Controlled transport in chiral quantum walks on graphs
Yi-Cong Yu, Xiaoming Cai

TL;DR
This paper explores how chiral quantum walks on graphs exhibit controllable asymmetric and complete transport properties, with a focus on Y-junction graphs, using gauge transformations and phase analysis to understand and optimize quantum transport.
Contribution
It introduces a gauge transformation approach to analyze chiral CTQWs, and develops a phase-based control method for asymmetric and complete transport on Y-junction graphs.
Findings
Chiral CTQWs are equivalent to non-chiral ones with initial momentum shifts.
Phases control asymmetric and complete transport in Y-junction graphs.
Explicit conditions for 100% quantum transport efficiency are derived.
Abstract
We investigate novel transport properties of chiral continuous-time quantum walks (CTQWs) on graphs. By employing a gauge transformation, we demonstrate that CTQWs on chiral chains are equivalent to those on non-chiral chains, but with additional momenta from initial wave packets. This explains the novel transport phenomenon numerically studied in [New J. Phys. 23, 083005(2021)]. Building on this, we delve deeper into the analysis of chiral CTQWs on the Y-junction graph, introducing phases to account for the chirality. The phase plays a key role in controlling both asymmetric transport and directed complete transport among the chains in the Y-junction graph. We systematically analyze these features through a comprehensive examination of the chiral continuous-time quantum walk (CTQW) on a Y-junction graph. Our analysis shows that the CTQW on Y-junction graph can be modeled as a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum and electron transport phenomena · Quantum Computing Algorithms and Architecture · Computational Physics and Python Applications
