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Photonic integrated beam delivery for a rubidium 3D magneto-optical trap

Author

Listed:
  • Andrei Isichenko

    (University of California Santa Barbara)

  • Nitesh Chauhan

    (University of California Santa Barbara)

  • Debapam Bose

    (University of California Santa Barbara)

  • Jiawei Wang

    (University of California Santa Barbara)

  • Paul D. Kunz

    (DEVCOM U.S. Army Research Laboratory)

  • Daniel J. Blumenthal

    (University of California Santa Barbara)

Abstract

Cold atoms are important for precision atomic applications including timekeeping and sensing. The 3D magneto-optical trap (3D-MOT), used to produce cold atoms, will benefit from photonic integration to improve reliability and reduce size, weight, and cost. These traps require the delivery of multiple, large area, collimated laser beams to an atomic vacuum cell. Yet, to date, beam delivery using an integrated waveguide approach has remained elusive. Here we report the demonstration of a 87Rb 3D-MOT using a fiber-coupled photonic integrated circuit to deliver all beams to cool and trap > 1 ×106 atoms to near 200 μK. The silicon nitride photonic circuit transforms fiber-coupled 780 nm cooling and repump light via waveguides to three mm-width non-diverging free-space cooling and repump beams directly to the rubidium cell. This planar, CMOS foundry-compatible integrated beam delivery is compatible with other components, such as lasers and modulators, promising system-on-chip solutions for cold atom applications.

Suggested Citation

  • Andrei Isichenko & Nitesh Chauhan & Debapam Bose & Jiawei Wang & Paul D. Kunz & Daniel J. Blumenthal, 2023. "Photonic integrated beam delivery for a rubidium 3D magneto-optical trap," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-38818-6
    DOI: 10.1038/s41467-023-38818-6
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    References listed on IDEAS

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    1. A. D. Tranter & H. J. Slatyer & M. R. Hush & A. C. Leung & J. L. Everett & K. V. Paul & P. Vernaz-Gris & P. K. Lam & B. C. Buchler & G. T. Campbell, 2018. "Multiparameter optimisation of a magneto-optical trap using deep learning," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    2. Nitesh Chauhan & Andrei Isichenko & Kaikai Liu & Jiawei Wang & Qiancheng Zhao & Ryan O. Behunin & Peter T. Rakich & Andrew M. Jayich & C. Fertig & C. W. Hoyt & Daniel J. Blumenthal, 2021. "Visible light photonic integrated Brillouin laser," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
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