Nash equilibrium quantum states and optimal quantum data classification

TL;DR

This paper introduces a game-theoretic approach using Nash equilibrium to classify quantum data optimally, focusing on distinguishing pure quantum states from their observable components under orthogonality constraints.

Contribution

It presents a novel application of game theory to quantum information, defining Nash equilibrium quantum states for optimal data classification.

Findings

Nash equilibrium quantum states enable optimal data classification.

The approach effectively distinguishes pure states from observable states.

Game theory provides a new framework for quantum data analysis.

Abstract

This letter reports a novel application of game theory to quantum informational processes which can be used to optimally classify data generated by these processes. To this end, the notion of simultaneously distinguishing a pure quantum state, generated by a quantum informational process, from its constituent observable states optimally - given the constraint of these observables being orthogonal to each other, is first introduced. This problem is solved via a non-cooperative game model and the affiliated solution concept of Nash equilibrium. The notion of Nash equilibrium quantum states is introduced and used to classify quantum data optimally.