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

Anisotropic and isotropic elasticity and thermal transport in monolayer C$_{24}$ networks from machine-learning molecular dynamics

Qing Li, Haikuan Dong, Penghua Ying, Zheyong Fan ยท 2025

Two-dimensional fullerene networks have recently attracted increasing interest due to their diverse bonding topologies and mechanically robust architectures. In this work, we develop an accurate machiโ€ฆ

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Physics Preprint PDF DOI

An Interpretable Operator-Learning Model for Electric Field Profile Reconstruction in Discharges Based on the EFISH Method

Zhijian Yang, Edwin Setiadi Sugeng, Mhedine Alicherif, Tat Loon Chng ยท 2025

Machine learning (ML) models have recently been used to reconstruct electric field distributions from EFISH signal profiles-the 'inverse EFISH problem'. This addresses the line-of-sight EFISH inaccuraโ€ฆ

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Physics Preprint PDF DOI

Interpretable Graph Neural Networks for Classifying Structure and Magnetism in Delafossite Compounds

Jovin Ryan Joseph, Do Hoon Kiem, Sinchul Yeom, Mina Yoon ยท 2025

Delafossites (ABC2, where A and B are metals and C is a chalcogen) are a versatile family of quantum materials and layered oxides/chalcogenides whose properties are highly sensitive to atomic compositโ€ฆ

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Physics Preprint PDF DOI

Cross-Geometry Transfer Learning in Fast Electromagnetic Shower Simulation

Frank Gaede, Gregor Kasieczka, Lorenzo Valente ยท 2025

Accurate particle shower simulation remains a critical computational bottleneck for high-energy physics. Traditional Monte Carlo methods, such as Geant4, are computationally prohibitive, while existinโ€ฆ

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Physics Preprint PDF DOI

Random purification channel made simple

Filippo Girardi, Francesco Anna Mele, Ludovico Lami ยท 2025

The recently introduced random purification channel, which converts $n$ i.i.d. copies of any mixed quantum state into a uniform convex combination of $n$ i.i.d. copies of its purifications, has provedโ€ฆ

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Physics Preprint PDF DOI

Detection of the Pairwise Kinematic Sunyaev-Zel'dovich Effect and Pairwise Velocity with DESI DR1 Galaxies and ACT DR6 and Planck CMB Data

Yulin Gong, Patricio A. Gallardo, Rachel Bean, Jenna Moore, Eve M. Vavagiakis, Nicholas Battaglia, Boryana Hadzhiyska, Yun-Hsin Hsu, Jessica Nicole Aguilar, Steven Ahlen, Davide Bianchi, David Brooks, Todd Claybaugh, Rebecca Canning, Mark Devlin, Peter Doel, Axel de la Macorra, Simone Ferraro, Andreu Font-Ribera, Jaime E. Forero-Romero, Enrique Gaztanaga, Gaston Gutierrez, Satya Gontcho A Gontcho, Julien Guy, Klaus Honscheid, Cullan Howlett, R. Henry Liu, Mustapha Ishak, Dick Joyce, Anthony Kremin, Claire Lamman, Michael Levi, Martin Landriau, Marc Manera, Aaron Meisner, Ramon Miquel, Michael D. Niemack, Seshadri Nadathur, Will Percival, Francisco Prada, Graziano Rossi, Bernardita Ried Guachalla, Eusebio Sanchez, Hee-Jong Seo, David Sprayberry, David Schlegel, Cristobal Sifon, Michael Schubnell, Joseph Harry Silber, Gregory Tarle, Benjamin Alan Weaver, Rongpu Zhou, Hu Zou ยท 2025

We present a 9.3-sigma detection of the pairwise kinematic Sunyaev-Zeldovich (kSZ) effect by combining a sample of 913,286 Luminous Red Galaxies (LRGs) from the Dark Energy Spectroscopic Instrument Daโ€ฆ

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Physics Preprint PDF DOI

Bounded-Error Quantum Simulation via Hamiltonian and Lindbladian Learning

Tristan Kraft, Manoj K. Joshi, William Lam, Tobias Olsacher, Florian Kranzl, Johannes Franke, Lata Kh Joshi, Rainer Blatt, Augusto Smerzi, Daniel Stilck Franca, Benoit Vermersch, Barbara Kraus, Christian F. Roos, Peter Zoller ยท 2025

Analog Quantum Simulators offer a route to exploring strongly correlated many-body dynamics beyond classical computation, but their predictive power remains limited by the absence of quantitative erroโ€ฆ

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Physics Preprint PDF DOI

Identifying bars in galaxies using machine learning

Rajit Shrivastava ยท 2025

This thesis presents an innovative framework for the automated detection and characterization of galactic bars, pivotal structures in spiral galaxies, using the YOLO-OBB (You Only Look Once with Orienโ€ฆ

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First Steps towards Machine Learning for Prediction and Pre-Correction in Direct Laser Writing

Sven Enns, Julian Hering-Stratemeier, Georg von Freymann ยท 2025

Additive manufacturing using 2-Photon Polymerization (2PP, aka direct laser writing DLW) enables the fabrication of almost arbitrary complex 3D structures from the meso to the submicron scale. Howeverโ€ฆ

