Information and disturbance in operational probabilistic theories
Giacomo Mauro D'Ariano, Paolo Perinotti, and Alessandro Tosini

TL;DR
This paper explores the fundamental relationship between information extraction and disturbance in general operational probabilistic theories, extending quantum insights to broader theoretical frameworks and characterizing when information can be obtained without disturbance.
Contribution
It introduces a generalized notion of disturbance and no-information tests, proving a structure theorem for probabilistic theories and characterizing classical systems as the only ones allowing disturbance-free information extraction.
Findings
No-information without disturbance implies classicality of the system.
Information retrievable without disturbance corresponds to perfectly discriminable, repeatable tests.
The set of states decomposes into a direct sum of perfectly discriminable subsets.
Abstract
Any measurement is intended to provide information on a system, namely knowledge about its state. However, we learn from quantum theory that it is generally impossible to extract information without disturbing the state of the system or its correlations with other systems. In this paper we address the issue of the interplay between information and disturbance for a general operational probabilistic theory. The traditional notion of disturbance considers the fate of the system state after the measurement. However, the fact that the system state is left untouched ensures that also correlations are preserved only in the presence of local discriminability. Here we provide the definition of disturbance that is appropriate for a general theory. Moreover, since in a theory without causality information can be gathered also on the effect, we generalise the notion of no-information test. We then…
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