2021
DOI: 10.48550/arxiv.2105.08303
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Curvature-dimension conditions for symmetric quantum Markov semigroups

Abstract: Following up on the recent work on lower Ricci curvature bounds for quantum systems, we introduce two noncommutative versions of curvature-dimension bounds for symmetric quantum Markov semigroups over matrix algebras. Under suitable such curvature-dimension conditions, we prove a family of dimension-dependent functional inequalities, a version of the Bonnet-Myers theorem and concavity of entropy power in the noncommutative setting. We also provide examples satisfying certain curvature-dimension conditions, inc… Show more

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Cited by 1 publication
(3 citation statements)
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“…We can also discuss the approximate tensorization property of F p,σ similarly to [53,Theorem 5.1] and the stability of the data processing inequality for the divergence F p,σ similarly to [59,Proposition 5.1]. Third, in view of [97], it is straightforward to consider the curvature-dimension conditions for quantum systems and investigate the finite-dimension version of the quantum Beckner's inequality. The details and refinements of these results would be worth being reported elsewhere.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
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“…We can also discuss the approximate tensorization property of F p,σ similarly to [53,Theorem 5.1] and the stability of the data processing inequality for the divergence F p,σ similarly to [59,Proposition 5.1]. Third, in view of [97], it is straightforward to consider the curvature-dimension conditions for quantum systems and investigate the finite-dimension version of the quantum Beckner's inequality. The details and refinements of these results would be worth being reported elsewhere.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…This helps us to obtain concentration inequalities in a similar manner as [60]. We first recall the carré du champ operator (gradient form) associated with P t = e tL [60,97]:…”
Section: Moment Estimates and Concentration Inequalitiesmentioning
confidence: 99%
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