Research

Compact, lightweight, and energy-efficient cold atom systems are crucial for advancing quantum technologies, yet their realization remains constrained by the bulky optical and magnetic components required in current atom trapping architectures. Here, we demonstrate a low-SWaP magneto-optical trap that seamlessly integrates planar optical and magnetic components into a unified platform. A monolithic dual-functional metasurface simultaneously polarized and shapes the cooling beam, replacing traditional lens-waveplate assemblies and converting a linearly polarized Gaussian beam into a circularly polarized flat-top beam. In parallel, a planar coil chip substitutes bulky anti-Helmholtz cols and generated the required quadrupole magnetic field with drastically reduced power consumption. Under D2 line cooling of 87Rb atoms, the fully planar system delivers nearly an order-of-magnitude improvement in trapping performance while operating at a fraction of the size, weight, and power of traditional systems. This compact, bulky-component-free approach offers a scalable, energy-efficient pathway toward chip-scale cold atom platforms.

Controlling multiple degrees of freedom of light in a small-footprint with
high-efficiency in a foundry-manufacturable platform is foundational for a
range of classical and quantum technologies. Achieving this requires photonic
design strategies that go beyond traditional physical intuition-based methods.
Reinforcement learning (RL), a subset of machine learning, is successful in
achieving optimum outcomes in dynamically evolving environments, e.g., in
strategy games or self-driving cars. Here, a novel paradigm based on
reinforcement learning is presented for photonic device design, and
multifunctional metasurface optics and integrated photonic devices operating
in the visible are realized. RL-based metasurface optics operating at free-space
wavelengths of 461 and 689 nm designed are fabricated and experimentally
characterized to simultaneously deflect input light at large deflection angles
and maintain or change its polarization. Further, the RL approach is used to
design in-plane integrated photonic devices such as bends, mode-converters,
wavelength demultiplexers, and beamsplitters, as well as waveguide-coupled
grating out-couplers to both control the angle of the out-of-plane beam
emission and polarization at visible wavelengths on a silicon nitride platform.
The results, targeting a two-color strontium magneto-optical trap for the
realization of a portable, alignment-free optical lattice clock, elucidate the
potential of reinforcement learning for the design of high-performance optics.

Optical metasurfaces of subwavelength pillars have provided new capabilities for the versatile definition of the amplitude, phase, and polarization of light. In this work, we demonstrate that an efficient dielectric metasurface lens can be used to trap and image single neutral atoms with a long working distance from the lens of 3 mm. We characterize the high-numerical-aperture optical tweezers using the trapped atoms and compare with numerical computations of the metasurface-lens performance. We predict that future metasurfaces for atom trapping will be able to leverage multiple ongoing developments in metasurface design and enable multifunctional control in complex quantum information experiments with neutral-atom arrays.