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Binary neural networks, i.e., neural networks whose parameters and activations are constrained to only two possible values, offer a compelling avenue for the deployment of deep learning models on energy- and memory-limited devices. However,…

Networks of coupled resonators are an ubiquitous concept in physics, forming the basis of synchronization phenomena, metamaterial formation, nonreciprocal behavior and topological effects. Such systems are typically explored using optical…

Mesoscale and Nanoscale Physics · Physics 2019-12-03 Juliane Doster , Simon Hoenl , Heribert Lorenz , Philipp Paulitschke , Eva M. Weig

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

The S-parameter $S_{21}$ is widely used to characterize the resonant properties of various systems. However, we demonstrates that the reliability of $S_{21}$ as a true indicator of system resonances depends heavily on the specific probing…

Mesoscale and Nanoscale Physics · Physics 2025-05-21 Jiongjie Wang , Jiang Xiao

We study a classical $\Lambda$-type three-level system based on three high-$Q$ micromechanical beam resonators embedded in a gradient electric field. By modulating the strength of the field at the difference frequency between adjacent beam…

The notion of "paired" fermions is central to important condensed matter phenomena such as superconductivity and superfluidity. While the concept is widely used and its physical meaning is clear there exists no systematic and mathematical…

Quantum Physics · Physics 2009-11-13 Christina V. Kraus , Michael M. Wolf , J. Ignacio Cirac , Geza Giedke

We study a simple model of a two-dimensional s-wave superconductor in the presence of a random potential in the regime of large disorder. We first use the Bogoliubov-de Gennes (BdG) approach to show that, with increasing disorder the…

Disordered Systems and Neural Networks · Physics 2013-05-29 Amit Ghosal , Mohit Randeria , Nandini Trivedi

Recent years have seen significant advances in quantum/quantum-inspired technologies capable of approximately searching for the ground state of Ising spin Hamiltonians. The promise of leveraging such technologies to accelerate the solution…

Optimization and Control · Mathematics 2024-01-24 Robin Brown , David E. Bernal Neira , Davide Venturelli , Marco Pavone

The ubiquity of parametric resonance is continually evident in the repeated experimental observations of this phenomenon in multiple physical systems. The elementary case of 2 mode parametric resonance of order 1 involves the excitation of…

Classical Physics · Physics 2017-08-08 Adarsh Ganesan , Cuong Do , Ashwin Seshia

Nonlinear effects in microresonators are efficient building blocks for all-optical computing and telecom systems. With the latest advances in microfabrication, coupled microresonators are used in a rapidly growing number of applications. In…

Recent research on deep neural networks (DNNs) has primarily focused on improving the model accuracy. Given a proper deep learning framework, it is generally possible to increase the depth or layer width to achieve a higher level of…

Computer Vision and Pattern Recognition · Computer Science 2020-11-04 Litao Yu , Yongsheng Gao , Jun Zhou , Jian Zhang

A new functional model for pairs of commuting isometries is described. Intertwining operators between such models are then studied in order to approach the classification of invariant subspaces of such pairs.

Spectral Theory · Mathematics 2008-05-27 H. Bercovici , R. G. Douglas , C. Foias

The nonlinear, parametric coupling between two harmonic oscillators has been used in the field of optomechanics for breakthrough experiments regarding the control and detection of mechanical resonators. Although this type of interaction is…

Quantum Physics · Physics 2022-12-08 D. Bothner , I. C. Rodrigues , G. A. Steele

Optical Ising machines promise to solve complex optimization problems with an optical hardware acceleration advantage. Here we study the ground state properties of a nonlinear optical Ising machine realized by spatial light modulator,…

Optics · Physics 2023-02-20 Santosh Kumar , Zhaotong Li , Ting Bu , Chunlei Qu , Yuping Huang

We compute numerically the second and third order nonlinear magnetic susceptibilities of an Ising ladder model in the context of two-dimensional coherent spectroscopy by using the infinite time-evolving block decimation method. The Ising…

Strongly Correlated Electrons · Physics 2023-04-26 Qi Gao , Yang Liu , Haijun Liao , Yuan Wan

The last couple of years have seen an ever-increasing interest in using different Ising solvers, like Quantum annealers, Coherent Ising machines, and Oscillator-based Ising machines, for solving tough computational problems in various…

Emerging Technologies · Computer Science 2024-04-09 Abhishek Kumar Singh , Kyle Jamieson

Identifying the pairing symmetry in unconventional superconductors is essential for reliably characterizing their superconducting states and for enabling their integration into realistic quantum devices. Here, we introduce a…

Superconductivity · Physics 2026-02-24 Adam Hložný , Jozef Haniš , Martin Gmitra , Marko Milivojević

Ising machines -- special-purpose hardware for heuristically solving Ising optimization problems -- based on probabilistic bits (p-bits) have been established as a promising alternative to heuristic optimization algorithms run on…

We investigate second-order nonlinear processes in a system of two coupled identical optical micro-resonators. The double resonance and phase-matching conditions are simultaneously obtained thanks to the frequency splitting induced by the…

Optics · Physics 2025-10-03 Yannick Dumeige , Yoan Léger

The Ising model is of prime importance in the field of statistical mechanics. Here we show that Ising-type interactions can be realized in periodically-driven circuits of stochastic binary resistors with memory. A key feature of our…

Mesoscale and Nanoscale Physics · Physics 2023-10-03 V. J. Dowling , Y. V. Pershin
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