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Main Authors: Chih, Liang-Ying, Holland, Murray
Format: Preprint
Published: 2021
Subjects:
Online Access:https://arxiv.org/abs/2106.11434
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author Chih, Liang-Ying
Holland, Murray
author_facet Chih, Liang-Ying
Holland, Murray
contents We demonstrate the design of a matterwave interferometer to measure acceleration in one dimension with high precision. The system we base this on consists of ultracold atoms in an optical lattice potential created by interfering laser beams. Our approach uses reinforcement learning, a branch of machine learning, that generates the protocols needed to realize lattice-based analogs of optical components including a beam splitter, a mirror, and a recombiner. The performance of these components is evaluated by comparison with their optical analogs. The interferometer's sensitivity to acceleration is quantitatively evaluated using a Bayesian statistical approach. We find the sensitivity to surpass that of standard Bragg interferometry, demonstrating the future potential for this design methodology.
format Preprint
id arxiv_https___arxiv_org_abs_2106_11434
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Reinforcement-learning based matterwave interferometer in a shaken optical lattice
Chih, Liang-Ying
Holland, Murray
Quantum Physics
We demonstrate the design of a matterwave interferometer to measure acceleration in one dimension with high precision. The system we base this on consists of ultracold atoms in an optical lattice potential created by interfering laser beams. Our approach uses reinforcement learning, a branch of machine learning, that generates the protocols needed to realize lattice-based analogs of optical components including a beam splitter, a mirror, and a recombiner. The performance of these components is evaluated by comparison with their optical analogs. The interferometer's sensitivity to acceleration is quantitatively evaluated using a Bayesian statistical approach. We find the sensitivity to surpass that of standard Bragg interferometry, demonstrating the future potential for this design methodology.
title Reinforcement-learning based matterwave interferometer in a shaken optical lattice
topic Quantum Physics
url https://arxiv.org/abs/2106.11434