Quantum Logic Spectroscopy of Polyatomic Molecules for Fundamental Physics Searches
ORAL
Abstract
Over the last decade, the quantum-logic spectroscopy (QLS) community has expanded from atomic species to diatomic molecules in ion traps. The ability to perform precision measurements with polyatomic molecules would introduce new experimental opportunities, as these molecules serve as sensitive sensors for fundamental physics. For instance, the inversion frequencies of H3O+ probe local position invariance; the energy differences between the left- and right-handed enantiomers of CHDBrI+ probe fundamental symmetry violation. In this work, we present collective theoretical efforts, bridging across first-principles predictions and AI-enabled quantum control schemes, to address the challenge posed by the densely populated ro-vibrational levels in polyatomic molecules. Specifically, we will discuss the design of a single state preparation scheme robust to environmental uncertainties and the resolution of hyperfine structure, employing interdisciplinary approaches that integrate artificial intelligence, AMO physics, and quantum chemistry.
*This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work was supported by NSF CAREER Award under grant number ECCS 2246394, NSF QuSeC-TAQS 2326840, NSF ExpandQISE 2231387, NSF PHY 2309315, and Moore Foundation EPI 12252.
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Publication: A. Pipi, X. Tao, P. Narang, and D.R. Leibrandt (2024). Molecular Quantum Control Algorithm Design by Reinforcement Learning. arXiv preprint arXiv:2410.11839.
Presenters
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Xuecheng Tao
- University of California, Los Angeles