Efficient data processing and quantum phenomena: Single-particle systems

We study the relation between the acquisition and analysis of data and quantum theory using a probabilistic and deterministic model for photon polarizers. We introduce criteria for efficient processing of data and then use these criteria to demonstrate that efficient processing of the data contained in single events is equivalent to the observation that Malus' law holds. A strictly deterministic process that also yields Malus' law is analyzed in detail. We present a performance analysis of the probabilistic and deterministic model of the photon polarizer. The latter is an adaptive dynamical system that has primitive learning capabilities. This additional feature has recently been shown to be sufficient to perform event-by-event simulations of interference phenomena, without using concepts of wave mechanics. We illustrate this by presenting results for a system of two chained Mach–Zehnder interferometers, suggesting that systems that perform efficient data processing and have learning capability are able to exhibit behavior that is usually attributed to quantum systems only.