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

How to Classically Verify a Quantum Cat without Killing It

Yael Tauman Kalai, Dakshita Khurana, Justin Raizes ยท 2026

Existing protocols for classical verification of quantum computation (CVQC) consume the prover's witness state, requiring a new witness state for each invocation. Because QMA witnesses are not generalโ€ฆ

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Physics Preprint PDF DOI

Micromolar chemical imaging by high-energy low-photodamage Coherent Anti-stokes Raman Scattering (HELP-CARS)

Guangrui Ding, Dingcheng Sun, Yifan Zhu, Rong Tang, Hongli Ni, Yuhao Yuan, Haonan Lin, Ji-Xin Cheng ยท 2026

Coherent anti-Stokes Raman scattering (CARS) microscopy offers label-free chemical imaging capabilities, but its performance is constrained by small Raman scattering cross-section, strong non-resonantโ€ฆ

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Physics Preprint PDF DOI

astromorph: Self-supervised machine learning pipeline for astronomical morphology analysis

Per Bjerkeli, Jouni Kainulainen, Maria Carmen Toribio, Leon Boschman, Otoniel Maya Lucas ยท 2026

Modern telescopes generate increasingly large and diverse datasets, often consisting of complex and morphologically rich structures. To efficiently explore such data requires automated methods that caโ€ฆ

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Physics Preprint PDF DOI

A multi-event interface for next-to-leading order calculations in MadGraph5_aMC@NLO

Rikkert Frederix, Stefan Roiser, Robert Schofbeck, Zenny Wettersten, Marco Zaro ยท 2026

We detail the implementation of a multi-event interface for next-to-leading order (NLO) calculations in MadGraph5_aMC@NLO, allowing tree-level scattering amplitudes for multiple phase space points to โ€ฆ

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Physics Preprint PDF DOI

An Exploration of the Equation of State Dependence of Core-Collapse Supernova Explosion Outcomes and Signatures

Aleksandr Rusakov, Adam S. Burrows, Tianshu Wang, David Vartanyan ยท 2026

We explore, using a state-of-the-art simulation code in 3D and to late enough times to witness final observables, the dependence of core-collapse supernova explosions on the nuclear equation of state.โ€ฆ

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Physics Preprint PDF DOI

PEST: Physics-Enhanced Swin Transformer for 3D Turbulence Simulation

Yilong Dai, Shengyu Chen, Xiaowei Jia, Peyman Givi, Runlong Yu ยท 2026

Accurate simulation of turbulent flows is fundamental to scientific and engineering applications. Direct numerical simulation (DNS) offers the highest fidelity but is computationally prohibitive, whilโ€ฆ

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Physics Preprint PDF DOI

Quantum Riemannian Cubics with Obstacle Avoidance for Quantum Geometric Model Predictive Control

Leonardo Colombo ยท 2026

We propose a geometric model predictive control framework for quantum systems subject to smoothness and state constraints. By formulating quantum state evolution intrinsically on the projective Hilberโ€ฆ

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Physics Preprint PDF DOI

NMRPeak: a ready-to-use intelligent system for molecular structure elucidation enabled by synergistic cross-modal learning

Fanjie Xu, Jinyuan Hu, Jingxiang Zou, Junjie Wang, Boying Huang, Zhifeng Gao, Xiaohong Ji, Weinan E, Zhong-Qun Tian, Fujie Tang, Jun Cheng ยท 2026

One-dimensional nuclear magnetic resonance (NMR) spectroscopy is essential for molecular structure elucidation in organic synthesis, drug discovery, natural product characterization, and metabolomics,โ€ฆ

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Physics Preprint PDF DOI

Weak forms offer strong regularisations: how to make physics-informed (quantum) machine learning more robust

Annie E. Paine, Smit Chaudhary, Antonio A. Gentile ยท 2026

Physics-informed (PI) methodologies have surged to become a pillar route to solve Differential Equations (DEs), sustained by the growth of machine learning methods in scientific contexts. The main proโ€ฆ

