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The parity-violating spin asymmetry Apv for elastic electron scattering from spin-zero nuclei, together with its QED corrections, is evaluated non-perturbatively within the phase-shift analysis. Dispersion corrections, taking into account…

Nuclear Theory · Physics 2026-03-30 D. H. Jakubassa-Amundsen , X. Roca-Maza

Foundation models (FMs) are pre-trained on large-scale datasets and then fine-tuned for a specific downstream task. The most common fine-tuning method is to update pretrained weights via low-rank adaptation (LoRA). Existing initialization…

Machine Learning · Computer Science 2025-10-21 Fabian Paischer , Lukas Hauzenberger , Thomas Schmied , Benedikt Alkin , Marc Peter Deisenroth , Sepp Hochreiter

High-precision calculations of hadron spectroscopy are a crucial task for Lattice QCD. State-of-the-art techniques are needed to disentangle the contributions from different energy states, such as solving the generalized eigenvalue problem…

High Energy Physics - Lattice · Physics 2011-02-01 Tereza Mendes

Weak-value amplification (WVA) has recently become an important technique for parameter estimation, owing to its ability to enhance the signal-to-noise ratio by amplifying extremely small signals with proper postselection strategies. In…

Quantum Physics · Physics 2018-03-28 Fei Li , Jingzheng Huang , Guihua Zeng

The development and first applications of a new periodic energy decomposition analysis (pEDA) scheme for extended systems based on the Kohn-Sham approach to density functional theory are described. The pEDA decomposes the binding energy…

Chemical Physics · Physics 2015-05-19 Marc Raupach , Ralf Tonner

Large foundation models have emerged in the last years and are pushing performance boundaries for a variety of tasks. Training or even finetuning such models demands vast datasets and computational resources, which are often scarce and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Leo Fillioux , Enzo Ferrante , Paul-Henry Cournède , Maria Vakalopoulou , Stergios Christodoulidis

This is a tutorial and survey paper on factor analysis, probabilistic Principal Component Analysis (PCA), variational inference, and Variational Autoencoder (VAE). These methods, which are tightly related, are dimensionality reduction and…

Machine Learning · Statistics 2022-05-25 Benyamin Ghojogh , Ali Ghodsi , Fakhri Karray , Mark Crowley

Progress in computing the spectrum of excited baryons and mesons in lattice QCD is described. Large sets of spatially-extended hadron operators are used. A new method of stochastically estimating the low-lying effects of quark propagation…

High Energy Physics - Lattice · Physics 2015-05-27 C. Morningstar , A. Bell , J. Bulava , J. Foley , K. J. Juge , D. Lenkner , C. H. Wong

A method for improving the performance of sparse-matrix based parity check codes is proposed, based on insight gained from methods of statistical physics. The advantages of the new approach are demonstrated on an existing encoding/decoding…

Disordered Systems and Neural Networks · Physics 2009-10-31 Ido Kanter , David Saad

Deep-inelastic ep scattering data, taken with the H1 detector at HERA, are used to study event shape variables over a large range of "relevant energy" Q between 7 GeV and 100 GeV. Previously published analysis on thrust, jet broadening, jet…

High Energy Physics - Phenomenology · Physics 2007-05-23 K. Rabbertz

Low-lying $\Lambda$ baryons with spin 1/2 are analyzed in two-flavor lattice QCD. In order to extract two low-lying states for each parity, we construct $2 \times 2$ cross correlators from flavor SU(3) ``octet'' and ``singlet'' baryon…

High Energy Physics - Lattice · Physics 2011-03-10 Toru T. Takahashi , Makoto Oka

Fair and unbiased machine learning is an important and active field of research, as decision processes are increasingly driven by models that learn from data. Unfortunately, any biases present in the data may be learned by the model,…

Machine Learning · Computer Science 2020-02-27 Matthew J. Vowels , Necati Cihan Camgoz , Richard Bowden

The parity-violating energy difference (PVED) between two enantiomers of a chiral molecule is caused by the weak interaction. Because of the smallness of the PVED, nonzero PVED is yet to be discovered in experimental searches. To detect the…

Chemical Physics · Physics 2022-02-09 Naoya Kuroda , Takumi Oho , Ayaki Sunaga , Masato Senami

A previously-proposed method of constructing spatially-extended gauge-invariant three-quark operators for use in Monte Carlo lattice QCD calculations is tested, and a methodology for using these operators to extract the energies of a large…

High Energy Physics - Lattice · Physics 2007-05-23 Adam C. Lichtl

We introduce a novel way to combine boosting with Gaussian process and mixed effects models. This allows for relaxing, first, the zero or linearity assumption for the prior mean function in Gaussian process and grouped random effects models…

Machine Learning · Computer Science 2024-11-06 Fabio Sigrist

Extended resolution shows that auxiliary variables are very powerful in theory. However, attempts to exploit this potential in practice have had limited success. One reasonably effective method in this regard is bounded variable addition…

Logic in Computer Science · Computer Science 2023-07-06 Andrew Haberlandt , Harrison Green , Marijn J. H. Heule

We analytically and numerically investigate the performance of weak-value amplification (WVA) and related parameter estimation methods in the presence of temporally correlated noise. WVA is a special instance of a general measurement…

QED radiative corrections have been calculated for leptonic and hadronic variables in parity-violating elastic ep scattering. For the first time, the calculation of the asymmetry in the elastic radiative tail is performed without the…

High Energy Physics - Phenomenology · Physics 2009-11-11 J. Arvieux , B. Collin , H. Guler , M. Morlet , S. Niccolai , S. Ong , J. Van de Wiele

In this paper, an enhanced Virtual Element Method (VEM) formulation is proposed for plane elasticity. It is based on the improvement of the strain representation within the element, without altering the degree of the displacement…

Numerical Analysis · Mathematics 2021-02-24 A. M. D'Altri , S. de Miranda , L. Patruno , E. Sacco

We propose the Variation Calibration Error (VCE) metric for assessing the calibration of machine learning classifiers. The metric can be viewed as an extension of the well-known Expected Calibration Error (ECE) which assesses the…

Machine Learning · Computer Science 2026-02-16 Andrew Thompson , Vivek Desai