747 citations · 1.9k across the 25 of their papers we have counts for
28 papers
Lithography-free in situ photonic inverse design
Yiqi Zhao, Martin M. Stein, Fan O. Wu +6
Inverse design has emerged as a powerful engineering approach in nanophotonics, leading to devices with unintuitive designs that extend beyond human intuition. However, inverse-des…
Programmable nonlinearity within nanophotonic waveguides
Benjamin A. Ash, Ryotatsu Yanagimoto, Mandar M. Sohoni +8
Nonlinear nanophotonics enables the engineering of optical functions using light-matter interactions in nanoscale structures with carefully designed geometries. Phase matching in n…
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…
TRON: Trainable, architecture-reconfigurable random optical neural networks
Ziao Wang, Fei Xia, Logan G. Wright +5
Deep learning has triggered explosive growth in the demand for specialized hardware processors, thus motivating the development of scalable and reconfigurable computing substrates.…
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…
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…
Programmable on-chip nonlinear photonics
Ryotatsu Yanagimoto, Benjamin A. Ash, Mandar M. Sohoni +7
Nonlinear photonics uses coherent interactions between optical waves to engineer functionality that is not possible with purely linear optics. Traditionally, the function of a nonl…
Training of Physical Neural Networks
Ali Momeni, Babak Rahmani, Benjamin Scellier +25
Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research…
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…
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…
Microwave signal processing using an analog quantum reservoir computer
Alen Senanian, Sridhar Prabhu, Vladimir Kremenetski +8
Quantum reservoir computing (QRC) has been proposed as a paradigm for performing machine learning with quantum processors where the training is efficient in the number of required…
Mesoscopic ultrafast nonlinear optics -- The emergence of multimode quantum non-Gaussian physics
Ryotatsu Yanagimoto, Edwin Ng, Marc Jankowski +8
Over the last few decades, nonlinear optics has become significantly more nonlinear, traversing nearly a billionfold improvement in energy efficiency, with ultrafast nonlinear nano…
Using system-reservoir methods to derive effective field theories for broadband nonlinear quantum optics: a case study on cascaded quadratic nonlinearities
Chris Gustin, Ryotatsu Yanagimoto, Edwin Ng +2
In broadband quantum optical systems, nonlinear interactions among a large number of frequency components induce complex dynamics that may defy heuristic analysis. In this work we…
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,…
Onset of non-Gaussian quantum physics in pulsed squeezing with mesoscopic fields
Ryotatsu Yanagimoto, Edwin Ng, Atsushi Yamamura +6
We study the emergence of non-Gaussian quantum features in pulsed squeezed light generation with a mesoscopic number (i.e., dozens to hundreds) of pump photons. Due to the strong o…
A Benchmarking Study of Quantum Algorithms for Combinatorial Optimization
Krishanu Sankar, Artur Scherer, Satoshi Kako +8
We study the performance scaling of three quantum algorithms for combinatorial optimization: measurement-feedback coherent Ising machines (MFB-CIM), discrete adiabatic quantum comp…
An optical neural network using less than 1 photon per multiplication
Tianyu Wang, Shi-Yuan Ma, Logan G. Wright +3
Deep learning has rapidly become a widespread tool in both scientific and commercial endeavors. Milestones of deep learning exceeding human performance have been achieved for a gro…
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems
Logan G. Wright, Tatsuhiro Onodera, Martin M. Stein +4
Deep neural networks have become a pervasive tool in science and engineering. However, modern deep neural networks' growing energy requirements now increasingly limit their scaling…
Efficient sampling of ground and low-energy Ising spin configurations with a coherent Ising machine
Edwin Ng, Tatsuhiro Onodera, Satoshi Kako +3
We show that the nonlinear stochastic dynamics of a measurement-feedback-based coherent Ising machine (MFB-CIM) in the presence of quantum noise can be exploited to sample degenera…
Towards an Engineering Framework for Ultrafast Quantum Nonlinear Optics
Ryotatsu Yanagimoto, Edwin Ng, Tatsuhiro Onodera +1
The advent of dispersion-engineered and highly nonlinear nanophotonics is expected to open up an all-optical path towards the strong-interaction regime of quantum optics by combini…
Efficient simulation of ultrafast quantum nonlinear optics with matrix product states
Ryotatsu Yanagimoto, Edwin Ng, Logan G. Wright +2
Ultra-short pulses propagating in nonlinear nanophotonic waveguides can simultaneously leverage both temporal and spatial field confinement, promising a route towards single-photon…
Broadband Parametric Downconversion as a Discrete-Continuum Fano Interaction
Ryotatsu Yanagimoto, Edwin Ng, Marc P. Jankowski +3
We introduce a theoretical framework based on Fano's theory of discrete-continuum interactions to analyze the quantum dynamics of broadband parametric downconversion (PDC) in the f…
Engineering a Kerr-based Deterministic Cubic Phase Gate via Gaussian Operations
Ryotatsu Yanagimoto, Tatsuhiro Onodera, Edwin Ng +3
We propose a deterministic, measurement-free implementation of a cubic phase gate for continuous-variable quantum information processing. In our scheme, the applications of displac…
A quantum annealer with fully programmable all-to-all coupling via Floquet engineering
Tatsuhiro Onodera, Edwin Ng, Peter L. McMahon
Quantum annealing is a promising approach to heuristically solving difficult combinatorial optimization problems. However, the connectivity limitations in current devices lead to a…