=icon}
PRE
AI
DOI：10.1109/TCAD.2025.3591735.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this article, we introduce a classical algorithm for random sampling of permutations, drawing inspiration from the Steinhaus–Johnson–Trotter algorithm. Our approach takes a comprehensive view of permutation sampling by expressing them as products of adjacent transpositions. Building on this, we develop a quantum analogue of the classical algorithm using a quantum circuit model for random sampling of permutations. As an application, we present a quantum algorithm for the two-sample randomization test to assess the difference of means in classical data. Finally, we propose a nested corona product graph generative model for symmetric groups, which facilitates random sampling of permutations from specific sets of permutations through a quantum circuit model.
Keywords:
Corona product of graphs
coxeter group
quantum circuits
symmetric group
Journal
I
IF:
2.9
Papers:
671
Citations:
9.6K
Organization
Cited Papers
Decomposing a permutation into a conjugated tensor product.png)
Proceedings of the 1997 international symposium on Symbolic and algebraic computation - ISSAC '97
OAAI
Proceedings of the 1997 international symposium on Symbolic and algebraic computation - ISSAC '97IF0
OAAIShareSaveShareSaveShareSaveShareSaveShareSaveShareSave
ShareSave
View more