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๐Ÿ” avoidance learning ๐Ÿ“‚ Physics
Showing 28154 results for "avoidance learning" in Physics
Physics Preprint PDF DOI

Type II and Type III Solar Radio Burst Classification Using Transfer Learning

Herman le Roux, Ruhann Steyn, Du Toit Strauss, Mark Daly, Peter T. Gallagher, Jeremiah Scully, Shane A. Maloney, Christian Monstein, Gunther Drevin ยท 2025

The Sun periodically emits intense bursts of radio emission known as solar radio bursts (SRBs). These bursts can disrupt radio communications and be indicative of large solar events that can disrupt tโ€ฆ

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Physics Preprint PDF DOI

Flow Gym: A framework for the development, benchmarking, training, and deployment of flow-field quantification methods

Francesco Banelli, Antonio Terpin, Alan Bonomi, Raffaello D'Andrea ยท 2025

Particle image velocimetry (PIV) and related optical-flow methods are widely used to quantify fluid motion, but their development and evaluation are often hindered by fragmented software, inconsistentโ€ฆ

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Physics Preprint PDF DOI

Probing Vector-Like Quarks at a future Muon-Proton Collider

Mudassar Hussain, Ijaz Ahmed, Tayyab Javaid, Haroon Saghir, Jamil Muhammad ยท 2025

This study investigates the discovery potential of a singly produced vector-like top quark ($T$) at a future muon-proton collider with center-of-mass energies of 5.29, 6.48, and 9.16 TeV, using a modeโ€ฆ

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Physics Preprint PDF DOI

Emergence of Nonequilibrium Latent Cycles in Unsupervised Generative Modeling

Marco Baiesi, Alberto Rosso ยท 2025

We show that nonequilibrium dynamics can play a constructive role in unsupervised machine learning by inducing the spontaneous emergence of latent-state cycles. We introduce a model in which visible aโ€ฆ

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Physics Preprint PDF DOI

Computing quantum entanglement with machine learning

Andrea Bulgarelli, Elia Cellini, Karl Jansen, Stefan Kuhn, Alessandro Nada, Shinichi Nakajima, Kim A. Nicoli, Marco Panero ยท 2025

Entanglement calculations in quantum field theories are extremely challenging and typically rely on the replica trick, where the problem is rephrased in a study of defects. We demonstrate that the useโ€ฆ

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Maritime object classification with SAR imagery using quantum kernel methods

John Tanner, Nicholas Davies, Pascal Jahan Elahi, Casey R. Myers, Du Huynh, Wei Liu, Mark Reynolds, Jingbo Wang ยท 2025

Illegal, unreported, and unregulated (IUU) fishing causes global economic losses of 10-25 billion USD annually and undermines marine sustainability and governance. Synthetic Aperture Radar (SAR) proviโ€ฆ

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Physics Preprint PDF DOI

Deep Learning-Based Quantum Transport Simulations in Two-Dimensional Materials

Jijie Zou, Zhanghao Zhouyin, Qiangqiang Gu, Shishir Kumar Pandey ยท 2025

Two-dimensional (2D) materials exhibit a wide range of electronic properties that make them promising candidates for next-generation nanoelectronic devices. Accurate prediction of their quantum transpโ€ฆ

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Physics Preprint PDF DOI

Free Energy Sources of Ion-scale Waves Observed by Parker Solar Probe

Niranjana Shankarappa, Kristopher G. Klein, Mihailo M. Martinovic, Trevor A. Bowen, Davin E. Larson, Roberto Livi, Ali Rahmati, Phyllis L. Whittlesey, Michael L. Stevens ยท 2025

Parker Solar Probe (PSP) observes abundant circularly polarized ion-scale waves throughout the inner heliosphere. These waves are a signature of the interplay between plasma microinstabilities and turโ€ฆ

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Classifying High-Energy Celestial Objects with Machine Learning Methods

Alexis Mathis, Daniel Yu, Nolan Faught, Tyrian Hobbs. (Northeastern University) ยท 2025

Machine learning is a field that has been growing in importance since the early 2010s due to the increasing accuracy of classification models and hardware advances that have enabled faster training onโ€ฆ

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Noisy Quantum Learning Theory

Jordan Cotler, Weiyuan Gong, Ishaan Kannan ยท 2025

We develop a framework for learning from noisy quantum experiments in which fault-tolerant devices access uncharacterized systems through noisy couplings. Introducing the complexity class $\textsf{NBQโ€ฆ