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Topological beam stirring in a multicore fiber

Alena Kolesnikova, Mikhail Gervaziev, Nikita Bochkarev, Denis Kharenko, Evgeny Podivilov, Sergey Babin ยท 2026

Multicore fibers (MCF) are perspective media for telecommunications, sensing, imaging and laser technologies. Here, the effect of beam stirring between weakly coupled cores is observed for sub-nanosecโ€ฆ

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Homing through Reinforcement Learning

Riya Singh, Pratikshya Jena, Anish Kumar, Shradha Mishra ยท 2026

Homing and navigation are fundamental behaviors in biological systems that enable agents to reliably reach a target under uncertainty. We present a Reinforcement Learning (RL) framework to model adaptโ€ฆ

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Empirical Study of Observable Sets in Multiclass Quantum Classification

Paul San Sebastian, Mikel Canizo, Roman Orus ยท 2026

Variational quantum algorithms have gained attention as early applications of quantum computers for learning tasks. In the context of supervised learning, most of the works that tackle classification โ€ฆ

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CSPR-Net: Self-supervised Curved Surface Projection Rectification Network for Geometric Distortion Correction in Non-planar Projections

Kejin Peng, Jia Wei, Xiang Hao ยท 2026

Projecting images onto non-planar surfaces inevitably introduces geometric distortions that degrade visual quality. Traditional correction methods often require tedious manual calibration or structureโ€ฆ

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Analysis of the Hopfield Model Incorporating the Effects of Unlearning

Shuta Takeuchi, Takashi Takahashi, Yoshiyuki Kabashima ยท 2026

We analyze a variant of the Hopfield model that incorporates an unlearning mechanism based on spin correlations in the high-temperature regime. In the large system limit where extensively many patternโ€ฆ

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Optimizing Spectral Prediction in MXene-Based Metasurfaces Through Multi-Channel Spectral Refinement and Savitzky-Golay Smoothing

Shujaat Khan, Waleed Iqbal Waseer ยท 2026

The prediction of electromagnetic spectra for MXene-based solar absorbers is a computationally intensive task, traditionally addressed using full-wave solvers. This study introduces an efficient deep โ€ฆ

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Quo vadis biophotonics? Wearing serendipity and slow science as a badge of pride, and embracing biology

G.E. Schroeder-Turk ยท 2026

This article is a reflection on the themes of the Faraday Discussion meeting on "Biological and bio-inspired optics" held from 20 to 22 July 2020. It is a personal perspective on the nature of this fiโ€ฆ

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Ferrofluid bend channel flows for multi-parameter tunable heat transfer enhancement Part 2 Deep Learning and Neural Network Modeling

Nadish Anand, Prashant Shukla, Warren Jasper ยท 2026

This work is the second in a series focused on ferrofluid bend channel flows. Here, ferrofluid flows in bend channels are modeled using machine learning methods, based on data generated from the CFD sโ€ฆ

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Design principles for III-nitride-nanocluster photocatalysts from region-resolved electronic structure

Shuaishuai Yuan, Gunther G. Andersson, Gregory F. Metha, Zetian Mi, Hong Guo ยท 2026

Understanding how nanocluster cocatalysts modify the electronic structure of III-nitride surfaces is central to the rational design of efficient photocatalytic interfaces. Here, we establish design prโ€ฆ

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Machine learning in online and offline reconstruction and identification with CMS

Uttiya Sarkar ยท 2026

Machine learning (ML) plays an increasingly important role in both online and offline event reconstruction and identification at CMS experiment. A variety of ML techniques are used to improve the idenโ€ฆ

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Trajectory arclength reveals chaos

Javier Jimenez-Lopez, V. J. Garcia-Garrido ยท 2026

In this paper we demonstrate that the phase space arclength of a trajectory, quantified by the time-averaged Lagrangian descriptor, is a robust and self-contained chaos indicator. By invoking Birkhoffโ€ฆ

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