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 83 tok/s
Gemini 2.5 Pro 34 tok/s Pro
GPT-5 Medium 24 tok/s Pro
GPT-5 High 21 tok/s Pro
GPT-4o 130 tok/s Pro
Kimi K2 207 tok/s Pro
GPT OSS 120B 460 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

A Unified Approach to Quantum Contraction and Correlation Coefficients (2505.15281v1)

Published 21 May 2025 in quant-ph, cs.IT, and math.IT

Abstract: In classical information theory, the maximal correlation coefficient is used to establish strong limits on distributed processing. Through its relation to the $\chi{2}$-contraction coefficient, it also establishes fundamental bounds on sequential processing. Two distinct quantum extensions of the maximal correlation coefficient have been introduced to recover these two scenarios, but they do not recover the entire classical framework. We introduce a family of non-commutative $L{2}(p)$ spaces induced by operator monotone functions from which families of quantum maximal correlation coefficients and the quantum $\chi{2}$-divergences can be identified. Through this framework, we lift the classical results to the quantum setting. For distributed processing, using our quantum maximal correlation coefficients, we establish strong limits on converting quantum states under local operations. For sequential processing, we clarify the relation between the data processing inequality of quantum maximal correlation coefficients, $\chi{2}$-contraction coefficients, and $f$-divergences. Moreover, we establish the quantum maximal correlation coefficients and $\chi{2}$-contraction coefficients are often computable via linear algebraic methods, which in particular implies a method for obtaining rigorous, computable upper bounds for time-homogeneous quantum Markov chains with a unique, full rank fixed point.

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.