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Solving coupled systems of differential equations (DEs) is a central problem across scientific computing. While Physics Informed Neural Networks (PINNs) offer a promising, mesh-free approach, their standard architectures struggle with the…

Quantum Physics · Physics 2026-02-17 Zhao-Wei Wang , Zhao-Ming Wang

Surface integral equation (SIE) methods are of great interest for the efficient electromagnetic modeling of various devices, from integrated circuits to antenna arrays. Existing acceleration algorithms for SIEs, such as the adaptive…

Computational Engineering, Finance, and Science · Computer Science 2021-07-13 Shashwat Sharma , Piero Triverio

A network of optical parametric oscillators is used to simulate classical Ising and XY spin chains. The collective nonlinear dynamics of this network, driven by quantum noise rather than thermal fluctuations, seeks out the Ising / XY ground…

This work presents two novel optimization methods based on integer linear programming (ILP) that minimize the number of adders used to implement a direct/transposed finite impulse response (FIR) filter adhering to a given frequency…

Signal Processing · Electrical Eng. & Systems 2019-12-10 Martin Kumm , Anastasia Volkova , Silviu-Ioan Filip

We develop improved physics-informed neural networks (PINNs) for high-order and high-dimensional power system models described by nonlinear ordinary differential equations. We propose some novel enhancements to improve PINN training and…

Machine Learning · Computer Science 2024-10-11 Vineet Jagadeesan Nair

To make a good balance between performance, cost, and power consumption, a hybrid intelligent reflecting surface (IRS)-aided directional modulation (DM) network is investigated in this paper, where the hybrid IRS consists of passive and…

Information Theory · Computer Science 2023-02-15 Rongen Dong , Hangjia He , Feng Shu , Riqing Chen , Jiangzhou Wang

Stochastic Ising machines, sIMs, are highly promising accelerators for optimization and sampling of computational problems that can be formulated as an Ising model. Here we investigate the computational advantage of sIM for simulations of…

Quantum Physics · Physics 2026-03-06 Rutger J. L. F. Berns , Davi R. Rodrigues , Giovanni Finocchio , Johan H. Mentink

Large Language Models (LLMs) have become essential in a variety of applications due to their advanced language understanding and generation capabilities. However, their computational and memory requirements pose significant challenges to…

Hardware Architecture · Computer Science 2024-12-02 Cristobal Ortega , Yann Falevoz , Renaud Ayrignac

Wave-based data processing by spin waves and their quanta, magnons, is a promising technique to overcome the challenges which CMOS-based logic networks are facing nowadays. The advantage of these quasi-particles lies in their potential for…

We present an application of Physics-Informed Neural Networks to handle MultiPhase-Field simulations of microstructure evolution. It has been showcased that a combination of optimization techniques extended and adapted from the PINNs…

Materials Science · Physics 2024-09-04 Seifallah Elfetni , Reza Darvishi Kamachali

A new carrier-based pulse-width modulation (PWM) technique to control power inverters is presented in this paper. To generate the output waveform, this technique compares a harmonic-injection modulating wave and a frequency-modulated…

We compare the Frequency-Resolved Frozen Phonon Multislice (FRFPMS) method, introduced in Phys. Rev. Lett. 124, 025501 (2020), with other theoretical approaches used to account for the inelastic scattering of high energy electrons, namely…

Materials Science · Physics 2023-04-27 Paul M. Zeiger , Juri Barthel , Leslie J. Allen , Ján Rusz

A non-equilibrium open-dissipative neural network, such as a coherent Ising machine based on mutually coupled optical parametric oscillators, has been proposed and demonstrated as a novel computing machine for hard combinatorial…

We contribute to the mathematical theory of the design of low temperature Ising machines, a type of experimental probabilistic computing device implementing the Ising model. Encoding the output of a function in the ground state of a…

Emerging Technologies · Computer Science 2025-07-18 Andrew G. Moore , Zachary Richey , Isaac K. Martin

The phase-locked loop (PLL) used in the doubly fed induction generator (DFIG) can cause frequency coupling phenomena, which will give negative resistance characteristics ofthe DFIG at low frequency, resulting in stability issues under weak…

Systems and Control · Electrical Eng. & Systems 2023-07-20 Xiaoling Xiong , Bochen Luo , Longcan Li , Ziming Sun , Frede Blaabjerg

The plane wave method is most widely used for solving the Kohn-Sham equations in first-principles materials science computations. In this procedure, the three-dimensional (3-dim) trial wave functions' fast Fourier transform (FFT) is a…

Computational Physics · Physics 2018-01-17 Xingyu Gao , Zeyao Mo , Jun Fang , Han Wang

Hybrid precoding has been recently proposed as a cost-effective transceiver solution for millimeter wave (mm-wave) systems. The analog component in such precoders, which is composed of a phase shifter network, is the key differentiating…

Information Theory · Computer Science 2017-07-27 Xianghao Yu , Jun Zhang , Khaled B. Letaief

A flexible intelligent metasurface (FIM) is composed of an array of low-cost radiating elements, each of which can independently radiate electromagnetic signals and flexibly adjust its position through a 3D surface-morphing process. In our…

Information Theory · Computer Science 2025-02-25 Jiancheng An , Chau Yuen , Marco Di Renzo , Mérouane Debbah , H. Vincent Poor , Lajos Hanzo

Index modulation (IM) has recently emerged as a promising concept for spectrum and energy-efficient next generation wireless communications systems since it strikes a good balance among error performance, complexity, and spectral…

Signal Processing · Electrical Eng. & Systems 2018-04-18 Adnan Zafar , Aijun Cao , Mahmoud Abdullahi , Lei Zhang , Pei Xiao , Muhammad Ali Imran

The Ising chain realizes the fundamental paradigm of spin fractionalization, where locally flipping a spin creates two domain walls (spinons) that can separate apart at no energy cost. In a quasi-one-dimensional system, the mean-field…

Strongly Correlated Electrons · Physics 2023-11-21 Leonie Woodland , David Macdougal , Ivelisse M. Cabrera , Jordan D. Thompson , D. Prabhakaran , Robert I. Bewley , Radu Coldea