Bayesian Searches and Quantum Oscillators

2018/12/19 by G. Chapline, Chapline, G., M. Otten +1
Computer Science · #Distributed Sensor Networks and Detection Algorithms #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #Quantum Physics (quant-ph)

paper · pdf · doi:10.48550/arxiv.1812.08272

openalex publication_date 2018/12/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A new LLNL Strategic Initiative is focused on developing improved methods for Bayesian inference when the input data depends on hidden parameters. Part of this effort involves investigating the idea of using an array of quantum oscillators (viz microwave cavities) as an analog computer for implementing Bayesian model selection. The practical motivations are twofold: 1) Bayesian model selection problems are often intractable using conventional digital computers, and 2) quantum information processing may allow detection of weak analog signals below the usual quantum noise threshold.

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