arXiv subjects

Robert M. Gray

Publications and source records attributed to Robert M. Gray.

22 records · Page 2Linked to original sources

arXiv2022

All-optical ultrafast ReLU function for energy-efficient nanophotonic deep learning

In recent years, the computational demands of deep learning applications have necessitated the introduction of energy-efficient hardware accelerators. Optical neural networks are a promising option; however, thus far they have been largely limited by the lack of energy-efficient nonlinear optical functions. Here, we experimentally demonstrate an all-optical Rectified Linear Unit (ReLU), which is the most widely used nonlinear activation function for deep learning, using a periodically-poled thin-film lithium niobate nanophotonic waveguide and achieve ultra-low energies in the regime of femtojoules per activation with near-instantaneous operation. Our results provide a clear and practical path towards truly all-optical, energy-efficient nanophotonic deep learning.

physics.optics↗

arXiv2021

Femtojoule, femtosecond all-optical switching in lithium niobate nanophotonics

Optical nonlinear functions are crucial for various applications in integrated photonics, such as all-optical information processing, photonic neural networks and on-chip ultrafast light sources. Due to the weak nonlinearities in most integrated photonic platforms, realizing optical nonlinear functions typically requires large driving energies in the picojoules level or beyond, thus imposing a barrier for most applications. Here, we tackle this challenge and demonstrate an integrated nonlinear splitter device in lithium niobate nano-waveguides by simultaneous engineering of the dispersion and quasi-phase matching. We achieve non-resonant all-optical switching with ultra-low energies down to tens of femtojoules, a near instantaneous switching time of 18 fs, and a large extinction ratio of more than 5 dB. Our nonlinear splitter simultaneously realizes switch-on and -off operations and features a state-of-the-art switching energy-time product as low as $1.4 \times10^{-27}$ J$\cdot$s. We also show a path toward attojoule level all-optical switching by further optimizing the device geometry. Our results can enable on-chip ultrafast and energy-efficient all-optical information processing, computing systems, and light sources.

physics.optics↗

arXiv2011

Rate-Constrained Simulation and Source Coding IID Sources

Necessary conditions for asymptotically optimal sliding-block or stationary codes for source coding and rate-constrained simulation of memoryless sources are presented and used to motivate a design technique for trellis-encoded source coding and rate-constrained simulation. The code structure has intuitive similarities to classic random coding arguments as well as to ``fake process'' methods and alphabet-constrained methods. Experimental evidence shows that the approach provides comparable or superior performance in comparison with previously published methods on common examples, sometimes by significant margins.

cs.IT↗

arXiv2007

A note on rate-distortion functions for nonstationary Gaussian autoregressive processes

Source coding theorems and Shannon rate-distortion functions were studied for the discrete-time Wiener process by Berger and generalized to nonstationary Gaussian autoregressive processes by Gray and by Hashimoto and Arimoto. Hashimoto and Arimoto provided an example apparently contradicting the methods used in Gray, implied that Gray's rate-distortion evaluation was not correct in the nonstationary case, and derived a new formula that agreed with previous results for the stationary case and held in the nonstationary case. In this correspondence it is shown that the rate-distortion formulas of Gray and Hashimoto and Arimoto are in fact consistent and that the example of of Hashimoto and Arimoto does not form a counter example to the methods or results of the earlier paper. Their results do provide an alternative, but equivalent, formula for the rate-distortion function in the nonstationary case and they provide a concrete example that the classic Kolmogorov formula differs from the autoregressive formula when the autoregressive source is not stationary. Some observations are offered on the different versions of the Toeplitz asymptotic eigenvalue distribution theorem used in the two papers to emphasize how a slight modification of the classic theorem avoids the problems with certain singularities.

cs.IT↗