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

Phase Transitions as the Breakdown of Statistical Indistinguishability

Taiyo Narita, Hideyuki Miyahara ยท 2026

We introduce a novel characterization of phase transitions based on hypothesis testing. In our formulation, a phase transition is defined as the breakdown of statistical indistinguishability under vโ€ฆ

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Physics Preprint PDF DOI

Machine-learning-assisted material and geometry characterization from Casimir force measurement

Hideo Iizuka, Shanhui Fan ยท 2026

A broadband electromagnetic source is important for scientific and technological applications. Quantum vacuum fluctuations, which manifest most prominently in the Casimir effect, provide a fundamentalโ€ฆ

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Physics Preprint PDF DOI

Energy conditions in static, spherically symmetric spacetimes and effective geometries

Zi-Liang Wang, Emmanuele Battista ยท 2026

Classical energy conditions are investigated in generic static and spherically symmetric spacetimes. In setups with nonconstant $g_{tt} g_{rr}$, the appearance of horizons can signal the violation of โ€ฆ

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Physics Preprint PDF DOI

Observable-Guided Generator Selection for Improving Trainability in Quantum Machine Learning with a $ \mathfrak{g} $-Purity Interpretation under Restricted Settings

Hiroshi Ohno ยท 2026

To study generator design for parameterized unitaries in quantum machine learning (QML), we propose an observable-guided generator selection algorithm for $ n $-qubit Pauli-string generator pools. Theโ€ฆ

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Physics Preprint PDF DOI

Self-Organization to the Edge of Ergodicity Breaking in a Complex Adaptive System

Nixie Sapphira Lesmana, Ling Feng, Kan Chen, Choy Heng Lai ยท 2026

Self-organized criticality (SOC) is widely proposed as a fundamental mechanism for collective behavior, yet its role in objective-driven, heterogeneous adaptive systems underpinning real complex systeโ€ฆ

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Physics Preprint PDF DOI

Explainable quantum regression algorithm with encoded data structure

C.-C. Joseph Wang, F. Perkkola, I. Salmenpera, A. Meijer-van de Griend, J. K. Nurminen ยท 2026

Hybrid variational quantum algorithms are promising for solving practical problems, such as combinatorial optimization, quantum chemistry simulation, quantum machine learning, and quantum error correcโ€ฆ

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Physics Preprint PDF DOI

Bridge the Gap between Classical and Quantum Neural Networks with Residual Connections

Junxu Li ยท 2026

We introduce a Hybrid Quantum Residual Network (HQRN) and establish an exact functional correspondence between its state evolution and the dynamics of classical networks with residual connections. Wheโ€ฆ

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Physics Preprint PDF DOI

A Structure-Preserving Graph Neural Solver for Parametric Hyperbolic Conservation Laws

Jiamin Jiang, Shanglin Lv, Jingrun Chen ยท 2026

Hyperbolic conservation laws govern a wide range of transport-driven dynamics featuring shocks, contact discontinuities, and complex wave interactions, posing distinct challenges for deep-learning-basโ€ฆ

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Physics Preprint PDF DOI

Classifying Supermassive Black Hole Growth Regimes to Observables Across Cosmological Simulations with Forecasts for LSST

Hitaishi Chillara ยท 2026

The possibility of over-massive black holes suggested by James Webb Space Telescope photometric discoveries of 'little red dots', may disfavor light supermassive black hole (SMBH) seeds. However, whatโ€ฆ

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Physics Preprint PDF DOI

Feature-level analysis and adversarial transfer in rotationally equivariant quantum machine learning

Maureen Krumtunger, Martin Sevior, Muhammad Usman ยท 2026

Group-equivariant quantum models are designed to exploit symmetry and can improve trainability, but it remains unclear how symmetry constraints shape their adversarial robustness. We study this questiโ€ฆ

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Quantum computation at the edge of chaos

Tomohiro Hashizume, Zhengjun Wang, Frank Schlawin, Dieter Jaksch ยท 2026

A key challenge in classical machine learning is to mitigate overparameterization by selecting sparse solutions. We translate this concept to the quantum domain, introducing quantum sparsity as a prinโ€ฆ

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Efficient $n$-qubit entangling operations via a superconducting quantum router

