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Machine learning offers a largely unexplored avenue for improving noisy disordered devices in physics using automated algorithms. Through simulations that include disorder in physical devices, particularly quantum devices, there is…

Disordered Systems and Neural Networks · Physics 2025-01-22 Jacob R. Taylor , Sankar Das Sarma

Brainwave signals are read through Electroencephalogram (EEG) devices. These signals are generated from an active brain based on brain activities and thoughts. The classification of brainwave signals is a challenging task due to its…

Signal Processing · Electrical Eng. & Systems 2020-02-18 Zhyar Rzgar K. Rostam , Sozan Abdullah Mahmood

This paper presents a neuromorphic system for cognitive load classification in a real-world setting, an Air Traffic Control (ATC) task, using a hardware implementation of Spiking Neural Networks (SNNs). Electroencephalogram (EEG) and…

Neural and Evolutionary Computing · Computer Science 2025-10-06 Jiahui An , Chonghao Cai , Olympia Gallou , Sara Irina Fabrikant , Giacomo Indiveri , Elisa Donati

The breathing-mode giant monopole resonance is studied within the framework of the relativistic mean-field (RMF) theory. Using a broad range of parameter sets, a systematic analysis of constrained incompressibility and excitation energy of…

Nuclear Theory · Physics 2009-10-28 M. V. Stoitsov , M. L. Cescato , P. Ring , M. M. Sharma

We present a variational Monte Carlo method that solves the nuclear many-body problem in the occupation number formalism exploiting an artificial neural network representation of the ground-state wave function. A memory-efficient version of…

We show that a simple artificial neural network trained on entanglement spectra of individual states of a many-body quantum system can be used to determine the transition between a many-body localized and a thermalizing regime.…

Disordered Systems and Neural Networks · Physics 2017-07-04 Frank Schindler , Nicolas Regnault , Titus Neupert

We give the easily recognizable name "cinnamon" and "cinnamon programming" to a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming paradigm…

Programming Languages · Computer Science 2017-10-18 Kostadin Kratchanov

In the present study, the capabilities of a new Convolutional Neural Network (CNN) model are explored with the paramount objective of reconstructing the temperature field of wall-bounded flows based on a limited set of measurement points…

Fluid Dynamics · Physics 2022-02-02 Victor Coppo Leite , Elia Merzari , Roberto Ponciroli , Lander Ibarra

Artificial neural networks have been recently introduced as a general ansatz to compactly represent many- body wave functions. In conjunction with Variational Monte Carlo, this ansatz has been applied to find Hamil- tonian ground states and…

Strongly Correlated Electrons · Physics 2018-10-24 Kenny Choo , Giuseppe Carleo , Nicolas Regnault , Titus Neupert

In a typical fusion experiment, the plasma can have several possible confinement modes. At the TCV tokamak, aside from the Low (L) and High (H) confinement modes, an additional mode, dithering (D), is frequently observed. Developing methods…

Plasma Physics · Physics 2021-05-26 Francisco Matos , Vlado Menkovski , Alessandro Pau , Gino Marceca , Frank Jenko

A new Quantum Monte-Carlo (QMC) approach is proposed to investigate low-lying states of nuclei within the shell model. The formalism relies on a variational symmetry-restored wave-function to guide the underlying Brownian motion. Sign/phase…

Nuclear Theory · Physics 2015-10-20 Jérémy Bonnard , Olivier Juillet

This study presents a novel transfer learning approach and data augmentation technique for mental stability classification using human voice signals and addresses the challenges associated with limited data availability. Convolutional…

Sound · Computer Science 2026-01-26 Rafiul Islam , Md. Taimur Ahad

A variational technique to describe the ground and scattering states below the break-up threshold for a three-nucleon system is developed. The method consists in expanding the wave function in terms of correlated Harmonic Hyperspherical…

Nuclear Theory · Physics 2009-10-30 A. Kievsky , M. Viviani , S. Rosati

Recently, quantum convolutional neural networks (QCNNs) are proposed, harnessing the power of quantum computing for faster training compared to the classical counterparts. However, this framework for deep learning also relies on multiple…

Quantum Physics · Physics 2024-12-12 Yifan Sun , Xiangdong Zhang

Discrete breathers (DBs) -- a spatial time-periodic localization of energy -- are predicted in a large variety of non-linear systems. Motivated by the conceptual bridging of the DBs phenomena in classical and quantum mechanical…

Quantum Physics · Physics 2011-12-26 Kirill Igumenshchev , Misha Ovchinnikov , Panagiotis Maniadis , Oleg Prezhdo

Computer Aided Diagnosis has emerged as an indispensible technique for validating the opinion of radiologists in CT interpretation. This paper presents a deep 3D Convolutional Neural Network (CNN) architecture for automated CT scan-based…

Image and Video Processing · Electrical Eng. & Systems 2019-06-05 Sumita Mishra , Naresh Kumar Chaudhary , Pallavi Asthana , Anil Kumar

A great deal of research work has been undertaken in alpha-clustering study since the pioneering discovery of 12C+12C molecular resonances half a century ago. Our knowledge on physics of nuclear molecules has increased considerably and…

Nuclear Experiment · Physics 2016-12-21 C. Beck

Three-body nuclear forces are essential for explaining the properties of light nuclei with a nucleon number greater than three. Building on insights from nuclear physics, we extract the form of quark three-body interactions and demonstrate…

High Energy Physics - Phenomenology · Physics 2024-08-02 Sungsik Noh , Aaron Park , Hyeongock Yun , Sungtae Cho , Su Houng Lee

Sleep apnea, a prevalent sleep disorder, involves repeated episodes of breathing interruptions during sleep, leading to various health complications, including cognitive impairments, high blood pressure, heart disease, stroke, and even…

Signal Processing · Electrical Eng. & Systems 2025-09-03 Chun Hin Siu , Hossein Miri

Computing the ground state of interacting quantum matter is a long-standing challenge, especially for complex two-dimensional systems. Recent developments have highlighted the potential of neural quantum states to solve the quantum…

Disordered Systems and Neural Networks · Physics 2025-07-03 Ao Chen , Markus Heyl