English
Related papers

Related papers: Gaussian Optical Ising Machines

200 papers

Optical parametric oscillation (OPO) is distinguished by its wavelength access, that is, the ability to flexibly generate coherent light at wavelengths that are dramatically different from the pump laser, and in principle bounded solely by…

We investigate an oscillator linearly coupled with a one-dimensional Ising system. The coupling gives rise to drastic changes both in the oscillator statics and dynamics. Firstly, there appears a second order phase transition, with the…

Statistical Mechanics · Physics 2015-05-27 A. Prados , L. L. Bonilla , A. Carpio

We propose a methodology for implementing Grover's algorithm in the digital quantum simulation of disordered Ising models. The core concept revolves around using the evolution operator for the Ising model as the quantum oracle within…

Quantum Physics · Physics 2025-04-28 Andrey Zhukov , Andrey Lebedev , Walter Pogosov

Ising machines exploit the natural dynamics of physical systems to minimize the Ising Hamiltonian and thereby address computationally hard combinatorial optimization problems. This paradigm has motivated a range of physical implementations.…

Computational Physics · Physics 2026-03-10 Abir Hasan , Nikhil Shukla

Optimizing an expensive-to-query function is a common task in science and engineering, where it is beneficial to keep the number of queries to a minimum. A popular strategy is Bayesian optimization (BO), which leverages probabilistic models…

Machine Learning · Computer Science 2019-07-05 Willie Neiswanger , Kirthevasan Kandasamy , Barnabas Poczos , Jeff Schneider , Eric Xing

When signals are measured through physical sensors, they are perturbed by noise. To reduce noise, low-pass filters are commonly employed in order to attenuate high frequency components in the incoming signal, regardless if they come from…

Signal Processing · Electrical Eng. & Systems 2021-11-08 Alejandro J. Ordóñez-Conejo , Armin Lederer , Sandra Hirche

An improved Iterative Physical Optics (IPO) image approximation method has been presented to dramatically increase the accuracy of the approximation and extend its applicability to PEC surfaces with smaller radii or larger curvatures.…

Classical Physics · Physics 2020-07-07 Shaolin Liao , Lu Ou

Miniaturized heat engines constitutes a fascinating field of current research. They are being studied theoretically as well as experimentally, with experiments involving colloidal particles and harmonic traps and even bacterial baths acting…

Statistical Mechanics · Physics 2017-07-04 Debarshi Basu , Joydip Nandi , A. M. Jayannavar , Rahul Marathe

Several powerful machines, such as the D-Wave 2000Q, dedicated to solving combinatorial optimization problems through the Ising-model formulation have been developed. To input problems into the machines, the unknown parameters on the Ising…

The successful development and optimisation of optically-driven micromachines will be greatly enhanced by the ability to computationally model the optical forces and torques applied to such devices. In principle, this can be done by…

Recently, several platforms were proposed and demonstrated a proof-of-principle for finding the global minimum of the spin Hamiltonians such as the Ising and XY models using gain-dissipative quantum and classical systems. The implementation…

Emerging Technologies · Computer Science 2018-07-03 Kirill P. Kalinin , Natalia G. Berloff

Due to an extremely rugged structure of the free energy landscape, the determination of spin-glass ground states is among the hardest known optimization problems, found to be NP-hard in the most general case. Owing to the specific structure…

Disordered Systems and Neural Networks · Physics 2011-11-10 Martin Weigel

Mesoscopic mechanical oscillators can be prepared in quantum states and coherently manipulated using the optomechanical interaction. This has recently been used to prepare squeezed mechanical states. However, the scheme used in these…

Quantum Physics · Physics 2018-11-14 James S. Bennett , Warwick P. Bowen

We study entanglement dynamics in dispersive optomechanical systems consisting of two optical modes and a mechanical oscillator inside an optical cavity. The two optical modes interact with the mechanical oscillator, but not directly with…

Quantum Physics · Physics 2021-01-04 Igor Brandão , Bruno Suassuna , Bruno Melo , Thiago Guerreiro

It is well known in quantum optics that any process involving the preparation of a multimode gaussian state, followed by a gaussian operation and gaussian measurements, can be efficiently simulated by classical computers. Here, we provide…

Quantum Physics · Physics 2025-08-22 Michael G. Jabbour , Leonardo Novo

Optical Character Recognition and extraction is a key tool in the automatic evaluation of documents in a financial context. However, the image data provided to automated systems can have unreliable quality, and can be inherently…

Computer Vision and Pattern Recognition · Computer Science 2020-05-11 Steven I Reeves , Dongwook Lee , Anurag Singh , Kunal Verma

Classical or quantum physical systems can simulate the Ising Hamiltonian for large-scale optimization and machine learning. However, devices such as quantum annealers and coherent Ising machines suffer an exponential drop in the probability…

Optics · Physics 2024-01-09 Marcello Calvanese Strinati , Claudio Conti

We present a simple quantum theory for the pulsed light generated by a synchronously pumped optical parametric oscillator (SPOPO) in the degenerate case where the signal and idler trains of pulses coincide, below threshold and neglecting…

Quantum Physics · Physics 2015-05-19 V. A. Averchenko , Yu. M. Golubev , C. Fabre , N. Treps

Networks of coupled Kerr parametric oscillators (KPOs) hold promise as for the realization of neuromorphic and quantum computation. Yet, their rich bifurcation structure remains largely not understood. Here, we employ secular perturbation…

Mesoscale and Nanoscale Physics · Physics 2025-01-16 Orjan Ameye , Alex Eichler , Oded Zilberberg

We introduce a new interpretation of sparse variational approximations for Gaussian processes using inducing points, which can lead to more scalable algorithms than previous methods. It is based on decomposing a Gaussian process as a sum of…

Machine Learning · Statistics 2024-02-27 Jiaxin Shi , Michalis K. Titsias , Andriy Mnih