Quick Navigation
Topics
Trapped Ion Quantum Computing
Quantum Simulation
Quantum walk mixing is faster than classical on periodic lattices
arXiv
Authors: Shyam Dhamapurkar, Xiu-Hao Deng
Year
2023
Paper ID
54346
Status
Preprint
Abstract Read
~2 min
Abstract Words
168
Citations
N/A
Abstract
This work focuses on the quantum mixing time, which is crucial for efficient quantum sampling and algorithm performance. We extend Richter's previous analysis of continuous time quantum walks on the periodic lattice mathbb{Z}n1times mathbb{Z}n2times dots times mathbb{Z}nd, allowing for non-identical dimensions ni. We present two quantum walks that achieve faster mixing compared to classical random walks. The first is a coordinate-wise quantum walk with a mixing time of Oleft\(left(sum{i=1}d ni right\) log{(d/ε)}right) and O\(d log(d/ε\)) measurements. The second is a continuous-time quantum walk with O\(log(1/ε\)) measurements, conjectured to have a mixing time of Oleft\(sumi=1d ni(log(n1\))2 log(1/ε)right). Our results demonstrate a quadratic speedup over classical mixing times on the generalized periodic lattice. We provide analytical evidence and numerical simulations supporting the conjectured faster mixing time. The ultimate goal is to prove the general conjecture for quantum walks on regular graphs.
Why This Paper Matters
- This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
- It adds a 2023 reference point for readers tracking recent quantum research.
- This work focuses on the quantum mixing time, which is crucial for efficient quantum sampling and algorithm performance.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.