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Pionless effective field theory in a finite volume (FVEFT$_{\pi\!/}$) is investigated as a framework for the analysis of multi-nucleon spectra and matrix elements calculated in lattice QCD (LQCD). By combining FVEFT$_{\pi\!/}$ with the…

Nuclear Theory · Physics 2021-04-21 W. Detmold , P. E. Shanahan

We use functional methods to compute one-loop effects in Heavy Quark Effective Theory. The covariant derivative expansion technique facilitates the efficient extraction of matching coefficients and renormalization group evolution equations.…

High Energy Physics - Phenomenology · Physics 2020-07-15 Timothy Cohen , Marat Freytsis , Xiaochuan Lu

Random matrix theory is used to assess the significance of weak correlations and is well established for Gaussian statistics. However, many complex systems, with stock markets as a prominent example, exhibit statistics with power-law tails,…

Statistical Mechanics · Physics 2013-03-19 Mauro Politi , Enrico Scalas , Daniel Fulger , Guido Germano

Graphical models for finite-dimensional spin glasses and real-world combinatorial optimization and satisfaction problems usually have an abundant number of short loops. The cluster variation method and its extension, the region graph…

Disordered Systems and Neural Networks · Physics 2013-07-29 Haijun Zhou , Chuang Wang

Lattice systems are effective for modeling heterogeneous materials, but their computational cost is often prohibitive. The QuasiContinuum (QC) method reduces this cost by interpolating the lattice response over a coarse finite-element mesh,…

Numerical Analysis · Mathematics 2026-03-27 Benjamin Werner , Ondřej Rokoš , Jan Zeman

Radiative corrections in Lorentz violating (LV) models have already received a lot of attention in the literature in recent years, with many instances where a LV operator in one sector of the Standard Model Extension (SME) generates, via…

High Energy Physics - Theory · Physics 2020-05-25 A. F. Ferrari , J. R. Nascimento , A. Yu. Petrov

We propose a new descriptor for local atomic environments, to be used in combination with machine learning models for the construction of interatomic potentials. The Local Atomic Tensors Trainable Expansion (LATTE) allows for the efficient…

Computational Physics · Physics 2024-05-15 Franco Pellegrini , Stefano de Gironcoli , Emine Küçükbenli

Several previous experimental and theoretical studies have shown that a leading edge vortex (LEV) on an airfoil or wing can provide lift enhancement. In this paper, unsteady 2D potential flow theory is employed to model the flow field of a…

Fluid Dynamics · Physics 2018-03-21 Xi Xia , Kamran Mohseni

We develop tools for performing effective field theory (EFT) calculations in a manifestly gauge-covariant fashion. We clarify how functional methods account for one-loop diagrams resulting from the exchange of both heavy and light fields,…

High Energy Physics - Phenomenology · Physics 2016-04-06 Brian Henning , Xiaochuan Lu , Hitoshi Murayama

Variational autoencoders (VAEs) are a popular generative model used to approximate distributions. The encoder part of the VAE is used in amortized learning of latent variables, producing a latent representation for data samples. Recently,…

Machine Learning · Statistics 2023-05-12 Daniel G. Edelberg , Roy R. Lederman

We consider the higher-derivative Lorentz-breaking extension of QED, where the new terms are the Myers-Pospelov-like ones in gauge and spinor sectors, and the higher--derivative CFJ term. For this theory, we study its tree-level dynamics,…

High Energy Physics - Theory · Physics 2019-05-14 T. Mariz , J. R. Nascimento , A. Yu. Petrov , C. Marat Reyes

Lattice networks with dissipative interactions are often employed to analyze materials with discrete micro- or meso-structures, or for a description of heterogeneous materials which can be modelled discretely. They are, however,…

Materials Science · Physics 2017-04-26 Ondřej Rokoš , Ron H. J. Peerlings , Jan Zeman

Large Language Models (LLMs) excel in natural language processing tasks but pose significant computational and memory challenges for edge deployment due to their intensive resource demands. This work addresses the efficiency of LLM…

Hardware Architecture · Computer Science 2025-07-02 Zhican Wang , Hongxiang Fan , Haroon Waris , Gang Wang , Zhenyu Li , Jianfei Jiang , Yanan Sun , Guanghui He

Variational autoencoders employ an amortized inference model to approximate the posterior of latent variables. However, such amortized variational inference faces two challenges: (1) the limited posterior expressiveness of fully-factorized…

Machine Learning · Computer Science 2022-12-01 Yookoon Park , Chris Dongjoo Kim , Gunhee Kim

It is shown that detailed and accurate information about the mass spectrum of the massive Schwinger model can be obtained using the technique of strong-coupling series expansions. Extended strong-coupling series for the energy eigenvalues…

High Energy Physics - Lattice · Physics 2009-10-30 C. J. Hamer , Zheng Weihong , J. Oitmaa

While reinforcement learning has achieved impressive progress in language model reasoning, it is constrained by the requirement for verifiable rewards. Recent verifier-free RL methods address this limitation by utilizing the probabilities…

Computation and Language · Computer Science 2026-05-26 Xueru Wen , Jie Lou , Yanjiang Liu , Hongyu Lin , Ben He , Xianpei Han , Le Sun , Yaojie Lu , Debing Zhang

Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual settings, yet existing approaches face a trade-off. Traditional probabilistic customer base…

Machine Learning · Statistics 2026-04-27 Jeffrey Näf , Riana Valera Mbelson , Markus Meierer

The recently-introduced Parity Expanded Variational Analysis (PEVA) technique allows for the isolation of baryon eigenstates on the lattice at finite momentum free from opposite-parity contamination. We find that this technique introduces a…

High Energy Physics - Lattice · Physics 2020-01-23 Finn M. Stokes , Waseem Kamleh , Derek B. Leinweber

A new iterative method is developed to numerically calculate the periodic, matched beam envelope solution of the coupled Kapchinskij-Vladimirskij (KV) equations describing the transverse evolution of a beam in a periodic, linear focusing…

Accelerator Physics · Physics 2009-11-11 Steven M. Lund , Sven H. Chilton , Edward P. Lee

Lattice relaxation profoundly reshapes electronic structures in twisted materials. Prevailing treatments, however, typically rely on large-scale density functional theory (DFT), which is computationally costly and mechanistically opaque.…

Materials Science · Physics 2025-09-17 Junxi Yu , Bingbing Wang , Cheng-Cheng Liu
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