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Gaussian Boson Sampling (GBS) provides a route toward demonstrating quantum computational advantage. However, optical loss, which reduces the entanglement in the system, can render GBS results classically simulable. We propose a nonlinear…

Quantum Physics · Physics 2026-05-29 Yukuan Zhao , Xiao-Ye Xu , Chuan-Feng Li , Guang-Can Guo

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that can solve large-scale combinatorial optimisation problems by finding the ground state of an Ising Hamiltonian. As a practical application of CIM, Aonishi et…

High-dimensional optimization is a critical challenge for operating large-scale scientific facilities. We apply a physics-informed Gaussian process (GP) optimizer to tune a complex system by conducting efficient global search. Typical GP…

Computational Physics · Physics 2021-07-14 Adi Hanuka , X. Huang , J. Shtalenkova , D. Kennedy , A. Edelen , V. R. Lalchand , D. Ratner , J. Duris

Recently, spatial photonic Ising machines (SPIMs) have demonstrated the abilities to compute the Ising Hamiltonian of large-scale spin systems, with the advantages of ultrafast speed and high power efficiency. However, such optical…

Optics · Physics 2024-01-17 Li Luo , Zhiyi Mi , Junyi Huang , Zhichao Ruan

Optical parametric oscillators (OPOs) have been studied as basic components for optical computing with phase encoding and Ising machines. Integrated photonics offers a scalable solution to incorporate a progressively larger number of…

Optics · Physics 2025-05-16 Jost Kellner , Alessandra Sabatti , Andreas Meader , Rachel Grange

Ellipsometry is a powerful and well-established optical technique used in the characterisation of materials. It works by combining the components of elliptically polarized light in order to draw information about the optical system. We…

Optics · Physics 2018-03-15 Manoel P. Araújo , Stefano De Leo , Gabriel G. Maia

Dynamical Ising machines achieve accelerated solving of complex combinatorial optimization problems by remapping the convergence to the ground state of the classical spin networks to the evolution of specially constructed continuous…

Emerging Technologies · Computer Science 2025-12-30 Aditya Shukla , Mikhail Erementchouk , Pinaki Mazumder

The commercial and industrial demand for the solution of hard combinatorial optimization problems push forward the development of efficient solvers. One of them is the Ising machine which can solve combinatorial problems mapped to Ising…

Similariton-like pulses are found to be formed in synchronously pumped singly resonant optical parametric oscillators (OPO) by numerical simulation. The nonlinear coupled-wave equations can be reduced to inhomogeneous nonlinear…

Pattern Formation and Solitons · Physics 2015-02-04 Fuyong Wang , Guoqiang Xie , Peng Yuan , Liejia Qian , Dingyuan Tang

Combinatorial optimization has wide applications from industry to natural science. Ising machines bring an emerging computing paradigm for efficiently solving a combinatorial optimization problem by searching a ground state of a given Ising…

Statistical Mechanics · Physics 2024-07-16 Kentaro Ohno , Tatsuhiko Shirai , Nozomu Togawa

Open-dissipative systems obeying parity-time ($\mathcal{PT}$) symmetry are capable of demonstrating oscillatory dynamics akin to the conservative systems. In contrast to limit cycle solutions characteristic of nonlinear systems, the…

Mesoscale and Nanoscale Physics · Physics 2021-09-01 I. Chestnov , Y. G. Rubo , A. Nalitov , A. Kavokin

Physical Ising machines rely on nature to guide a dynamical system towards an optimal state which can be read out as a heuristical solution to a combinatorial optimization problem. Such designs that use nature as a computing mechanism can…

We demonstrate robust programmable state preparation in small VCSEL arrays with optical feedback using transient optical injection in the form of Gaussian pulses. In Lang--Kobayashi type models of delay-coupled 2- and 3-laser arrays,…

Optics · Physics 2026-04-21 Max M. Chumley , Herbert G. Winful

Ising machines as hardware solvers of combinatorial optimization problems (COPs) can efficiently explore large solution spaces due to their inherent parallelism and physics-based dynamics. Many important COP classes such as satisfiability…

This paper presents a coupled ring oscillator based Potts ma chine to solve NP-hard combinatorial optimization problems (COPs). Potts model is a generalization of the Ising model, cap turing multivalued spins in contrast to the…

Hardware Architecture · Computer Science 2025-04-08 Yilmaz Ege Gonul , Baris Taskin

We explore the coherent dynamics in a small network of three coupled parametric oscillators and demonstrate the effect of frustration on the persistent beating between them. Since a single-mode parametric oscillator represents an analog of…

The aim of this work is to prove that it is possible to realise an optical system which produces as output a light intensity that can be expressed in the same mathematical form of the spin glass Hamiltonian. The optical system under study…

Disordered Systems and Neural Networks · Physics 2020-10-27 Erik Hörmann

The challenge posted by modern science is to find a way to compute the NP-hard problem. Here we present a coherent computation model based on the whispering-gallery mode micro-resonators. We introduce the optically connected…

Optics · Physics 2022-06-28 Yong-Pan Gao , Peng-Fei Lu , Chuan Wang

We investigate the dynamics of multi-mode optical systems driven by two-photon processes and subject to non-local losses, incorporating quantum noise at the Gaussian level. Our findings show that the statistics retrieved from a single…

Quantum Physics · Physics 2024-12-18 Jacopo Tosca , Marcello Calvanese Strinati , Claudio Conti , Cristiano Ciuti

Bayesian optimization (BO) methods are useful for optimizing functions that are expensive to evaluate, lack an analytical expression and whose evaluations can be contaminated by noise. These methods rely on a probabilistic model of the…

Machine Learning · Statistics 2020-02-04 Eduardo C. Garrido-Merchán , Daniel Hernández-Lobato
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