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

Photon Dynamics and Collision Risks in Relativistic Spaceflight: A Comparative Study of Methods and Implications

Li Kai Wen, Joao Rodrigues ยท 2025

This dissertation explores the dynamics of relativistic spaceflight, focusing on the risks associated with collisions and photon interactions as a spacecraft approaches velocities near the speed of liโ€ฆ

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Linearly-scalable and entropy-optimal learning of nonstationary and nonlinear manifolds

Illia Horenko ยท 2025

We propose an Entropy-Optimal Manifold Clustering (EOMC) - and show that it mitigates the cost scaling and robustness issues of the existing dimensionality reduction and manifold learning tools in nonโ€ฆ

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Photonic Quantum-Accelerated Machine Learning

Markus Rambach, Abhishek Roy, Alexei Gilchrist, Akitada Sakurai, William J. Munro, Kae Nemoto, Andrew G. White ยท 2025

Machine learning is widely applied in modern society, but has yet to capitalise on the unique benefits offered by quantum resources. Boson sampling -- a quantum-interference based sampling protocol --โ€ฆ

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Machine learning classification of baseband data of CHIME FRBs

Mohanraj Madheshwaran, Tetsuya Hashimoto, Tomotsugu Goto, William J. Pearson, Murthadza Aznam, Simon C.-C. Ho, Vignesh V.V. Rao, Sridhar Gajendran ยท 2025

Fast Radio Bursts (FRBs) are bright millisecond radio pulses. Their origin is still unknown in the field of astronomy. A notable distinction among FRBs is that some sources repeat, while others appearโ€ฆ

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Magnetic activity of ultracool dwarfs in the LAMOST DR11

Yue Xiang, Shenghong Gu, Dongtao Cao ยท 2025

Ultracool dwarfs consist of lowest-mass stars and brown dwarfs. Their interior is fully convective, different from that of the partly-convective Sun-like stars. Magnetic field generation process beneaโ€ฆ

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Leading-twist gluon transverse momentum dependent distributions from large-momentum effective theory

Xiupeng Xie, Zhun Lu ยท 2025

We present the perturbative calculation of the leading-twist gluon transverse momentum dependent distribution functions (TMDPDFs) at one-loop level within large-momentum effective theory. By employingโ€ฆ

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The Milky Way Imaging Scroll Painting Survey: Data Release 1

Ji Yang, Qing-Zeng Yan, Yang Su, Shaobo Zhang, Xin Zhou, Yan Sun, Yiping Ao, Xuepeng Chen, Zhiwei Chen, Fujun Du, Min Fang, Yan Gong, Zhibo Jiang, Shengyu Jin, Binggang Ju, Chong Li, Yingjie Li, Yi Liu, Dengrong Lu, Chunsheng Luo, Yuehui Ma, Ruiqing Mao, Jixian Sun, Chen Wang, Hongchi Wang, Min Wang, Min Wang (Qinghai), Xindong Wang, Wenting Xu, Ye Xu, Kun Yan, Ping Yan, Lixia Yuan, Miaomiao Zhang, Yongxing Zhang ยท 2025

We present the first data release (DR1) of the Milky Way Imaging Scroll Painting (MWISP) survey, a mapping in the J=(1-0) transition lines of 12CO, 13CO, and C18O toward the northern Galactic plane duโ€ฆ

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Large-scale Lindblad learning from time-series data

Ewout van den Berg, Brad Mitchell, Ken Xuan Wei, Moein Malekakhlagh ยท 2025

In this work, we develop a protocol for learning a time-independent Lindblad model for operations that can be applied repeatedly on a quantum computer. The protocol is highly scalable for models with โ€ฆ

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Advantages of Broadband Metalenses for Generalizable Image Classification

Yubo Zhang, Johannes Froch, Jinlin Xiang, Shane Colburn, Myunghoo Lee, Zhihao Zhou, Minho Choi, Eli Shlizerman, Arka Majumdar ยท 2025

Optical neural networks (ONNs) are gaining increasing attention to accelerate machine learning tasks. In particular, static meta-optical encoders designed for task-specific pre-processing have demonstโ€ฆ

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The Two-Infall Model Revisited: Constraints on Milky Way Bulge Assembly from >30,000 Galactic Chemical Evolution Models and Machine Learning

Niall Miller, Meridith Joyce, Christian I. Johnson, Jamie Tayar, Thomas Trueman, R Michael Rich ยท 2025

We constrain the formation history of the Milky Way bulge using a two-infall Galactic Chemical Evolution (GCE) framework implemented in the OMEGA++ code. We recover a best-fit scenario in which the buโ€ฆ

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Predicting interstitial elements in Refractory Complex Concentrated Alloys

Aomin Huang, Siya Zhu, Calvin Belcher, Ryker Rigsby, Diran Apelian, Raymundo Arroyave, Enrique J. Lavernia ยท 2025

