Arrays of dark and bright traps for neutral atoms generated by silicon-on-sapphire metasurfaces

Oral

Abstract

Arrays of neutral atoms are a promising platform for quantum technologies, including computing and sensing. However, scaling up the size of the arrays remains a big challenge, in significant part due to limits in pixel counts in active optical elements used to form arrays of optical tweezers, e.g., spatial light modulators (SLMs). In this work, we experimentally demonstrate crystalline silicon-on-sapphire (c-SOS) metasurfaces that are readily scalable to generate larger and more complex arrays, including arrays of optical bottle beams that trap atoms in dark regions interleaved with bright tweezer arrays. The high refractive index and indirect band gap of crystalline silicon makes it possible to design high-resolution near-infrared metasurfaces that can be manufactured at scale using CMOS-compatible processes. Compared with the active optical components that have become widely used, metasurfaces provide a nearly indefinitely scalable number of pixels, enabling large arrays of complex traps in a very small form factor, as well as reduced dynamic noise. To design metasurfaces that can generate three-dimensional complex bottle beams to serve as dark traps, we modified the Gerchberg-Saxton algorithm to enforce complex-amplitude profiles at the focal plane of the metasurface and to optimize the uniformity of the traps across the array. We fabricated and measured c-SOS metasurfaces that convert a Gaussian laser beam into three trap-array configurations: a 21-by-21 array of bright traps, a 7-by-7 array of dark bottle-beams, and a dual-species geometry consisting of interleaved bright and dark traps.

Publication: arXiv preprint arXiv:2601.01038

Presenters

  • Chengyu Fang

    • University of Wisconsin - Madison

Authors

  • Chengyu Fang

    • University of Wisconsin - Madison
  • Minjeong Kim

    • University of Wisconsin - Madison
  • Hongyan Mei

    • University of Wisconsin - Madison
  • Xuting Yang

    • University of Wisconsin - Madison
  • Zhaoning Yu

  • Yuzhe Xiao

  • Sanket Deshpande

    • University of Wisconsin - Madison
  • Preston Huft

  • Alan Dibos

    • Argonne National Laboratory
  • David Czaplewski

  • Mark Saffman

    • University of Wisconsin - Madison
  • Jennifer Choy

    • University of Wisconsin - Madison
  • Mikhail Kats