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arxiv: 1805.11652 · v2 · pith:67KQCJKInew · submitted 2018-05-29 · 🪐 quant-ph

Entropy accumulation with improved second-order term

classification 🪐 quant-ph
keywords protocolstheoremboundssecond-ordertermaccumulationdoneentropy
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The entropy accumulation theorem states that the smooth min-entropy of an $n$-partite system $A = (A_1, \ldots, A_n)$ is lower-bounded by the sum of the von Neumann entropies of suitably chosen conditional states up to corrections that are sublinear in $n$. This theorem is particularly suited to proving the security of quantum cryptographic protocols, and in particular so-called device-independent protocols for randomness expansion and key distribution, where the devices can be built and preprogrammed by a malicious supplier. However, while the bounds provided by this theorem are optimal in the first order, the second-order term is bounded more crudely, in such a way that the bounds deteriorate significantly when the theorem is applied directly to protocols where parameter estimation is done by sampling a small fraction of the positions, as is done in most QKD protocols. The objective of this paper is to improve this second-order sublinear term and remedy this problem. On the way, we prove various bounds on the divergence variance, which might be of independent interest.

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  1. Finite-size quantum key distribution rates from R\'enyi entropies using conic optimization

    quant-ph 2025-11 unverdicted novelty 7.0

    A general conic optimization solver computes finite-size QKD rates from Rényi entropies more reliably than prior Frank-Wolfe methods.