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Trapped Ion Quantum Computing

Quantum walks advantage on the dihedral group for uniform sampling problem

arXiv
Authors: Shyam Dhamapurkar, Yuhang Dang, Saniya Wagh, Xiu-Hao Deng

Year

2023

Paper ID

53081

Status

Preprint

Abstract Read

~2 min

Abstract Words

174

Citations

N/A

Abstract

Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science. The mixing property is necessary for Markov chains to approach stationary distributions and is facilitated by walks. Quantum walks show promise for faster mixing times than classical methods but lack universal proof, especially in finite group settings. Here, we investigate the continuous-time quantum walks on Cayley graphs of the dihedral group D2n for odd n, generated by the smallest inverse closed symmetric subset. We present a significant finding that, in contrast to the classical mixing time on these Cayley graphs, which typically takes at least order Ω\(n2 log(1/2ε\)), the continuous-time quantum walk mixing time on D2n is of order O\(n (log n\)5 log(1/ε)), achieving a quadratic improvement over the classical case. Our paper advances the general understanding of quantum walk mixing on Cayley graphs, highlighting the improved mixing time achieved by continuous-time quantum walks on D2n. This work has potential applications in algorithms for a class of sampling problems based on non-abelian groups.

Why This Paper Matters

  • This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
  • It adds a 2023 reference point for readers tracking recent quantum research.
  • Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer science.

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