Refractory complex concentrated alloys, composed of multiple principal refractory elements, are promising candidates for high-temperature structural applications due to their exceptional thermal stabiโ€ฆ

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F2: Offline Reinforcement Learning for Hamiltonian Simulation via Free-Fermionic Subroutine Compilation

Ethan Decker, Christopher Watson, Junyu Zhou, Yuhao Liu, Chenxu Liu, Ang Li, Gushu Li, Samuel Stein ยท 2025

Compiling shallow and accurate quantum circuits for Hamiltonian simulation remains challenging due to hardware constraints and the combinatorial complexity of minimizing gate count and circuit depth. โ€ฆ

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Danger Zone: Establishing Buffers for Enhanced Classification in BPT Diagrams

Changhyun Cho, Ahmad Nemer, Ivan Yu. Katkov, Joseph D. Gelfand ยท 2025

This study utilizes unsupervised machine learning, specifically the uniform manifold approximation and projection (UMAP) algorithm, to classify optical spectra originating from star-forming regions, Sโ€ฆ

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Complete next-to-next-to-leading order QCD corrections to the decay matrix in $\boldsymbol{B}$-meson mixing at leading power

Ulrich Nierste, Pascal Reeck, Vladyslav Shtabovenko, Matthias Steinhauser ยท 2025

We compute next-to-next-to-leading order corrections to the decay width difference of mass eigenstates and the charge-parity (CP) asymmetry $a_{\rm fs}$ in flavour-specific decays of neutral $B$ mesonโ€ฆ

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Novel thermodynamic inequality for rotating AdS black holes

Hamid R. Bakhtiarizadeh ยท 2025

We propose a new thermodynamic inequality for stationary and asymptotically Anti-de Sitter rotating black holes, $ 4\pi J^2/(3MV)<1 $. This inequality is derived by analyzing the roots of the identityโ€ฆ

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Trapped Fermions Through Kolmogorov-Arnold Wavefunctions

Paulo F. Bedaque, Jacob Cigliano, Hersh Kumar, Srijit Paul, Suryansh Rajawat ยท 2025

We investigate a variational Monte Carlo framework for trapped one-dimensional mixture of spin-$\frac{1}{2}$ fermions using Kolmogorov-Arnold networks (KANs) to construct universal neural-network waveโ€ฆ

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Hot, Photoionized X-ray Gas in Two Luminous Type 2 Quasars: Chandra-HST Evidence for a Wind-Driven Sequence

Anna Trindade Falcao, S. Kraemer, L. Feuillet, R. Middei, T. J. Turner, J. Reeves, V. Braito, A. Ptak, H. R. Schmitt, T. C. Fischer, D. M. Crenshaw, Luis C. Ho, M. Revalski, T. Storchi-Bergmann, M. Vestergaard, C. M. Gaskell, W. P. Maksym, M. Elvis, M. J. Ward, H. Netzer ยท 2025

We present new Chandra/ACIS-S imaging spectroscopy of two luminous type 2 quasars, FIRST J120041.4+314745 ($z$=0.116) and 2MASX J13003807+5454367 ($z$=0.088), and compare their X-ray emission with Hubโ€ฆ

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Spatio-temporal equilibrium thermodynamics of guided optical waves at positive and negative temperatures

Lucas Zanaglia, Josselin Garnier, Claire Michel, Valerie Doya, Mario Ferraro, Stefan Wabnitz, Iacopo Carusotto, Antonio Picozzi ยท 2025

Optical thermalization has been recently studied theoretically and experimentally in the 2D spatial evolution of (quasi-)monochromatic light waves propagating in multimode fibers. In this work, we invโ€ฆ

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A scalable and real-time neural decoder for topological quantum codes

Andrew W. Senior, Thomas Edlich, Francisco J.H. Heras, Lei M. Zhang, Oscar Higgott, James S. Spencer, Taylor Applebaum, Sam Blackwell, Justin Ledford, Akvile Zemgulyte, Augustin Zidek, Noah Shutty, Andrew Cowie, Yin Li, George Holland, Peter Brooks, Charlie Beattie, Michael Newman, Alex Davies, Cody Jones, Sergio Boixo, Hartmut Neven, Pushmeet Kohli, Johannes Bausch ยท 2025

Fault-tolerant quantum computing will require error rates far below those achievable with physical qubits. Quantum error correction (QEC) bridges this gap, but depends on decoders being simultaneouslyโ€ฆ

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Quantum algorithms for viscosity solutions to nonlinear Hamilton-Jacobi equations based on an entropy penalisation method

Shi Jin, Nana Liu ยท 2025

We present a framework for efficient extraction of the viscosity solutions of nonlinear Hamilton-Jacobi equations with convex Hamiltonians. These viscosity solutions play a central role in areas such โ€ฆ

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