Machine-learning enhanced dark soliton detection in Bose–Einstein condensates

Author:

Guo Shangjie,Fritsch Amilson R,Greenberg Craig,Spielman I BORCID,Zwolak Justyna PORCID

Abstract

Abstract Most data in cold-atom experiments comes from images, the analysis of which is limited by our preconceptions of the patterns that could be present in the data. We focus on the well-defined case of detecting dark solitons—appearing as local density depletions in a Bose–Einstein condensate (BEC)—using a methodology that is extensible to the general task of pattern recognition in images of cold atoms. Studying soliton dynamics over a wide range of parameters requires the analysis of large datasets, making the existing human-inspection-based methodology a significant bottleneck. Here we describe an automated classification and positioning system for identifying localized excitations in atomic BECs utilizing deep convolutional neural networks to eliminate the need for human image examination. Furthermore, we openly publish our labeled dataset of dark solitons, the first of its kind, for further machine learning research.

Publisher

IOP Publishing

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Reference47 articles.

1. A convolutional neural network neutrino event classifier;Aurisano;J. Instrum.,2016

2. Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber;Acciarri;J. Instrum.,2017

3. Image-based jet analysis;Kagan,2020

4. Deep learning for directional dark matter search;Golovatiuk;J. Phys.: Conf. Series,2020

5. Convolutional neural networks for direct detection of dark matter;Khosa;J. Phys. G: Nucl. Part. Phys.,2020

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3