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arXiv · 2505.23464

Trainable dynamical masking for readout-free optical computing

S. Bogdanov·E. Manuylovich·S. K. Turitsyn
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Abstract

Nonlinear systems, transforming an input signal into a high-dimensional output feature space, can be used for non-conventional computing. This approach, however, requires a change of system parameters during training rather than coefficients in a software program. We propose here to use available off-the-shelf high-speed optical communication devices and technologies to implement a trainable dynamical mask in addition to or even instead of the traditional readout layer for extreme learning machine-based computing. The computational potential of the proposed approach is demonstrated with both regression and time series prediction tasks.

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S. Bogdanov, E. Manuylovich, S. K. Turitsyn. 2025-05-29. Trainable dynamical masking for readout-free optical computing. https://arxiv.org/abs/2505.23464

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