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Hermitian Yang--Mills connections on general vector bundles: geometry and physical Yukawa couplings

Challenger Mishra, Justin Tan ยท 2025

We compute solutions to the Hermitian Yang-Mills equations on holomorphic vector bundles $V$ via an alternating optimisation procedure founded on geometric machine learning. The proposed method is fulโ€ฆ

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Generative Adversarial Variational Quantum Kolmogorov-Arnold Network

Hikaru Wakaura ยท 2025

Kolmogorov Arnold Networks is a novel multilayer neuromorphic network that can exhibit higher accuracy than a neural network. It can learn and predict more accurately than neural networks with a smallโ€ฆ

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Quantum Approaches to Urban Logistics: From Core QAOA to Clustered Scalability

F. Picariello, G. Turati, R. Antonelli, I. Bailo, S. Bonura, G. Ciarfaglia, S. Cipolla, P. Cremonesi, M. Ferrari Dacrema, M. Gabusi, I. Gentile, V. Morreale, A. Noto ยท 2025

The Traveling Salesman Problem (TSP) is a fundamental challenge in combinatorial optimization, widely applied in logistics and transportation. As the size of TSP instances grows, traditional algorithmโ€ฆ

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Ultrahigh-Q chiral resonances empowered by multi-head attention deep learning

Cong Zhang, Jiaju Wu, Huazheng Wu, Yufei Liu, Xu Yang, Na Liu, Chaoyang Wang, Peipei Chen, Chenggang Yan, Seng Yang, Xingguang Liu, Shaowei Jiang ยท 2025

High quality (Q) factor optical chiral resonators are indispensable for many chiral photonic devices. Designing ultrahigh Q-factors in chiral metasurfaces traditionally relies on extensive parameter sโ€ฆ

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Pulsed learning for quantum data re-uploading models

Ignacio B. Acedo, Pablo Rodriguez-Grasa, Pablo Garcia-Azorin, Javier Gonzalez-Conde ยท 2025

While Quantum Machine Learning (QML) holds great potential, its practical realization on Noisy Intermediate-Scale Quantum (NISQ) hardware has been hindered by the limitations of variational quantum ciโ€ฆ

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Subtracting compact binary foregrounds utilizing anisotropic statistic for third-generation gravitational-wave detectors

Soichiro Kuwahara, Atsushi Nishizawa, Lorenzo Valbusa Dall'Armi ยท 2025

The astrophysical foreground from compact-binary coalescence signals is expected to be a dominant part of total gravitational wave (GW) energy density in the frequency band of the third-generation detโ€ฆ

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Field Reconstruction for High-Frequency Electromagnetic Exposure Assessment Based on Deep Learning

Miao Cao, Zicheng Liu, Bazargul Matkerim, Tongning Wu, Changyou Li, Yali Zong, Bo Qi ยท 2025

Fifth-generation (5G) communication systems, operating in higher frequency bands from 3 to 300 GHz, provide unprecedented bandwidth to enable ultra-high data rates and low-latency services. However, tโ€ฆ

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Thermal and Size Effects in Ferroelastic Domains by Machine Learning

Luka Geddis Zellmann, Sumner B. Harris, John R. R. Scott, Yi-Chieh Yang, Joerg Jinschek, Rama Vasudevan, Miryam Arredondo ยท 2025

Ferroelastic domain walls (DWs) underpin key functionalities in complex oxides. In free-standing ferroic thin films, where elastic interactions are highly thickness dependent, understanding DW behavioโ€ฆ

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Deep Photonic Reservoir Computing with On-chip Nonlinearity

Jinlong Xiang, Youlve Chen, Yuchen Yin, Zhenyu Zhao, Chaojun Xu, An He, Xintong Lv, Yikai Su, Xuhan Guo ยท 2025

Reservoir computing, renowned for its low training cost, has emerged as a promising lightweight paradigm for efficient spatiotemporal processing,it remains challenging to realize deep photonic reservoโ€ฆ

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Optimal Distributed Similarity Estimation of Quantum Channels

Congcong Zheng, Kun Wang, Xutao Yu, Ping Xu, Zaichen Zhang ยท 2025

We study distributed similarity estimation of quantum channels (DSEC), a primitive for cross-platform verification where two remote quantum devices are compared by estimating the inner product of theiโ€ฆ

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