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

Probabilistic modeling over permutations using quantum computers

Vasilis Belis, Giulio Crognaletti, Matteo Argenton, Michele Grossi, Maria Schuld ยท 2026

Quantum computers provide a super-exponential speedup for performing a Fourier transform over the symmetric group, an ability for which practical use cases have remained elusive so far. In this work, โ€ฆ

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Physics Preprint PDF DOI

Characterizing High-Capacity Janus Aminobenzene-Graphene Anode for Sodium-Ion Batteries with Machine Learning

Claudia Islas-Vargas, L. Ricardo Montoya, Carlos A. Vital-Jose, Oliver T. Unke, Klaus-Robert Muller, Huziel E. Sauceda ยท 2026

Sodium-ion batteries require anodes that combine high capacity, low operating voltage, fast Na-ion transport, and mechanical stability, which conventional anodes struggle to deliver. Here, we use the โ€ฆ

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Physics Preprint PDF DOI

Probing the Spacetime Structure of Entanglement in Monitored Quantum Circuits with Graph Neural Networks

Javad Vahedi, Stefan Kettemann ยท 2026

Global entanglement in quantum many-body systems is inherently nonlocal, raising the question of whether it can be inferred from local observations. We investigate this problem in monitored quantum ciโ€ฆ

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Physics Preprint PDF DOI

The SPHEREx Ices Investigation: An Overview

Gary J. Melnick, Joseph L. Hora, Matthew L. N. Ashby, Volker Tolls, Jaeyeong Kim, Carey M. Lisse, Roberta Paladini, Michael W. Werner, Jeong-Eun Lee, Young-Jun Kim, Miju Kang, Yun-Ting Cheng, James J. Bock, Brendan P. Crill, Ari Cukierman, Olivier Dore, Andreas Faisst, Howard Hui, Woong-Seob Jeong, Chul-Hwan Kim, Ho-Gyu Lee, Jae-Joon Lee, Daniel Masters, Chi H. Nguyen, Jinyoung Noh, Ji Yeon Seok, Soung-Chul Yang, Yujin Yang, Michael Zemcov ยท 2026

SPHEREx is a NASA mission designed to perform an all-sky spectroscopic survey in the 0.75 - 5 $\mu$m wavelength range. Its primary science objectives are to investigate: (1) inflationary cosmology, (2โ€ฆ

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Physics Preprint PDF DOI

JOYS: Linking the molecular ice and gas-phase composition towards the high-mass hot core IRAS 18089-1732

C. Gieser, W. R. M. Rocha, Y. Chen, K. Slavicinska, E. F. van Dishoeck, P. Nazari, N. G. C. Brunken, L. Francis, H. Beuther, S. Reyes-Reyes, A. Caratti o Garatti, P. D. Klaassen, J. M. Vorster, M. G. Navarro ยท 2026

Context. The formation and destruction of molecules in the interstellar medium is a complex interplay between gas-phase reactions as well as processes on grain surfaces and within icy mantles. For manโ€ฆ

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Physics Preprint PDF DOI

A plug-and-play approach with fast uncertainty quantification for weak lensing mass mapping

Hubert Leterme, Andreas Tersenov, Jalal Fadili, Jean-Luc Starck ยท 2026

Upcoming stage-IV surveys such as Euclid and Rubin will deliver vast amounts of high-precision data, opening new opportunities to constrain cosmological models with unprecedented accuracy. A key step โ€ฆ

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Physics Preprint PDF DOI

NeuralFVM: Neural-physics-based Finite Volume Method for Turbulent Flows Using the $k$-$\omega$ Model

Tingkai Xue, Yu Jiao, Te Ba, Jingliang Wang, Juntao Yang, Simon See, Boyang Chen, Claire E. Heaney, Christopher C. Pain, Chang Wei Kang, Mohamed Arif Bin Mohamed, Hongying Li ยท 2026

In this work, we develop a neural-physics solver based on finite volume method (FVM), namely NeuralFVM, for turbulent flows by implementing the standard $k$-$\omega$ model designed for efficient Graphโ€ฆ

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Physics Preprint PDF DOI

Small-Data Machine Learning Uncovers Decoupled Control Mechanisms of Crystallinity and Surface Morphology in $\beta$-Ga2O3 Epitaxy

Min Peng, Yuanjun Tang, Dianmeng Dong, Yang Zhang, Cheng Wang, Shulin Jiao, Xiaotong Ma, Shichao Zhang, Jingchen Wang, Huiying Wang, Yongxin Zhang, Huiping Zhu, Yue-Wen Fang, Fan Zhang, Zhenping Wu ยท 2026

