We describe a physics-based data compression method inspired by the photonic time stretch wherein information-rich portions of the data are dilated in a process that emulates the effect of group velocity dispersion on temporal signals. With this coding operation, the data can be downsampled at a lower rate than without it. In contrast to previous implementation of the warped stretch compression, here the decoding can be performed without the need of phase recovery. We present rate-distortion analysis and show improvement in PSNR compared to compression via uniform downsampling.

We introduce three types of analog optical accelerators for enhancing the performance of electronic computing. These include (1) physical computing using complex optical dynamics in silicon for acceleration of scientific computing, (2) spectrotemporal processing and sparse coding using dispersion basis functions and (3) photonic computing primitives for performing nonlinear mathematical operations.

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