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 150 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 33 tok/s Pro
GPT-5 High 34 tok/s Pro
GPT-4o 113 tok/s Pro
Kimi K2 211 tok/s Pro
GPT OSS 120B 444 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Multiobjective Optimization for Robust Holonomic Quantum Gates (2504.17259v1)

Published 24 Apr 2025 in quant-ph

Abstract: Robust pulses have been widely used to reduce the sensitivity of quantum gate operations against various systematic errors due to the imperfections in practical quantum control. Yet, the typical optimization focuses on minimizing one type of errors serving as the one-objective algorithm, which arises a more susceptible sensitivity to other error sources. Optimizing multiple conflicting objectives of errors simultaneously remains a big challenge in quantum computing. Here, we propose a multiobjective optimization algorithm to achieve nonadiabatic holonomic quantum gates with enhanced robustness. We show that by considering the amplitude error, the detuning error and the decoherence of the Rydberg state as three individual objectives to be minimized, this algorithm can effectively balance multiple competing objectives, giving rise to a set of Pareto optimal solutions. We apply the Entropy Weight method to select the best solution that implements the robust holonomic gates, outperforming existing optimal gates with one-objective by having both higher gate fidelity and stronger robustness. This numerical approach of optimizing gates with multiple objectives can be readily applied to other gate protocols featuring a promising advance in fault-tolerant quantum computing with Rydberg atoms.

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.

Authors (2)

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 1 tweet and received 3 likes.

Upgrade to Pro to view all of the tweets about this paper: