Intelligent Infrared Sensing Enabled by Moiré Quantum Geometry: Experiment and Theory

ORAL · Invited

Abstract

Optical sensors measure the information of light, such as intensity, polarization state, wavelength or spectrum. They are traditionally mono-functional, bulky, and inefficient. By integrating advances in moiré quantum materials and deep learning, we demonstrate an all-in-one intelligent sensing scheme for light in mid-infrared regime at 79 K [1]. We show that moiré quantum materials exhibit extraordinarily large nonlinear bulk photovoltaic effect because their structure-level symmetry breaking promotes substantial quantum geometric properties. By leveraging the top-gate and bottom-gate tunability of two-dimensional materials, each incoming light produces a unique nonlinear response map, which encodes all the light information. A trained convolutional neural network is shown to be able to decode the power, wavelength, and polarization state of the light simultaneously and instantaneously with a high precision level. This new scheme not only identifies a pathway for future intelligent sensing technologies in an extremely compact, on-chip manner but also opens a new horizon for deep quantum sensing schemes [2] that can be generalized to include other frequency regimes [3].

* This work was supported by the NSF under grant numbers DMR-1945351 through the CAREER program, DMR-2324033 through the DMREF program, and DMR-2105139 through the CMP program.

Publication: [1] Ma et al., Intelligent infrared sensing enabled by tunable moiré quantum geometry. Nature 604, 266–272 (2022).
[2] Yuan et al., Geometric deep optical sensing. Science 379, eade1220 (2023).
[3] Cheung et al., Nonlinear light-matter interactions and convolutional neural networks for intelligent quantum sensing, in preparation.

Presenters

  • Patrick Cheung

    University of Texas at Dallas

Authors

  • Patrick Cheung

    University of Texas at Dallas