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Photonic principal component analysis using an on-chip microring weight bank
Author(s) -
Y. Philip,
Alexander N. Tait,
Thomas Ferreira de Lima,
Siamak Abbaslou,
Bhavin J. Shastri,
Paul R. Prucnal
Publication year - 2019
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.018329
Subject(s) - principal component analysis , photonics , computer science , multiplexing , chip , channel (broadcasting) , curse of dimensionality , interference (communication) , wavelength division multiplexing , dimensionality reduction , electronic engineering , algorithm , optics , wavelength , telecommunications , artificial intelligence , physics , engineering
Photonic principal component analysis (PCA) enables high-performance dimensionality reduction in wideband analog systems. In this paper, we report a photonic PCA approach using an on-chip microring (MRR) weight bank to perform weighted addition operations on correlated wavelength-division multiplexed (WDM) inputs. We are able to configure the MRR weight bank with record-high accuracy and precision, and generate multi-channel correlated input signals in a controllable manner. We also consider the realistic scenario in which the PCA procedure remains blind to the waveforms of both the input signals and weighted addition output, and propose a novel PCA algorithm that is able to extract principal components (PCs) solely based on the statistical information of the weighted addition output. Our experimental demonstration of two-channel photonic PCA produces PCs holding consistently high correspondence to those computed by a conventional software-based PCA method. Our numerical simulation further validates that our scheme can be generalized to high-dimensional (up to but not limited to eight-channel) PCA with good convergence. The proposed technique could bring new solutions to problems in microwave communications, ultrafast control, and on-chip information processing.

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