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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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