Machine learner optimization of atom loading in optical nanofiber evanescent dipole traps

Gupta, Ratnesh K.; Everett, Jesse L.; Tranter, Aaron D.; Henke, René; Gokhroo, Vandna; Lam, Ping Koy; Chormaic, Síle Nic

Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Machine learner optimization of atom loading in optical nanofiber evanescent dipole traps

Date

2022

Authors

Publisher

Optica Publishing Group (formerly OSA)

Abstract

We use an online machine learning algorithm to optimize cooling and loading of rubidium-87 atoms into an evanescent dipole trap array along an optical nanofiber, increasing the number of trapped atoms by 50%.

URI

https://dspace-test.anu.edu.au/handle/1885/733761696

Collections

DevOps Integration

Type

Conference paper

Book Title

Quantum 2.0, QUANTUM 2022

Entity type

Publication

Full item page

Cultural advice

Machine learner optimization of atom loading in optical nanofiber evanescent dipole traps

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Access Statement

Research Projects

Organizational Units

Journal Issue

Abstract

Description

Keywords

Citation

URI

Collections

Source

Type

Book Title

Entity type

Access Statement

License Rights

DOI

Restricted until