Xuntao Wu, Haoxiong Yan, Gustav Andersson, Alexander Anferov, Christopher R. Conner, Yash J. Joshi, Bayan Karimi, Amber M. King, Shiheng Li, Howard L. Malc, Jacob M. Miller, Harsh Mishra, Hong Qiao, Minseok Ryu, Jian Shi, Andrew N. Cleland ยท 2026

Quantum algorithms on near-term quantum processors are typically executed using shallow quantum circuits composed of one- and two-qubit gates. However, as circuit depth and gate number increase, gate โ€ฆ

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Physics Preprint PDF DOI

Cloning is as Hard as Learning for Stabilizer States

Nikhil Bansal, Matthias C. Caro, Gaurav Mahajan ยท 2026

The impossibility of simultaneously cloning non-orthogonal states lies at the foundations of quantum theory. Even when allowing for approximation errors, cloning an arbitrary unknown pure state requirโ€ฆ

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Optimal algorithmic complexity of inference in quantum kernel methods

Elies Gil-Fuster, Seongwook Shin, Sofiene Jerbi, Jens Eisert, Maximilian J. Kramer ยท 2026

Quantum kernel methods are among the leading candidates for achieving quantum advantage in supervised learning. A key bottleneck is the cost of inference: evaluating a trained model on new data requirโ€ฆ

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Physics Preprint PDF DOI

Understanding the regulation of star formation within TNG100 galaxies on kpc-scales using machine learning I: Global versus local

Bryanne McDonough, Sathvika S. Iyengar, Ansa Brew-Smith, Asa F.L. Bluck, Joanna Piotrowska ยท 2026

We apply Random Forest and XGBoost machine learning algorithms to determine which galaxy properties most effectively predict star formation and quenching in simulated galaxies. Using spatially-resolveโ€ฆ

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Physics Preprint PDF DOI

Quantum Metropolis-Hastings via Penalised Qubitized Walks: Spectral Filtering and Circuit Implementation

Miguel Carrasco-Arango, Rosa M. Badia, Artur Garcia-Saez ยท 2026

The Metropolis-Hastings algorithm is a cornerstone of Markov Chain Monte Carlo methods, underpinning a wide range of applications in computational physics, Bayesian inference, and machine learning. Quโ€ฆ

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Physics Preprint PDF DOI

Localization and Confidence Region Estimation of Short GRBs with the COSI BGO Shield Using a HEALPix-Based Deep Learning Approach

N. Parmiggiani, A. Bulgarelli, G. Panebianco, E. Burns, E. Neights, V. Fioretti, I. Martinez-Castellanos, L. Castaldini, A. Ciabattoni, A. Di Piano, R. Falco, S. Gallego, G. Mustafa, P. Patel, A. Rizzo, E. A. Wulf, D. H. Hartmann, C. A. Kierans, J. A. Tomsick, A. Zoglauer ยท 2026

The Compton Spectrometer and Imager is a NASA satellite mission under development that will survey the entire sky in the 0.2-5 MeV range using a wide-field germanium detector array, surrounded on the โ€ฆ

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Physics Preprint PDF DOI

GAT-QNN: Genetic Algorithm-Based Training of Hybrid Quantum Neural Networks

Tasnim Ahmed, Alberto Marchisio, Muhammad Kashif, Nouhaila Innan, Muhammad Shafique ยท 2026

Hybrid Quantum Neural Networks (HQNNs) combine classical learning with parameterized quantum circuits, but their practical performance is often limited by (i) the noise of Noisy Intermediate-Scale Quaโ€ฆ

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Endwall and leading-edge film cooling of turbine blades in a hydrogen-fueled rotating detonation combustor-turbine coupled system

Yeqi Zhou, Songbai Yao, Jingtian Yu, Weijia Qian, Ping Wang, Wenwu Zhang ยท 2026

This study performs a three-dimensional numerical simulation of the coupled flow field in a hydrogen-air rotating detonation combustor (RDC)-turbine system to evaluate the effectiveness of different fโ€ฆ

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Learning to Concatenate Quantum Codes

Nico Meyer, Christopher Mutschler, Dominik Seu{ss}, Andreas Maier, Daniel D. Scherer ยท 2026

Concatenating quantum error correction codes scales error correction capability by driving logical error rates down double-exponentially across levels. However, the noise structure shifts under concatโ€ฆ

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