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Quantum Machine Learning Entanglement Theory Quantum Correlations

Quantum conditional entropies from convex trace functionals

arXiv
Authors: Roberto Rubboli, Milad M. Goodarzi, Marco Tomamichel

Year

2024

Paper ID

37526

Status

Preprint

Abstract Read

~2 min

Abstract Words

87

Citations

N/A

Abstract

We study geometric properties of trace functionals that generalize those in [Zhang, Adv. Math. 365:107053 (2020)], arising from a novel family of conditional entropies with applications in quantum information. Building on new convexity results for these functionals, we establish data-processing inequalities and additivity properties for our entropies, demonstrating their operational significance. We further prove completeness under duality, chain rules, and various monotonicity properties for this family. Our proofs draw on tools from complex interpolation theory, multivariate Araki--Lieb and Lieb--Thirring inequalities, variational characterizations of trace functionals, and spectral pinching techniques.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2024 reference point for readers tracking recent quantum research.
  • We study geometric properties of trace functionals that generalize those in [Zhang, Adv.

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