Principle of Information Increase: An Operational Perspective of Information Gain in the Foundations of Quantum Theory

Abstract

A measurement performed on a quantum system is an act of gaining information about its state, a view that is widespread in practical and foundational work in quantum theory. However, the concept of information in quantum theory reconstructions is multiply-defined, and its conceptual foundations remain surprisingly under-explored. In this paper, we investigate the gain of information in quantum measurements from an operational viewpoint. We show that the continuous extension of the Shannon entropy naturally admits two distinct measures of information gain, differential information gain and relative information gain, and that these have radically different characteristics. In particular, while differential information gain can increase or decrease as additional data is acquired, relative information gain consistently grows, and moreover exhibits asymptotic indifference to the data or choice of Bayesian prior. In order to make a principled choice between these measures, we articulate a Principle of Information Increase, which incorporates Summhammer's proposal that more data from measurements leads to more knowledge about the system, and also takes into consideration black swan events. This principle favors differential information gain as the more relevant metric in two-outcome quantum systems, and guides the selection of priors for these information measures. Finally, we show that, of the beta distribution priors, the Jeffreys' binomial prior is the prior ensures maximal robustness of information gain to the particular data sequence obtained in a run of experiments.