Existing photonic matrix processers are too small to tackle relevant problems. Here, I review our group’s recent work on scaling up analog photonic platforms. This work includes iterative advances to old approaches (accurate methods to calibrate MZI meshes), experimental demonstrations of recent proposals (a VCSEL array-based coherent detection ONN and a single-shot ONN based on reconfigurable free-space optical fan-out and weighting), and entirely new architectures (WDM-powered and RF-photonic fiber circuits for edge computing). The lessons learned from studying this diverse array of approaches helps inform the future development of photonic hardware for computation.
Subwavelength grating (SWG) metamaterial structures are excellent platforms for guided-wave nonlinear optics, but their design and optimization are challenging due to the large number of geometric degrees of freedom and the need for compute-intensive 3D simulations. Here, we demonstrate inverse design of χ(2) SWG waveguides using an efficient and accurate differentiable plane-wave expansion (PWE) eigensolver. Our solver, which incorporates sparse iterative algorithms and subpixel smoothing, enables efficient eigensolution and end-to-end differentiation from geometric parameters to the SWG figure of merit, which depends both on the eigenvalues (first-order perturbation theory) and the eigenvectors and group indices (second-order perturbation theory), both in forward- and reverse-mode. We apply this solver to the design and optimization of metamaterial waveguides for two types of backward SHG: idler-reversed and pump-reversed. This approach may find use in designing periodic structures more generally, including nanobeam cavities, slow-light modulators, and vertically coupled resonators.
We route the single photons from a trapped barium ion in a nanophotonic circuit. For this routing, we first generate C-band telecom single photons from barium ion which makes them compatible with the silicon-nitride photonic foundry. Then using the thermo-optic property of silicon-nitride, we switch the single photons in a Mach-Zehnder interferometer controlling the current of the phase-shifter. These results could enable a new generation of compact and reconfigurable integrated photonic devices that can serve as efficient quantum interconnects for quantum computers and sensors.
Conventional multiport interferometers based on MZI meshes suffer from component imperfections, which limit their scaling. We introduce two new designs that overcome this limitation: a 3-splitter MZI for generic errors and a broadband MZI+Crossing design for more realistic correlated errors. These architectures, motivated by the correspondence between SU(2) and the Riemann sphere, are more error tolerant than the standard MZI mesh and support progressive self-configuration. Numerical simulations reveal orders-of-magnitude error reductions compared to the standard MZI mesh; moreover, the mesh is asymptotically perfect: the matrix error decreases with mesh size.
KEYWORDS: Wavelength division multiplexing, Neural networks, Integrated optics, Modulators, Computer programming, Modulation, Analog electronics, Time-frequency analysis, Signal to noise ratio
We introduce an optical neural-network architecture for edge computing that takes advantage of wavelength multiplexing, high-bandwidth modulation, and integration detection. Our protocol consists of a server and a client, which divide the task of neural-network inference into two steps: (1) a difficult step of optical weight distribution, performed at the server and (2) an easy step of modulation and integration detection, performed at the edge device. This arrangement allows for large-scale neural networks to be run on low-power edge devices accessible by an optical link. We perform simulations to estimate the speed and energy limits of this scheme.
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