The variance of relative surprisal as single-shot quantifier
Paul Boes, Nelly H. Y. Ng, Henrik Wilming

TL;DR
This paper investigates the variance of relative surprisal as a key single-shot quantifier in quantum information theory, providing new conditions for state transitions, relations to entropies, and applications in thermodynamics and resource theories.
Contribution
It introduces the variance of relative surprisal as a fundamental single-shot quantifier, establishing necessary and sufficient conditions for quantum state transitions without optimization.
Findings
Provides conditions for approximate quantum state transitions.
Clarifies relation between variance of surprisal and smoothed entropies.
Derives bounds on entropy production and resource interconvertibility.
Abstract
The variance of (relative) surprisal, also known as varentropy, so far mostly plays a role in information theory as quantifying the leading order corrections to asymptotic i.i.d.~limits. Here, we comprehensively study the use of it to derive single-shot results in (quantum) information theory. We show that it gives genuine sufficient and necessary conditions for approximate state-transitions between pairs of quantum states in the single-shot setting, without the need for further optimization. We also clarify its relation to smoothed min- and max-entropies, and construct a monotone for resource theories using only the standard (relative) entropy and variance of (relative) surprisal. This immediately gives rise to enhanced lower bounds for entropy production in random processes. We establish certain properties of the variance of relative surprisal which will be useful for further…
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