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

Monitoring of Continuous-Wave Hardware Injections in LIGO Interferometers during the O4 Observing Run

Preet Baxi, Jessica Leviton, Eilam Morag, Matthew Pitkin, Keith Riles ยท 2026

Although there have now been hundreds of transient gravitational-wave detections of merging compact stars by the LIGO-Virgo-KAGRA (LVK) detector network, no continuous-wave (CW) signals have yet been โ€ฆ

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Physics Preprint PDF DOI

Using 23 Years of ACS/SBC Data to Understand Backgrounds: Explaining & Predicting Background Variations

Christopher J. R. Clark, Roberto J. Avila, Alyssa Guzman, Norman A. Grogin ยท 2026

Recent analysis of 23 years of Hubble Space Telescope ACS/SBC data has shown that background levels can vary considerably between observations, with most filters showing over an order of magnitude varโ€ฆ

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Machine-learning enabled characterization of individual ring resonators in integrated photonic lattices

Elizabeth Louis Pereira, Amin Hashemi, Faluke Aikebaier, Hongwei Li, Jose L. Lado, Andrea Blanco-Redondo ยท 2026

Accurately determining the underlying physical parameters of individual elements in integrated photonics is increasingly difficult as device architectures become more complex. Inferring these parameteโ€ฆ

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Efficient State Preparation for Quantum Machine Learning

Chris Nakhl, Maxwell West, Muhammad Usman ยท 2026

One of the key considerations in the development of Quantum Machine Learning (QML) protocols is the encoding of classical data onto a quantum device. In this chapter we introduce the Matrix Product Stโ€ฆ

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Field report from Collaborative Research Center 1625: Heterogeneous research data management using ontology representations

Doaa Mohamed, Samuel Garcia Vazquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker ยท 2026

The goal of the Collaborative Research Center 1625 is the establishment of a scientific basis for the atomic-scale understanding and design of multifunctional compositionally complex solid solution suโ€ฆ

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Sub-Leading Logarithms for Scalar Potential Models on de Sitter

S. P. Miao (NCKU), N. C. Tsamis (U Crete), R. P. Woodard (U Florida) ยท 2026

The continual production of long wavelength scalars and gravitons during inflation injects secular growth into loop corrections which would be constant in flat space. One typically finds that each addโ€ฆ

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Progressive Mixture-of-Experts with autoencoder routing for continual RANS turbulence modelling

Haoyu Ji, Yinhang Luo, Hanyu Zhou, Yaomin Zhao ยท 2026

Developing Reynolds-averaged Navier-Stokes (RANS) turbulence models that remain accurate across diverse flow regimes remains a long-standing challenge. In this work, we propose a novel framework, termโ€ฆ

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Representative-volume sizing in finite cylindrical computed tomography by low-wavenumber spectral convergence

Fernando Alonso-Marroquin, Abdullah Alqubalee, Christian Tantardini ยท 2026

Choosing a representative element volume (REV) from finite cylindrical Computed Tomography (CT) scans becomes ambiguous when a key field variable exhibits a slow axial trend, reflecting either geologiโ€ฆ

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Data-Driven Exploration and Insights into Temperature-Dependent Phonons in Inorganic Materials

Huiju Lee, Zhi Li, Jiangang he, Yi Xia ยท 2026

Phonons, quantized vibrations of the atomic lattice, are fundamental to understanding thermal transport, structural stability, and phase behavior in crystalline solids. Despite advances in computationโ€ฆ

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A saturation-absorption rubidium magnetometer with multilevel optical Bloch-equation modeling for intermediate-to-high fields

Mayand Dangi, Prateek Rajan Gupta, Joseph Kasti, Nivedan Vishwanath, Michael Zepp, David Smith, Benedikt Geiger, Jennifer T. Choy ยท 2026

We present SASHMAG (Saturated Absorption Spectroscopy High-field MAGnetometer), an atomic sensor designed for precision magnetic-field measurements in the intermediate-to-high field regime ($>0.2\,\teโ€ฆ

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Heavy Neutrinos across the Electroweak-to-Multi-TeV Frontier via Novel ML-Enhanced Probes

Yin-Fa Shen, Alfredo Gurrola, Francesco Romeo, Denis Rathjens, Andres Florez ยท 2026

We propose a new strategy to probe heavy neutrinos with non-universal fermion couplings at the Large Hadron Collider (LHC) using a novel production mechanism and machine-learning algorithms. Focusing โ€ฆ

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The Progenitor of the Type II-Plateau SN 2025pht in NGC 1637: The Dustiest, Most Luminous Red Supergiant So Far?

