Training quantum measurement devices to discriminate unknown non-orthogonal quantum states
D. Concha, L. Pereira, L. Zambrano, A. Delgado

TL;DR
This paper presents a method to train quantum measurement devices to discriminate unknown non-orthogonal quantum states with minimal error, approaching theoretical limits even without a precise channel model.
Contribution
It introduces a training approach for quantum measurements that works without detailed channel knowledge, utilizing classical communication and noise-tolerant optimization.
Findings
Achieves error probabilities close to the Helstrom bound for two unknown pure states.
Effectively extends to higher dimensions and larger state sets.
Reduces resource requirements through search space reduction.
Abstract
Here, we study the problem of decoding information transmitted through unknown quantum states. We assume that Alice encodes an alphabet into a set of orthogonal quantum states, which are then transmitted to Bob. However, the quantum channel that mediates the transmission maps the orthogonal states into non-orthogonal states, possibly mixed. If an accurate model of the channel is unavailable, then the states received by Bob are unknown. In order to decode the transmitted information we propose to train a measurement device to achieve the smallest possible error in the discrimination process. This is achieved by supplementing the quantum channel with a classical one, which allows the transmission of information required for the training, and resorting to a noise-tolerant optimization algorithm. We demonstrate the training method in the case of minimum-error discrimination and show that it…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum Mechanics and Applications
