activity
20222026
most citedImage sensing with multilayer, nonlinear optical neural networks

271 citations · 346 across the 13 of their papers we have counts for

collaborators

14 papers

physics.optics2026

Measurement-Adapted Eigentask Representations for Photon-Limited Optical Readout

Tianyang Chen, Mandar M. Sohoni, Saeed A. Khan +5

Optical readout in low-light imaging is fundamentally limited by measurement noise, including photon shot noise, detector noise, and quantization error. In this regime, downstream…

cs.LG2026

Physical Foundation Models: Fixed hardware implementations of large-scale neural networks

Logan G Wright, Tianyu Wang, Tatsuhiro Onodera +1

Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks -- text and code generation, qu…

cs.CV2026

Ultra-low-light computer vision using trained photon correlations

Mandar M. Sohoni, Jérémie Laydevant, Mathieu Ouellet +7

Illumination using correlated photon sources has been established as an approach to allowing high-fidelity images to be reconstructed from noisy camera frames by taking advantage o…

cs.CV2026

Radiology Report Generation for Low-Quality X-Ray Images

Hongze Zhu, Chen Hu, Jiaxuan Jiang +6

Vision-Language Models (VLMs) have significantly advanced automated Radiology Report Generation (RRG). However, existing methods implicitly assume high-quality inputs, overlooking…

physics.optics2026

Machine vision with small numbers of detected photons per inference

Shi-Yuan Ma, Jérémie Laydevant, Mandar M. Sohoni +3

Machine vision, including object recognition and image reconstruction, is a central technology in many consumer devices and scientific instruments. The design of machine-vision sys…

quant-ph2025

Quantum optical neural networks using atom-cavity interactions to provide all-optical nonlinearity

Chuanzhou Zhu, Tianyu Wang, Peter L. McMahon +1

Optical neural networks (ONNs) have been developed to enhance processing speed and energy efficiency in machine learning by leveraging optical devices for nonlinear activation and…

quant-ph2025

Large-scale quantum reservoir computing using a Gaussian Boson Sampler

Valeria Cimini, Mandar M. Sohoni, Federico Presutti +7

A Gaussian boson sampler (GBS) is a special-purpose quantum computer that can be practically realized at large scale in optics. Here we report on experiments in which we used a fre…

cs.ET2025★ 18 cited

Roadmap on Neuromorphic Photonics

Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147

This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…

physics.optics2024★ 7 cited

Arbitrary control over multimode wave propagation for machine learning

Tatsuhiro Onodera, Martin M. Stein, Benjamin A. Ash +10

Controlled multimode wave propagation can enable more space-efficient photonic processors than architectures based on discrete components connected by single-mode waveguides. Inste…

quant-ph2024★ 4 cited

Tunable spectral correlations of highly multimode visible light via broadband quantum frequency conversion

Federico Presutti, Logan G. Wright, Shi-Yuan Ma +4

Multimode squeezed states of light are a resource for achieving quantum advantage in computing and sensing, where spatial or temporal modes have been the experimental norm. In our…

cs.ET2023★ 16 cited

The hardware is the software

Jeremie Laydevant, Logan G. Wright, Tianyu Wang +1

Human brains and bodies are not hardware running software: the hardware is the software. We reason that because the microscopic physics of artificial-intelligence hardware and of h…

physics.optics2023★ 24 cited

Quantum-limited stochastic optical neural networks operating at a few quanta per activation

Shi-Yuan Ma, Tianyu Wang, Jérémie Laydevant +2

Energy efficiency in computation is ultimately limited by noise, with quantum limits setting the fundamental noise floor. Analog physical neural networks hold promise for improved…

cs.ET2023★ 6 cited

Optical Transformers

Maxwell G. Anderson, Shi-Yuan Ma, Tianyu Wang +2

The rapidly increasing size of deep-learning models has caused renewed and growing interest in alternatives to digital computers to dramatically reduce the energy cost of running s…

physics.optics2022★ 271 cited

Image sensing with multilayer, nonlinear optical neural networks

Tianyu Wang, Mandar M. Sohoni, Logan G. Wright +5

Optical imaging is commonly used for both scientific and technological applications across industry and academia. In image sensing, a measurement, such as of an object's position,…