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Sampling of min-entropy relative to quantum knowledge

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abstract

Let X_1, ..., X_n be a sequence of n classical random variables and consider a sample of r positions selected at random. Then, except with (exponentially in r) small probability, the min-entropy of the sample is not smaller than, roughly, a fraction r/n of the total min-entropy of all positions X_1, ..., X_n, which is optimal. Here, we show that this statement, originally proven by Vadhan [LNCS, vol. 2729, Springer, 2003] for the purely classical case, is still true if the min-entropy is measured relative to a quantum system. Because min-entropy quantifies the amount of randomness that can be extracted from a given random variable, our result can be used to prove the soundness of locally computable extractors in a context where side information might be quantum-mechanical. In particular, it implies that key agreement in the bounded-storage model (using a standard sample-and-hash protocol) is fully secure against quantum adversaries, thus solving a long-standing open problem.

fields

quant-ph 1

years

2026 1

verdicts

UNVERDICTED 1

representative citing papers

Quantum randomness beyond projective measurements

quant-ph · 2026-05-18 · unverdicted · novelty 7.0

Unbiased extremal rank-one measurements generate characterized randomness in dimension 2, with tetrahedral SIC having the least, and SICs achieve maximal 2 log d randomness device-dependently in dimensions where they exist.

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  • Quantum randomness beyond projective measurements quant-ph · 2026-05-18 · unverdicted · none · ref 10 · internal anchor

    Unbiased extremal rank-one measurements generate characterized randomness in dimension 2, with tetrahedral SIC having the least, and SICs achieve maximal 2 log d randomness device-dependently in dimensions where they exist.