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Quantum and classical physics can be used for mathematical computations that are hard to tackle by conventional electronics. Very recently, optical Ising machines have been demonstrated for computing the minima of spin Hamiltonians, paving…

Optics · Physics 2019-06-26 D. Pierangeli , G. Marcucci , C. Conti

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…

Deep neural networks (DNNs) have shown very promising results for various image restoration (IR) tasks. However, the design of network architectures remains a major challenging for achieving further improvements. While most existing…

Computer Vision and Pattern Recognition · Computer Science 2020-10-28 Weisheng Dong , Peiyao Wang , Wotao Yin , Guangming Shi , Fangfang Wu , Xiaotong Lu

Networks of coupled Kerr parametric oscillators (KPOs) are a leading physical platform for analog solving of complex optimization problems. These systems are colloquially known as ``Ising machines''. We experimentally and theoretically…

Existing high-performance deep learning models require very intensive computing. For this reason, it is difficult to embed a deep learning model into a system with limited resources. In this paper, we propose the novel idea of the network…

Machine Learning · Computer Science 2019-02-13 Dae-Woong Jeong , Jaehun Kim , Youngseok Kim , Tae-Ho Kim , Myungsu Chae

Finding the ground state of an Ising-spin glass on general graphs belongs to the class of NP-hard problems, widely believed to have no efficient polynomial-time algorithms for solving them. An approach developed in computer science for…

Disordered Systems and Neural Networks · Physics 2022-04-06 Ran Yaacoby , Nathan Schaar , Leon Kellerhals , Oren Raz , Danny Hermelin , Rami Pugatch

In machine learning approach to image denoising a network is trained to recover a clean image from a noisy one. In this paper a novel structure is proposed based on training multiple specialized networks as opposed to existing structures…

Image and Video Processing · Electrical Eng. & Systems 2020-12-01 Seyed Mohsen Hosseini

We investigate the application of graph-cut methods for the study of the critical behaviour of the two-dimensional random-field Ising model. We focus on exact ground-state calculations, crossing the phase boundary of the model at zero…

Disordered Systems and Neural Networks · Physics 2022-04-04 Argyro Mainou , Nikolaos G. Fytas , Martin Weigel

In this paper we study the inference of the kinetic Ising model on sparse graphs by the decimation method. The decimation method, which was first proposed in [Phys. Rev. Lett. 112, 070603] for the static inverse Ising problem, tries to…

Disordered Systems and Neural Networks · Physics 2016-06-30 Aurélien Decelle , Pan Zhang

Computation with the Ising model is central to future computing technologies like quantum annealing, adiabatic quantum computing, and thermodynamic classical computing. Traditionally, computed values have been equated with ground states.…

Disordered Systems and Neural Networks · Physics 2025-11-04 Andrew G. Moore

Circuits of biological neurons, such as in the functional parts of the brain can be modeled as networks of coupled oscillators. Inspired by the ability of these systems to express a rich set of outputs while keeping (gradients of) state…

Machine Learning · Computer Science 2021-03-16 T. Konstantin Rusch , Siddhartha Mishra

In this paper, we propose a subgradient algorithm with a non-asymptotic convergence guarantee to solve copositive programming problems. The subproblem to be solved at each iteration is a standard quadratic programming problem, which is…

Optimization and Control · Mathematics 2026-04-30 Mitsuhiro Nishijima , Pierre-Louis Poirion , Akiko Takeda

The past decade has seen the emergence of Ising machines targeting hard combinatorial optimization problems by minimizing the Ising Hamiltonian with spins represented by continuous dynamical variables. However, capabilities of these…

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

This paper improves and in two cases nearly settles, up to logarithmically lower-order factors, the deterministic complexity of some of the most central problems in distributed graph algorithms, which have been studied for over three…

Data Structures and Algorithms · Computer Science 2024-10-28 Mohsen Ghaffari , Christoph Grunau

We extended the Broad Histogram Method in order to obtain spectral degeneracies for systems with multiparametric Hamiltonians. As examples we obtained the critical lines for the square lattice Ising model with nearest and next-nearest…

Statistical Mechanics · Physics 2009-10-31 A. R. Lima , P. M. C. de Oliveira , T. J. P. Penna

We propose a new method that uses deep learning techniques to solve the inverse problems. The inverse problem is cast in the form of learning an end-to-end mapping from observed data to the ground-truth. Inspired by the splitting strategy…

Computer Vision and Pattern Recognition · Computer Science 2017-12-04 Kai Fan , Qi Wei , Wenlin Wang , Amit Chakraborty , Katherine Heller

Quantum error correction is an essential ingredient for reliable quantum computation for theoretically provable quantum speedup. Topological color codes, one of the quantum error correction codes, have an advantage against the surface codes…

Quantum Physics · Physics 2024-02-02 Yugo Takada , Yusaku Takeuchi , Keisuke Fujii

Optomechanical systems combine extreme sensitivity and bandwidth in the control of mechanical motion, of interest for various applications. Integrated on a chip, actuated and detected all-optically by a single laser, they could disrupt…

Ising machines, which are dynamical systems designed to operate in a parallel and iterative manner, have emerged as a new paradigm for solving combinatorial optimization problems. Despite computational advantages, the quality of solutions…

Statistical Mechanics · Physics 2026-01-30 Shu Zhou , K. Y. Michael Wong , Juntao Wang , David Shui Wing Hui , Daniel Ebler , Jie Sun

We consider the distributed message-passing {LOCAL} model. In this model a communication network is represented by a graph where vertices host processors, and communication is performed over the edges. Computation proceeds in synchronous…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-05-01 Leonid Barenboim