Scaling on-chip photonic neural processors using arbitrarily programmable wave propagation

arXiv:2402.17750v1 Announce Type: cross
Abstract: On-chip photonic processors for neural networks have potential benefits in both speed and energy efficiency but have not yet reached the scale at which they can outperform electronic processors. The dominant paradigm for designing on-chip photonics is to make networks of relatively bulky discrete components connected by one-dimensional waveguides. A far more compact alternative is to avoid explicitly defining any components and instead sculpt the continuous substrate of the photonic processor to directly perform the …

abstract arxiv benefits chip components cs.et cs.lg designing efficiency electronic energy energy efficiency networks neural networks paradigm photonics physics.optics processors propagation scale scaling speed type