Quantum Entropy and Central Limit Theorem

TL;DR

This paper develops a framework for discrete-variable quantum systems using convolution, establishing entropy inequalities, a quantum central limit theorem, and analyzing the convergence to a mean state with implications for quantum thermodynamics.

Contribution

It introduces a novel convolution-based framework for DV quantum systems, including a quantum CLT and entropy principles, advancing understanding of quantum state behavior.

Findings

The mean state minimizes relative entropy to a given state.

Convolution of stabilizer states yields a stabilizer state.

Quantum central limit theorem shows convergence to the mean state.

Abstract

We introduce a framework to study discrete-variable (DV) quantum systems based on qudits. It relies on notions of a mean state (MS), a minimal stabilizer-projection state (MSPS), and a new convolution. Some interesting consequences are: The MS is the closest MSPS to a given state with respect to the relative entropy; the MS is extremal with respect to the von Neumann entropy, demonstrating a ''maximal entropy principle in DV systems.'' We obtain a series of inequalities for quantum entropies and for Fisher information based on convolution, giving a ''second law of thermodynamics for quantum convolutions.'' We show that the convolution of two stabilizer states is a stabilizer state. We establish a central limit theorem, based on iterating the convolution of a zero-mean quantum state, and show this converges to its MS. The rate of convergence is characterized by the ''magic gap,'' which we define in terms of the support of the characteristic function of the state. We elaborate on two examples: the DV beam splitter and the DV amplifier.