Publications (36)
100 Mfps ghost imaging with wavelength division multiplexing
Shin Motooka, Noriki Komori, Tomoaki Niiyama +1
Ghost imaging (GI) and single-pixel imaging (SPI) techniques enable image reconstruction without spatially resolved detectors, offering unique access to wide spectral ranges and ch…
Photonic reservoir computing based on nonlinear wave dynamics at a microscale
Satoshi Sunada, Atsushi Uchida
High-dimensional nonlinear dynamical systems including neural networks can be utilized as a computational resource for information processing. In this sense, nonlinear wave systems…
Chaos-assisted emission from asymmetric resonant cavity microlasers
Susumu Shinohara, Takahisa Harayama, Takehiro Fukushima +3
We study emission from quasi-one-dimensional modes of an asymmetric resonant cavity that are associated with a stable periodic ray orbit confined inside the cavity by total interna…
Wave Chaos in Rotating Optical Cavities
Takahisa Harayama, Satoshi Sunada, Tomohiro Miyasaka
It is shown that, even when the eigenmodes of an optical cavity are wave-chaotic, the frequency splitting due to the rotation of the cavity occurs and the frequency difference is p…
Sagnac effect in resonant microcavities
Satoshi Sunada, Takahisa Harayama
The Sagnac effect in two dimensional (2D) resonant microcavities is studied theoretically and numerically. The frequency shift due to the Sagnac effect occurs as a threshold phenom…
Programmable Photonic Circuit for Optical Logic Operations and 2-Bit Decoding
Noel Francisco Prado Bucaro, Yushan Hu, Satoshi Sunada +1
We present a programmable silicon photonic circuit composed of cascaded multiport directional couplers interleaved with thermo-optic phase shifters. The device forms a reconfigurab…
A thin and soft optical tactile sensor for highly sensitive object perception
Yanchen Shen, Kohei Tsuji, Haruto Koizumi +7
Tactile sensing is crucial in robotics and wearable devices for safe perception and interaction with the environment. Optical tactile sensors have emerged as promising solutions, a…
Universal single-mode lasing in fully chaotic two-dimensional microcavity lasers under continuous-wave operation with large pumping power
Takahisa Harayama, Satoshi Sunada, Susumu Shinohara
For a fully chaotic two-dimensional (2D) microcavity laser, we present a theory that guarantees both the existence of a stable single-mode lasing state and the nonexistence of a st…
Long-path formation in a deformed microdisk laser
Susumu Shinohara, Takehiro Fukushima, Satoshi Sunada +2
An asymmetric resonant cavity can be used to form a path that is much longer than the cavity size. We demonstrate this capability for a deformed microdisk equipped with two linear…
Model-free front-to-end training of a large high performance laser neural network
Anas Skalli, Satoshi Sunada, Mirko Goldmann +5
Artificial neural networks (ANNs), have become ubiquitous and revolutionized many applications ranging from computer vision to medical diagnoses. However, they offer a fundamentall…
Ultrafast single-channel machine vision based on neuro-inspired photonic computing
Tomoya Yamaguchi, Kohei Arai, Tomoaki Niiyama +2
High-speed machine vision is increasing its importance in both scientific and technological applications. Neuro-inspired photonic computing is a promising approach to speed-up mach…
Physical Reservoir Signal Acquisition for Sub-Nyquist Waveform Reconstruction
Yuito Ito, Anas Skalli, Tetsuya Asai +1
The paper proposes reservoir signal acquisition, using a physical reservoir as a measurement device to transform broadband signals into multiple low‑rate samples, enabling exact or…
Using multidimensional speckle dynamics for high-speed, large-scale, parallel photonic computing
Satoshi Sunada, Kazutaka Kanno, Atsushi Uchida
The recent rapid increase in demand for data processing has resulted in the need for novel machine learning concepts and hardware. Physical reservoir computing and an extreme learn…
Physical deep learning based on optimal control of dynamical systems
Genki Furuhata, Tomoaki Niiyama, Satoshi Sunada
Deep learning is the backbone of artificial intelligence technologies, and it can be regarded as a kind of multilayer feedforward neural network. An essence of deep learning is inf…
Analysis of temporal structure of laser chaos by Allan variance
Naoki Asuke, Nicolas Chauvet, André Röhm +6
Allan variance has been widely utilized in evaluating the stability of the time series generated by atomic clocks and lasers, in time regimes ranging from short to extremely long.…
General-Purpose Nonlinear Function Approximation via Linear Integrated Photonics
Ayana Mizuno, Isamu Takai, Makoto Nakai +3
Photonic computing has emerged as a promising platform for accelerating artificial intelligence workloads by enabling low-latency and energy-efficient linear operations such as vec…
Roadmap for Unconventional Computing with Nanotechnology
Giovanni Finocchio, Jean Anne C. Incorvia, Joseph S. Friedman +48
In the "Beyond Moore's Law" era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same ti…
Blending Optimal Control and Biologically Plausible Learning for Noise-Robust Physical Neural Networks
Satoshi Sunada, Tomoaki Niiyama, Kazutaka Kanno +4
The rapidly increasing computational demands for artificial intelligence (AI) have spurred the exploration of computing principles beyond conventional digital computers. Physical n…
