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Fundamental connections between utility theories of wealth and information theory

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arxiv 2306.07975 v1 pith:CIWNHXVH submitted 2023-05-22 cs.IT math.ITquant-ph

classification cs.ITmath.ITquant-ph
keywords informationutilitytaskstheoriestheorywealthbettingintroduce
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abstract

We establish fundamental connections between utility theories of wealth from the economic sciences and information-theoretic quantities. In particular, we introduce operational tasks based on betting where both gambler and bookmaker have access to side information, or betting tasks with double side information for short. In order to characterise these operational tasks we introduce new conditional R\'enyi divergences, and explore some of their properties. Furthermore, we introduce an utility theory of wealth ratios, and operationally interpret there the two-parameter $(q,r)$ generalised mutual information measure recently introduced by V. M. Ili\'c and I. V. Djordjevi\'c; it quantifies the advantage provided by side information in betting tasks for utility theories of wealth ratios. Moreover, we show that the Ili\'c-Djordjevi\'c conditional entropy satisfies a type of generalised chain rule, which generalises that of Arimoto-R\'enyi. Finally, we address the implications of these results on the quantum resource theories of informative measurements and non-constant channels. Altogether, these results further help strengthening the bridge between the theory of expected utility from the economic sciences and Shannon's theory of information.

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Cited by 2 Pith papers

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  1. Dynamical Landauer principle: Thermodynamic criteria of transmitting classical information

    quant-ph 2025-02 conditional novelty 6.0 of 10

    One-shot classical capacities equal, up to error terms, the extractable work from correlations after transmission, yielding the equivalence n bits = n times kBT ln2 of transmitted energy.

  2. Multi-object operational tasks for measurement incompatibility

    quant-ph 2024-12 accept novelty 6.0 of 10

    The advantage of a state and an incompatible measurement set in subchannel discrimination games equals (1 + robustness of state)(1 + robustness of measurement set), and similarly for weight in exclusion games.

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