Quantum State Discrimination Using the Minimum Average Number of Copies

TL;DR

This paper introduces a novel quantum state discrimination task focused on minimizing resources for a fixed error rate, demonstrating that new strategies outperform previous methods through theoretical derivation and experimental validation.

Contribution

The paper presents a new resource-efficient quantum state discrimination approach and experimentally verifies its superiority over existing strategies.

Findings

New discrimination task reduces resource usage for fixed error rates.

Proposed detection scheme outperforms previous strategies.

Experimental results confirm theoretical predictions.

Abstract

In the task of discriminating between nonorthogonal quantum states from multiple copies, the key parameters are the error probability and the resources (number of copies) used. Previous studies have considered the task of minimizing the average error probability for fixed resources. Here we introduce a new state discrimination task: minimizing the average resources for a fixed admissible error probability. We show that this new task is not performed optimally by previously known strategies, and derive and experimentally test a detection scheme that performs better.