Power-law fluctuations near critical point in semiconductor lasers with delayed feedback
Tomoaki Niiyama, Satoshi Sunada
Since the analogy between laser oscillation and second-order phase transition was indicated in the 1970s, dynamical fluctuations on lasing threshold inherent in critical phenomena…
Signature of Wave Chaos in Spectral Characteristics of Microcavity Lasers
Satoshi Sunada, Susumu Shinohara, Takehiro Fukushima +1
We report the spectral characteristics of fully chaotic and non-chaotic microcavity lasers under continuous-wave operating conditions. It is found that fully chaotic microcavity la…
Efficient optical path folding by using multiple total internal reflections in a microcavity
Susumu Shinohara, Satoshi Sunada, Takehiro Fukushima +3
We propose using an asymmetric resonant microcavity for the efficient generation of an optical path that is much longer than the diameter of the cavity. The path is formed along a…
Parallel bandit architecture based on laser chaos for reinforcement learning
Takashi Urushibara, Nicolas Chauvet, Satoshi Kochi +5
Accelerating artificial intelligence by photonics is an active field of study aiming to exploit the unique properties of photons. Reinforcement learning is an important branch of m…
Design of resonant microcavities: application to optical gyroscopes
Satoshi Sunada, Takahisa Harayama
We study theoretically and numerically the effect of rotation on resonant frequencies of microcavities in a rotating frame of reference. Cavity rotation causes the shifts of the re…
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…
A ring laser gyroscope without lock-in phenomenon
Satoshi Sunada, Shuichi Tamura, Keizo Inagaki +1
We theoretically and numerically study the effect of backscattering on rotating ring lasers by employing the Maxwell-Bloch equations. We show that frequency shifts due to the Sagna…
Optical skin: Sensor-integration-free multimodal flexible sensing
Sho Shimadera, Kei Kitagawa, Koyo Sagehashi +2
The biological skin enables animals to sense various stimuli. Extensive efforts have been made recently to develop smart skin-like sensors to extend the capabilities of biological…
Controlling chaotic itinerancy in laser dynamics for reinforcement learning
Ryugo Iwami, Takatomo Mihana, Kazutaka Kanno +3
Photonic artificial intelligence has attracted considerable interest in accelerating machine learning; however, the unique optical properties have not been fully utilized for achie…
Photonic neural field on a silicon chip: large-scale, high-speed neuro-inspired computing and sensing
Satoshi Sunada, Atsushi Uchida
Photonic neural networks have significant potential for high-speed neural processing with low latency and ultralow energy consumption. However, the on-chip implementation of a larg…
Gigahertz-rate random speckle projection for high-speed single-pixel image classification
Jinsei Hanawa, Tomoaki Niiyama, Yutaka Endo +1
Imaging techniques based on single-pixel detection, such as ghost imaging, can reconstruct or recognize a target scene from multiple measurements using a sequence of random mask pa…
Expanding detection bandwidth via a photonic reservoir for ultrafast optical sensing
Yuito Ito, Tomoaki Niiyama, Tetsuya Asai +3
The detection of ultrafast optical and radio-frequency (RF) signals is crucial for applications ranging from high-speed communications to advanced sensing. However, conventional de…
Self-adjustment of a nonlinear lasing mode to a pumped area in a two-dimensional microcavity
Yuta Kawashima, Susumu Shinohara, Satoshi Sunada +1
We numerically performed wave dynamical simulations based on the Maxwell-Bloch (MB) model for a quadrupole-deformed microcavity laser with spatially selective pumping. We demonstra…
Chaotic laser based physical random bit streaming system with a computer application interface
Susumu Shinohara, Kenichi Arai, Peter Davis +2
We demonstrate a random bit streaming system that uses a chaotic laser as its physical entropy source. By performing real-time bit manipulation for bias reduction, we were able to…
Photonic reservoir computing with complex networks
Sion Park, Kohei Watabe, Satoshi Sunada +2
Photonic reservoir computing has attracted increasing attention as a fast and low-cost approach for time-series prediction. Photonic reservoir computing utilizes the high speed, br…
Optical hyperdimensional soft sensing: Speckle-based touch interface and tactile sensor
Kei Kitagawa, Kohei Tsuji, Koyo Sagehashi +2
Hyperdimensional computing (HDC) is an emerging computing paradigm that exploits the distributed representation of input data in a hyperdimensional space, the dimensions of which a…
Lotka-Volterra competition mechanism embedded in a decision-making method
Tomoaki Niiyama, Genki Furuhata, Atsushi Uchida +2
Decision making is a fundamental capability of living organisms, and has recently been gaining increasing importance in many engineering applications. Here, we consider a simple de…
Enhanced response of non-Hermitian photonic systems near exceptional points
Satoshi Sunada
This paper theoretically and numerically studies the response characteristics of non-Hermitian resonant photonic systems operating near an exceptional point (EP), where two resonan…