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The Parity-Doublet Model (PDM) is a chirally invariant effective theory for strong-interaction matter involving nucleons and their opposite-parity partners in a parity-doubling framework. We introduce a multiplicatively renormalizable…

Nuclear Theory · Physics 2026-04-24 Mattia Recchi , Lorenz von Smekal , Jochen Wambach

We investigate a relativistic quantum field theory in the particle representation using a non-perturbative variational technique. The theory is that of two massive scalar particles, `nucleons' and `mesons', interacting via a Yukawa…

Nuclear Theory · Physics 2009-10-28 A. W. Schreiber , R. Rosenfelder

A diffusion Monte Carlo algorithm is introduced that can determine the correct nodal structure of the wave function of a few-fermion system and its ground-state energy without an uncontrolled bias. This is achieved by confining signed…

Computational Physics · Physics 2020-02-05 Alexander A. Kunitsa , So Hirata

A self-consistent theory for two-particle fluctuations with renormalized irreducible vertices is proposed. Using the Parquet formalism, we construct the fully antisymmetric full vertex in terms of the two-particle fluctuations in the…

Strongly Correlated Electrons · Physics 2015-05-19 Hiroaki Kusunose

This work presents a family of parsimonious Gaussian process models which allow to build, from a finite sample, a model-based classifier in an infinite dimensional space. The proposed parsimonious models are obtained by constraining the…

Methodology · Statistics 2012-06-18 Charles Bouveyron , Stéphane Girard , Mathieu Fauvel

A general Lorentz--invariant parameterization for the long-range part of the $0\nu\beta\beta$ decay rate is derived. Combined with the short range part this general parameterization in terms of effective $B-L$ violating couplings will allow…

High Energy Physics - Phenomenology · Physics 2009-10-31 H. Päs , M. Hirsch , H. V. Klapdor-Kleingrothaus , S. G. Kovalenko

The application of Wilson's Numerical Renormalization Group (NRG) method to dissipative quantum impurity models, in particular the sub-ohmic spin-boson model, has led to conclusions regarding the quantum critical behavior which are in…

Statistical Mechanics · Physics 2012-03-16 Matthias Vojta

Recurrent neural networks (RNNs) are brain-inspired models widely used in machine learning for analyzing sequential data. The present work is a contribution towards a deeper understanding of how RNNs process input signals using the response…

Machine Learning · Statistics 2021-02-15 Soon Hoe Lim

Determinantal point processes are characterized by a special structural property of the correlation functions: they are given by minors of a correlation kernel. However, unlike the correlation functions themselves, this kernel is not…

Probability · Mathematics 2022-06-15 Grigori Olshanski

Nucleon decays into a lepton and two pseudoscalar mesons represent key channels for probing baryon number violation, complementing conventional two-body modes. In this Letter, we model-independently correlate two- and three-body processes…

High Energy Physics - Phenomenology · Physics 2026-04-28 Wei-Qi Fan , Yi Liao , Xiao-Dong Ma

Inference in popular nonparametric Bayesian models typically relies on sampling or other approximations. This paper presents a general methodology for constructing novel tractable nonparametric Bayesian methods by applying the kernel trick…

Machine Learning · Statistics 2011-08-15 Ferenc Huszár , Simon Lacoste-Julien

Partial mean with generated regressors arises in several econometric problems, such as the distribution of potential outcomes with continuous treatments and the quantile structural function in a nonseparable triangular model. This paper…

Econometrics · Economics 2018-11-02 Ying-Ying Lee

The affine group of a tree is the group of the isometries of a homogeneous tree that fix an end of its boundary. Consider a probability measure on this group and the associated random walk. The main goal of this paper is to determine the…

Probability · Mathematics 2007-05-23 Sara Brofferio

We derive an evolution equation for the generating functional which accounts for processes for both gluon emission and recombination. In terms of color dipoles, the kernel of this equation describes evolution as a classical branching…

High Energy Physics - Phenomenology · Physics 2009-11-11 Eugene Levin , Michael Lublinsky

Let $A$ be a primitive matrix and let $\lambda$ be its Perron-Frobenius eigenvalue. We give formulas expressing the associated normalized Perron-Frobenius eigenvector as a simple functional of a multitype Galton-Watson process whose mean…

Probability · Mathematics 2018-03-26 Raphaël Cerf , Joseba Dalmau

We observe that the Connes--Kreimer Hopf-algebraic approach to perturbative renormalisation works not just for Hopf algebras but more generally for filtered bialgebras $B$ with the property that $B_0$ is spanned by group-like elements (e.g.…

Mathematical Physics · Physics 2015-11-09 Joachim Kock

Generative diffusion models apply the concept of Langevin dynamics in physics to machine leaning, attracting a lot of interests from engineering, statistics and physics, but a complete picture about inherent mechanisms is still lacking. In…

Statistical Mechanics · Physics 2025-01-07 Zhendong Yu , Haiping Huang

The single renormalon-chain contribution to the correlator of scalar currents in QCD is calculated in the $\bar{MS}$-scheme in the limit of a large $N_f$. We find that in the factorial growth of the coefficients due to renormalons takes…

High Energy Physics - Phenomenology · Physics 2008-11-26 D. J. Broadhurst , A. L. Kataev , C. J. Maxwell

We build the two dimensional Gross-Neveu model by a new method which requires neither cluster expansion nor discretization of phase-space. It simply reorganizes the perturbative series in terms of trees. With this method we can for the…

High Energy Physics - Theory · Physics 2009-05-07 M. Disertori , V. Rivasseau

Consider a Crump-Mode-Jagers process generated by an increasing random walk whose increments have finite second moment. Let $Y_k(t)$ be the number of individuals in generation $k\in \mathbb N$ born in the time interval $[0,t]$. We prove a…

Probability · Mathematics 2022-12-29 Alexander Iksanov , Zakhar Kabluchko , Valeriya Kotelnikova
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