Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 67 tok/s
Gemini 2.5 Pro 62 tok/s Pro
GPT-5 Medium 41 tok/s Pro
GPT-5 High 37 tok/s Pro
GPT-4o 137 tok/s Pro
Kimi K2 190 tok/s Pro
GPT OSS 120B 457 tok/s Pro
Claude Sonnet 4.5 34 tok/s Pro
2000 character limit reached

Quasi-Perfect State Transfer in Spin Chains via Parametrization of On-Site Energies (2410.14053v2)

Published 17 Oct 2024 in quant-ph, cond-mat.other, physics.app-ph, and physics.comp-ph

Abstract: In recent years, significant progress has been made in the field of state transfer in spin chains, with the aim of achieving perfect state transfer for quantum information processing applications. Previous research has mainly focused on manipulating inter-site couplings within spin chains; here, we investigate in detail the potential of modifying on-site energies to facilitate precise quantum information transfer. Our findings demonstrate that through targeted adjustments to the diagonal elements of the XY Hamiltonian and leveraging a genetic algorithm, quasi-perfect state transfer can be achieved with careful consideration of the system's spectral characteristics. This investigation into on-site energies offers an alternative approach for achieving high-fidelity state transfer, especially in cases where manipulation of inter-site couplings may be impractical. This study thus represents a significant advancement towards unlocking the diverse applications of spin chains within practical quantum information systems.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

This paper has been mentioned in 4 posts and received 0 likes.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube