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Allie X. Wu
Researcher at Princeton University
Publications - 15
Citations - 869
Allie X. Wu is an academic researcher from Princeton University. The author has contributed to research in topics: Photonics & Silicon photonics. The author has an hindex of 6, co-authored 15 publications receiving 582 citations.
Papers
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Journal ArticleDOI
Neuromorphic photonic networks using silicon photonic weight banks.
Alexander N. Tait,Thomas Ferreira de Lima,Ellen Zhou,Allie X. Wu,Mitchell A. Nahmias,Bhavin J. Shastri,Paul R. Prucnal +6 more
TL;DR: First observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks are reported, and a mathematical isomorphism between the silicon photonics circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis.
Journal ArticleDOI
Neuromorphic Silicon Photonic Networks
Alexander N. Tait,Thomas Ferreira de Lima,Ellen Zhou,Allie X. Wu,Mitchell A. Nahmias,Bhavin J. Shastri,Paul R. Prucnal +6 more
TL;DR: In this article, a recurrent silicon photonic neural network, in which connections are configured by microring weight banks, is presented and power consumption analysis for modulator-class neurons is derived.
Journal ArticleDOI
Microring Weight Banks
Alexander N. Tait,Allie X. Wu,Thomas Ferreira de Lima,Ellen Zhou,Bhavin J. Shastri,Mitchell A. Nahmias,Paul R. Prucnal +6 more
TL;DR: By introducing a quantitative description of independent weighting, this work establishes performance tradeoffs between channel count and power penalty in microring weight banks, which are central to analog wavelength-division multiplexed processing networks in silicon.
Journal ArticleDOI
Two-pole microring weight banks.
Alexander N. Tait,Allie X. Wu,Thomas Ferreira de Lima,Mitchell A. Nahmias,Bhavin J. Shastri,Paul R. Prucnal +5 more
TL;DR: Two-pole designs are fabricated that exploit inter-channel interference in MRR weight banks in a way that is robust to dynamic tuning and fabrication variation and predicts a channel count improvement of 3.4-fold, which is substantially greater than predicted by incoherent analysis used in conventional MRR devices.
Posted Content
Neuromorphic Silicon Photonics.
Alexander N. Tait,Ellen Zhou,Thomas Ferreira de Lima,Allie X. Wu,Mitchell A. Nahmias,Bhavin J. Shastri,Paul R. Prucnal +6 more
TL;DR: First observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks are reported, which could access new regimes of ultrafast information processing for radio, control, and scientific computing.