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A detection of sulfur-bearing cyclic hydrocarbons in space

Mitsunori Araki, Miguel Sanz-Novo, Christian P. Endres, Paola Caselli, Victor M. Rivilla, Izaskun Jimenez-Serra, Laura Colzi, Shaoshan Zeng, Andres Megias, Alvaro Lopez-Gallifa, Antonio Martinez-Henares, David San Andres, Sergio Martin, Miguel A. Requena-Torres, Juan Garcia de la Concepcion, Valerio Lattanzi ยท 2025

Molecules harbouring sulfur are thought to have played a key role in the biological processes of life on Earth, and thus, they are of much interest when found in space. Here we report on the astronomiโ€ฆ

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Statistical analysis and correction of the pile-up effect in MAPMT single photoelectron counting with the SPACIROC-3 ASIC: application to the Mini-EUSO experiment

Enzio M'sihid, Etienne Parizot, Matteo Battisti, Sylvie Blin (on behalf of the JEM-EUSO Collaboration) ยท 2025

We present a comprehensive study addressing pile-up effects in single photoelectron counting with R-11265 Hamamatsu multi-anode photomultiplier tubes (MAPMTs) equipped with the SPACIROC-3 ASIC. Extendโ€ฆ

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Physics Preprint PDF DOI

From Knots to Crystals: Machine-Learned Potentials for Self-Assembling Topological Solitons in Liquid Crystals

Arunkumar Bupathy, Darian Hall, Ivan I. Smalyukh, Gerardo Campos-Villalobos, Rodolfo Subert, Marjolein Dijkstra ยท 2025

Knotted fields in classical and quantum systems were long recognized for their non-trivial topologies and particle-like behavior, but practical applications have been limited by the difficulty of stabโ€ฆ

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Identifying genuine entanglement of lossy noisy very large scale continuous variable Greenberger-Horne-Zeilinger state

Xiao-yu Chen ยท 2025

Genuine entanglement identification of large scale systems is crucial for quantum computation, quantum communication and quantum learning advantage. In contrast to experiments, where noisy intermediatโ€ฆ

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SlotFlow: Amortized Trans-Dimensional Inference with Slot-Based Normalizing Flows

Niklas Houba, Giovanni Giarda, Lorenzo Speri ยท 2025

Inferring the number of distinct components contributing to an observation, while simultaneously estimating their parameters, remains a long-standing challenge across signal processing, astrophysics, โ€ฆ

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Nonstabilizerness Estimation using Graph Neural Networks

Vincenzo Lipardi, Domenica Dibenedetto, Georgios Stamoulis, Evert van Nieuwenburg, Mark H.M. Winands ยท 2025

This article proposes a Graph Neural Network (GNN) approach to estimate nonstabilizerness in quantum circuits, measured by the stabilizer R\'enyi entropy (SRE). Nonstabilizerness is a fundamental resoโ€ฆ

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Reservoir neuromorphic computing based on spin-orbit coupling in an organic crystal resonator

Teng Long, Yibo Deng, Xuekai Ma, Chunling Gu, Guillaume Malpuech, Qing Liao, Hongbing Fu, Dmitry Solnyshkov ยท 2025

Neuromorphic computing is at the basis of the recent progress in artificial intelligence. But the progress is accompanied with increasing demands in computational resources and power supply. Reservoirโ€ฆ

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Sulfur monoxide as a tracer of the Galactic $^{32}$S/$^{34}$S gradient

Yipeng Zou, Jiangshui Zhang, Dingyuan Wei, Yaoting Yan, Donatella Romano, Youxin Wang, Jialiang Chen, Hongzhi Yu, Jieyu Zhao ยท 2025

To date, the Galactic interstellar radial $^{32}$S/$^{34}$S gradient has only been studied with the CS isotopologs, which may be affected by uncertainties due to the use of a single tracer. As anotherโ€ฆ

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Blazar classification from multi-wavelength data using Deep Learning

Saqlain Afroz, Titir Mukherjee, Raj Prince ยท 2025

The Fermi Large Area Telescope (Fermi-LAT) has detected more than 7,000 gamma-ray sources, a significant fraction of which are identified as blazars, while a comparable number remain classified as blaโ€ฆ

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Physics Preprint PDF DOI

Rapid Determination of Nanodiamond Size Distribution and Impurity Concentration from Raman Spectra Using an Open Machine-Learning Toolbox

Sergei V. Koniakhin, Oleg I. Utesov, Vitaly I. Korepanov, Andrey G. Yashenkin ยท 2025

Ready-to-use numerical toolbox for nanodiamond Raman spectra calculation and fit is presented. The developed theoretical approach allows accounting for arbitrary nanoparticle size-distribution and theโ€ฆ

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Physics Preprint PDF DOI

MDcraft -- a modern molecular dynamics simulation package with machine learning potentials support

I. S. Galtsov, R. V. Muratov, G. V. Vyskvarko, S. A. Murzov, S. A. Dyachkov, P. R. Levashov ยท 2025

Molecular dynamics is widely used to study various phenomena, such as diffusion, shock wave propagation, and plasma dynamics. A wide range of software packages supports the expanding scope of moleculaโ€ฆ

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