Schuyler D. Van Dyk, Tamas Szalai, Gagandeep S. Anand, Thomas G. Brink, Noah Zimmer, Dan Milisavljevic, Ori D. Fox, Jacob E. Jencson, WeiKang Zheng, Alexei V. Filippenko ยท 2026

We provide a characterization of the red supergiant (RSG) progenitor candidate for the nearby Type II-plateau supernova (SN) 2025pht in NGC 1637. The star was first detectable in 2001 by the Hubble Spโ€ฆ

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Learning Volterra Kernels for Non-Markovian Open Quantum Systems

Jimmie Adriazola, Katarzyna Roszak ยท 2026

We develop a data-driven framework for identifying non-Markovian dynamical equations of motion for open quantum systems. Starting from the Nakajima--Zwanzig formalism, we vectorize the reduced densityโ€ฆ

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Agentic AI and Machine Learning for Accelerated Materials Discovery and Applications

Jihua Chen, Panagiotis Christakopoulos, Karuna D. Chen, Ilia N. Ivanov, Rigoberto Advincula ยท 2026

Artificial Intelligence (AI), especially AI agents, is increasingly being applied to chemistry, healthcare, and manufacturing to enhance productivity. In this review, we discuss the progress of AI andโ€ฆ

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Machine Learning-Driven Creep Law Discovery Across Alloy Compositional Space

Hongshun Chen, Ryan Zhou, Rujing Zha, Zihan Chen, Wenpan Li, Rowan Rolark, John Patrick Reidy, Jian Cao, Ping Guo, David C. Dunand, Horacio D. Espinosa ยท 2026

Hihg-temperature creep characterization of structural alloys traditionally relies on serial uniaxial tests, which are highly inefficient for exploring the large search space of alloy compositions and โ€ฆ

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Measuring the Vertical Structure of Active Galactic Nuclei Disks with Transformer Models and the Vera C. Rubin Observatory

Amy Secunda, Sebastian Wagner-Carena, Helen Qu, Shirley Ho ยท 2026

Reverberation mapping is one of the main techniques used to study active galactic nuclei (AGN) accretion disks. Traditional continuum reverberation mapping uses short lags between variability in diffeโ€ฆ

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Towards a Self-Driving Trigger at the LHC: Adaptive Response in Real Time

Shaghayegh Emami, Cecilia Tosciri, Giovanna Salvi, Zixin Ding, Yuxin Chen, Abhijith Gandrakota, Christian Herwig, David W. Miller, Jennifer Ngadiuba, Nhan Tran ยท 2026

Real-time data filtering and selection -- or trigger -- systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider (LHC) must process extremely high-rate datโ€ฆ

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An Optimal Observable Machine for reinterpretable measurements in high-energy physics

Torben Mohr, Alejandro Quiroga Trivino, Fabian Riemer, Artur Monsch, Matteo Defranchis, Joscha Knolle, Ankita Mehta, Jan Kieseler, Markus Klute ยท 2026

A machine-learning-based framework for constructing generator-level observables optimized for parameter extraction in particle physics analyses is introduced, referred to as the Optimal Observable Macโ€ฆ

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Kernel Learning for Regression via Quantum Annealing Based Spectral Sampling

Yasushi Hasegawa, Masayuki Ohzeki ยท 2026

While quantum annealing (QA) has been developed for combinatorial optimization, practical QA devices operate at finite temperature and under noise, and their outputs can be regarded as stochastic sampโ€ฆ

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Blind Deconvolution in Astronomy: How Does a Standalone U-Net Perform?

Jean-Eric Campagne ยท 2026

Aims: This study investigates whether a U-Net architecture can perform standalone end-to-end blind deconvolution of astronomical images without any prior knowledge of the Point Spread Function (PSF) oโ€ฆ

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