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 81 tok/s
Gemini 2.5 Pro 44 tok/s Pro
GPT-5 Medium 22 tok/s Pro
GPT-5 High 25 tok/s Pro
GPT-4o 81 tok/s Pro
Kimi K2 172 tok/s Pro
GPT OSS 120B 434 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Critical Scaling of the Quantum Wasserstein Distance (2504.02709v1)

Published 3 Apr 2025 in quant-ph

Abstract: Distinguishing quantum states with minimal sampling overhead is of fundamental importance to teach quantum data to an algorithm. Recently, the quantum Wasserstein distance emerged from the theory of quantum optimal transport as a promising tool in this context. Here we show on general grounds that the quantum Wasserstein distance between two ground states of a quantum critical system exhibits critical scaling. We demonstrate this explicitly using known closed analytical expressions for the magnetic correlations in the transverse field Ising model, to numerically extract the critical exponents for the distance close to the quantum critical point, confirming our analytical derivation. Our results have implications for learning of ground states of quantum critical phases of matter.

Summary

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

Lightbulb On 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.