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Nucleus-nucleus scattering is studied in the local Reggeon Field Theory in the quasi-classical approximation with non-eikonal boundary conditions corresponding to the Glauber picture at low energies. Comparison with the commonly used…

High Energy Physics - Phenomenology · Physics 2008-11-26 M. A. Braun

We present a general frame to extend functional renormalization group (fRG) based computational schemes by using an exactly solvable interacting reference problem as starting point for the RG flow. The systematic expansion around this…

Strongly Correlated Electrons · Physics 2015-02-11 Nils Wentzell , Ciro Taranto , Andrey A. Katanin , Alessandro Toschi , Sabine Andergassen

Can large distance high energy QCD be described by Reggeon Field Theory as an effective emergent theory? We start to investigate the issue employing functional renormalisation group techniques.

High Energy Physics - Theory · Physics 2015-06-23 J. Bartels , C. Contreras , G. P. Vacca

Attempts to apply effective field theory (EFT) methods to nonrelativistic nucleon-nucleon (NN) scattering have raised questions about the nature and limitations of an EFT expansion when used nonperturbatively. We discuss the characteristics…

Nuclear Theory · Physics 2009-10-31 James V. Steele , R. J. Furnstahl

Accessibility percolation is a new type of percolation problem inspired by evolutionary biology: a random number, called its fitness, is assigned to each vertex of a graph, then a path in the graph is accessible if fitnesses are strictly…

Probability · Mathematics 2023-03-01 Frank Duque , Daniel Ramirez-Gomez , Alejandro Roldán-Correa , Leon A. Valencia

Diffusion theory is a central tool of modern population genetics, yielding simple expressions for fixation probabilities and other quantities that are not easily derived from the underlying Wright-Fisher model. Unfortunately, the textbook…

Populations and Evolution · Quantitative Biology 2022-12-19 Camila Bräutigam , Matteo Smerlak

Genetic Programming has been very successful in solving a large area of problems but its use as a machine learning algorithm has been limited so far. One of the reasons is the problem of overfitting which cannot be solved or suppresed as…

Neural and Evolutionary Computing · Computer Science 2015-05-05 Jan Žegklitz , Petr Pošík

A general theory of stochastic decision forests is developed to bridge two concepts of information flow: decision trees and refined partitions on the one side, filtrations from probability theory on the other. Instead of the traditional…

Theoretical Economics · Economics 2024-11-12 E. Emanuel Rapsch

Near the beginning of the century, Wright and Fisher devised an elegant, mathematically tractable model of gene reproduction and replacement that laid the foundation for contemporary population genetics. The Wright-Fisher model and its…

Probability · Mathematics 2013-12-23 Todd L. Parsons

Decision trees are powerful machine learning algorithms, widely used in fields such as economics and medicine for their simplicity and interpretability. However, decision trees such as CART are prone to overfitting, especially when grown…

Machine Learning · Statistics 2026-01-13 Likun Zhang , Wei Ma

Kinetic Field Theory (KFT) is a statistical field theory for an ensemble of point-like classical particles in or out of equilibrium. We review its application to cosmological structure formation. Beginning with the construction of the…

We propose a novel ensemble method called Riemann-Lebesgue Forest (RLF) for regression. The core idea in RLF is to mimic the way how a measurable function can be approximated by partitioning its range into a few intervals. With this idea in…

Machine Learning · Statistics 2024-05-13 Tian Qin , Wei-Min Huang

We give a detailed exposition of the formalism of Kinetic Field Theory (KFT) with emphasis on the perturbative determination of observables. KFT is a statistical non-equilibrium classical field theory based on the path integral formulation…

High Energy Physics - Theory · Physics 2022-10-05 Lavinia Heisenberg , Shayan Hemmatyar , Stefan Zentarra

The random percolation model can be viewed as the dual of a well defined confining gauge theory; since this theory, having no Monte Carlo dynamics at all, is simple to simulate, it is possible to study the properties of the flux tube with…

High Energy Physics - Lattice · Physics 2009-04-14 Pietro Giudice , Ferdinando Gliozzi , Stefano Lottini

A new version of double field theory (DFT) is derived for the exactly solvable background of an in general left-right asymmetric WZW model in the large level limit. This generalizes the original DFT that was derived via expanding closed…

High Energy Physics - Theory · Physics 2015-03-03 Ralph Blumenhagen , Falk Hassler , Dieter Lust

We apply a stochastic method of minimizing the ground state energy in variational calculations of light nuclei using the Refined Resonating Group Model (RRGM). The method utilizes a bit representation of the width parameters to be varied.…

Nuclear Theory · Physics 2008-11-26 Christian Winkler , Hartmut M. Hofmann

Reactor physics aims at studying the neutron population in a reactor core under the influence of feedback mechanisms, such as the Doppler temperature effect. Numerical schemes to calculate macroscopic properties emerging from such coupled…

Statistical Mechanics · Physics 2022-12-28 Benjamin Dechenaux , Thomas Delcambre , Eric Dumonteil

We consider the non-trivial boundary conformal field theory with exactly marginal boundary deformation. In recent years this deformation has been studied in the context of rolling tachyons and S-branes in string theory. Here we study the…

High Energy Physics - Theory · Physics 2008-11-26 Shinsuke Kawai , Esko Keski-Vakkuri , Robert G. Leigh , Sean Nowling

A general analysis of line defect renormalisation group (RG) flows in the $\varepsilon$ expansion below $d=4$ dimensions is undertaken. The defect beta function for general scalar-fermion bulk theories is computed to next-to-leading order…

High Energy Physics - Theory · Physics 2023-07-26 William H. Pannell , Andreas Stergiou

The field of health informatics has been profoundly influenced by the development of random forest models, which have led to significant advances in the interpretability of feature interactions. These models are characterized by their…

Machine Learning · Computer Science 2025-06-04 Akshat Dubey , Aleksandar Anžel , Georges Hattab