Generalized R\'enyi entropy accumulation theorem and generalized quantum probability estimation
Amir Arqand, Thomas A. Hahn, Ernest Y.-Z. Tan

TL;DR
This paper introduces a new entropy accumulation bound that improves finite-size performance, simplifies computation via convex optimization, and extends applicability to fully-Rényi security proofs in quantum cryptography.
Contribution
It derives a novel entropy accumulation bound that is easier to compute, more optimal, and applicable directly at the Rénnyi entropy level, advancing quantum cryptography security analysis.
Findings
Provides significantly better finite-size bounds.
Enables computation through convex optimization without affine min-tradeoff functions.
Applies directly to prepare-and-measure protocols without additional procedures.
Abstract
The entropy accumulation theorem, and its subsequent generalized version, is a powerful tool in the security analysis of many device-dependent and device-independent cryptography protocols. However, it has the drawback that the finite-size bounds it yields are not necessarily optimal, and furthermore it relies on the construction of an affine min-tradeoff function, which can often be challenging to construct optimally in practice. In this work, we address both of these challenges simultaneously by deriving a new entropy accumulation bound. Our bound yields significantly better finite-size performance, and can be computed as an intuitively interpretable convex optimization, without any specification of affine min-tradeoff functions. Furthermore, it can be applied directly at the level of R\'enyi entropies if desired, yielding fully-R\'enyi security proofs. Our proof techniques are based…
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Taxonomy
TopicsStatistical Mechanics and Entropy