The ultrawide-bandgap semiconductor $\beta$-Ga2O3 holds exceptional promise for next-generation power electronics and deep-ultraviolet optoelectronics, yet its widespread application is hindered by thโ€ฆ

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Physics Preprint PDF DOI

Many-body mobility edges in one dimension revealed by efficient and interpretable feature-based learning with Kolmogorov-Arnold Networks

Siqi Dai, Tian-Cheng Yi, Xingbo Wei, Yunbo Zhang ยท 2026

We study the many-body localization (MBL) transition in interacting fermionic systems on disordered one-dimensional lattices using a physics-informed machine-learning framework. Instead of feeding fulโ€ฆ

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Physics Preprint PDF DOI

Model selection in hybrid quantum neural networks with applications to quantum transformer architectures

Harsh Wadhwa, Rahul Bhowmick, Naipunnya Raj, Rajiv Sangle, Ruchira V. Bhat, Krishnakumar Sabapathy ยท 2026

Quantum machine learning models generally lack principled design guidelines, often requiring full resource-intensive training across numerous choices of encodings, quantum circuit designs and initialiโ€ฆ

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Physics Preprint PDF DOI

Exploring self-driving labs for optoelectronic materials

Jonathan Staaf Scragg ยท 2026

Self-driving laboratories (SDLs), by combining automation with machine learning-guided experiment selection, have the potential to transform experimental materials science. To date, most SDLs have beeโ€ฆ

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SPINONet: Scalable Spiking Physics-informed Neural Operator for Computational Mechanics Applications

Shailesh Garg, Luis Mandl, Somdatta Goswami, Souvik Chakraborty ยท 2026

Energy efficiency remains a critical challenge in deploying physics-informed operator learning models for computational mechanics and scientific computing, particularly in power-constrained settings sโ€ฆ

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Physics Preprint PDF DOI

Distilling the knowledge with quantum neural networks

Yuxuan Yan, Sitian Qian, Qi Zhao, Xingjian Zhang ยท 2026

Quantum Neural Networks (QNNs) are a promising class of quantum machine learning models with potential quantum advantages when implemented on scalable, error-corrected quantum computers. However, as sโ€ฆ

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Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks

Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel ยท 2026

We propose a Quantum Federated Autoencoder for Anomaly Detection, a framework that leverages quantum federated learning for efficient, secure, and distributed processing in IoT networks. By harnessingโ€ฆ

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Physics Preprint PDF DOI

Orbital Debris in Earth Orbit: Operations, Stability, Control, and Market Formation

Slava G. Turyshev ยท 2026

Orbital debris in Earth orbit is not adequately described as a static inventory problem. It is a coupled operations-stability problem governed by shell occupancy, collision kernel, breakup severity, aโ€ฆ

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Quantum Fuzzy Sets Revisited: Density Matrices, Decoherence, and the Q-Matrix Framework

Mirco A. Mannucci ยท 2026

In 2006 we proposed Quantum Fuzzy Sets, observing that states of a quantum register could serve as characteristic functions of fuzzy subsets, embedding Zadeh's unit interval into the Bloch sphere. Thaโ€ฆ

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B-jet Tagging Using a Hybrid Edge Convolution and Transformer Architecture

Diego F. Vasquez Plaza, Vidya Manian ยท 2026

Jet flavor tagging plays an important role in precise Standard Model measurement enabling the extraction of mass dependence in jet-quark interaction and quark-gluon plasma (QGP) interactions. They alsโ€ฆ

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The Average Relative Entropy and Transpilation Depth determines the noise robustness in Variational Quantum Classifiers

Aakash Ravindra Shinde, Arianne Meijer - van de Griend, Jukka K. Nurminen ยท 2026

Variational Quantum Algorithms (VQAs) have been extensively researched for applications in Quantum Machine Learning (QML), Optimization, and Molecular simulations. Although designed for Noisy Intermedโ€ฆ

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Obstacle-aware navigation of smart microswimmers in a turbulent flow

Vaishnavi Gajendragad, Akanksha Gupta, Nadia Bihari Padhan, Rahul Pandit ยท 2026

Microswimmers in turbulent flows often navigate complex, heterogeneous, and obstacle-rich environments, where they exhibit intricate behaviors such as trapping at and escape from obstacles. We generalโ€ฆ

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Physics Preprint PDF DOI

Towards Computational Microscope of Chemical Order-Disorder via ML-Accelerated Monte Carlo Simulation

Fanli Zhou, Hao Chen, Pengxiang Xu, Kai Yang, Zongrui Pei, Xianglin Liu ยท 2026

Tailoring the performance of next-generation high entropy materials requires a deep understanding of the competition between entropy-driven random solid solution and enthalpy-driven chemical ordering.โ€ฆ

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