Photonic principal component analysis using an on-chip microring weight bank

Philip Y. Ma, Alexander N. Tait, Thomas Ferreira De Lima, Siamak Abbaslou, Bhavin J. Shastri, Paul R. Prucnal

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)18329-18342
Number of pages14
JournalOptics Express
Volume27
Issue number13
DOIs
StatePublished - 2019

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics

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