Reinforcement-learning-based matter-wave interferometer in a shaken optical lattice
We demonstrate the design of a matter-wave 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 mac...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2021-09-01
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| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/PhysRevResearch.3.033279 |
| _version_ | 1797210922091020288 |
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| author | Liang-Ying Chih Murray Holland |
| author_facet | Liang-Ying Chih Murray Holland |
| author_sort | Liang-Ying Chih |
| collection | DOAJ |
| description | We demonstrate the design of a matter-wave 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. |
| first_indexed | 2024-04-24T10:18:17Z |
| format | Article |
| id | doaj.art-49dfc9439c164040b75486b0ef9feef0 |
| institution | Directory Open Access Journal |
| issn | 2643-1564 |
| language | English |
| last_indexed | 2024-04-24T10:18:17Z |
| publishDate | 2021-09-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review Research |
| spelling | doaj.art-49dfc9439c164040b75486b0ef9feef02024-04-12T17:14:23ZengAmerican Physical SocietyPhysical Review Research2643-15642021-09-013303327910.1103/PhysRevResearch.3.033279Reinforcement-learning-based matter-wave interferometer in a shaken optical latticeLiang-Ying ChihMurray HollandWe demonstrate the design of a matter-wave 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.http://doi.org/10.1103/PhysRevResearch.3.033279 |
| spellingShingle | Liang-Ying Chih Murray Holland Reinforcement-learning-based matter-wave interferometer in a shaken optical lattice Physical Review Research |
| title | Reinforcement-learning-based matter-wave interferometer in a shaken optical lattice |
| title_full | Reinforcement-learning-based matter-wave interferometer in a shaken optical lattice |
| title_fullStr | Reinforcement-learning-based matter-wave interferometer in a shaken optical lattice |
| title_full_unstemmed | Reinforcement-learning-based matter-wave interferometer in a shaken optical lattice |
| title_short | Reinforcement-learning-based matter-wave interferometer in a shaken optical lattice |
| title_sort | reinforcement learning based matter wave interferometer in a shaken optical lattice |
| url | http://doi.org/10.1103/PhysRevResearch.3.033279 |
| work_keys_str_mv | AT liangyingchih reinforcementlearningbasedmatterwaveinterferometerinashakenopticallattice AT murrayholland reinforcementlearningbasedmatterwaveinterferometerinashakenopticallattice |