Machine learning optimization and characterization of a high-optical depth two-color nanofiber trap
Abstract
Optical nanofibers provide a way of coupling quantum information in cold atoms across large distances; however, this coupling requires atoms to reside close to the nanofiber surface. Atoms can be trapped close to the surface using a two-color dipole trap. Here, we present our experimental realization of a two-color dipole trap. We optimize the number of trapped atoms using a machine learning algorithm and measure the optical density via the transmission. We estimate the number of atoms in the trap to be approximately 1400 and the lifetime of the atoms in the trap to be 28 ms. Machine learning optimization improved the on-resonance optical depth from 0.5 in the initial optimization stage to optical depths exceeding 15.
Fields of Study & Subjects
Cold Atom Physics and Bose-Einstein Condensates
Quantum Information and Cryptography
Quantum chaos and dynamical systems
Publication details
- Journal / source
- AVS Quantum Science
- Publisher
- American Vacuum Society
- Volume
- 8
- Issue
- 2
- Publication date
- 1 June 2026
- Language
- EN