27 citations · 121 across the 15 of their papers we have counts for
6 papers · 1 filter
Lithography-free in situ photonic inverse design
Yiqi Zhao, Martin M. Stein, Fan O. Wu +6
Inverse design has emerged as a powerful engineering approach in nanophotonics, leading to devices with unintuitive designs that extend beyond human intuition. However, inverse-des…
Programmable nonlinearity within nanophotonic waveguides
Benjamin A. Ash, Ryotatsu Yanagimoto, Mandar M. Sohoni +8
Nonlinear nanophotonics enables the engineering of optical functions using light-matter interactions in nanoscale structures with carefully designed geometries. Phase matching in n…
TRON: Trainable, architecture-reconfigurable random optical neural networks
Ziao Wang, Fei Xia, Logan G. Wright +5
Deep learning has triggered explosive growth in the demand for specialized hardware processors, thus motivating the development of scalable and reconfigurable computing substrates.…
Machine vision with small numbers of detected photons per inference
Shi-Yuan Ma, Jérémie Laydevant, Mandar M. Sohoni +3
Machine vision, including object recognition and image reconstruction, is a central technology in many consumer devices and scientific instruments. The design of machine-vision sys…
Programmable on-chip nonlinear photonics
Ryotatsu Yanagimoto, Benjamin A. Ash, Mandar M. Sohoni +7
Nonlinear photonics uses coherent interactions between optical waves to engineer functionality that is not possible with purely linear optics. Traditionally, the function of a nonl…
Arbitrary control over multimode wave propagation for machine learning
Tatsuhiro Onodera, Martin M. Stein, Benjamin A. Ash +10
Controlled multimode wave propagation can enable more space-efficient photonic processors than architectures based on discrete components connected by single-mode waveguides. Inste…