English
Related papers

Related papers: The GRACE system for SUSY processes

200 papers

We elaborate on the method of differential equations for evaluating Feynman integrals. We focus on systems of equations for master integrals having a linear dependence on the dimensional parameter. For these systems we identify the criteria…

High Energy Physics - Phenomenology · Physics 2015-06-18 Mario Argeri , Stefano Di Vita , Pierpaolo Mastrolia , Edoardo Mirabella , Johannes Schlenk , Ulrich Schubert , Lorenzo Tancredi

We present a new approach to some four-fermion lattice field theories which we call the generalized fermion bag approach. The basic idea is to identify unpaired fermionic degrees of freedom that cause sign problems and collect them in a…

High Energy Physics - Lattice · Physics 2011-12-01 Shailesh Chandrasekharan , Anyi Li

L\"uscher's local bosonic algorithm for Monte Carlo simulations of quantum field theories with fermions is applied to the simulation of a possibly supersymmetric Yang-Mills theory with a Majorana fermion in the adjoint representation.…

High Energy Physics - Lattice · Physics 2009-10-28 I. Montvay

We show how to apply renormalization group algorithms incorporating entanglement filtering methods and a loop optimization to a tensor network which includes Grassmann variables which represent fermions in an underlying lattice field…

High Energy Physics - Lattice · Physics 2023-01-12 Muhammad Asaduzzaman , Simon Catterall , Yannick Meurice , Ryo Sakai , Goksu Can Toga

The structure of the quark and lepton masses and mixing angles provides one of the few windows we have on the underlying physics generating the \sm. In an attempt to identify the underlying symmetry group we look for the simplest gauge…

High Energy Physics - Phenomenology · Physics 2011-07-19 Luis E. Ibanez , G. G. Ross

We offer a new proposal for the Monte Carlo treatment of many-fermion systems in continuous space. It is based upon Diffusion Monte Carlo with significant modifications: correlated pairs of random walkers that carry opposite signs;…

Condensed Matter · Physics 2009-10-31 M. H. Kalos , Francesco Pederiva

Building surrogate models is one common approach when we attempt to learn unknown black-box functions. Bayesian optimization provides a framework which allows us to build surrogate models based on sequential samples drawn from the function…

Machine Learning · Computer Science 2021-09-17 Hengrui Luo , James W. Demmel , Younghyun Cho , Xiaoye S. Li , Yang Liu

Relaxation processes driven by a Laplacian matrix can be found in many real-world big-data systems, for example, in search engines on the World-Wide-Web and the dynamic load balancing protocols in mesh networks. To numerically implement…

Statistical Mechanics · Physics 2015-06-19 S. Hwang , D. -S. Lee , B. Kahng

It is shown how to construct exactly gauge-invariant S-matrix elements for processes involving unstable gauge particles such as the $W$ and $Z^0$ bosons. The results are applied to derive a physically meaningful expression for the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Robin G. Stuart

A greedy randomized augmented Kaczmarz (GRAK) method was proposed in [Z.-Z. Bai and W.-T. WU, SIAM J. Sci. Comput., 43 (2021), pp. A3892-A3911] for large and sparse inconsistent linear systems. However, one has to construct two new index…

Numerical Analysis · Mathematics 2023-10-24 Shunchang Li , Gang Wu

Gaussian processes (GPs) are widely used in nonparametric regression, classification and spatio-temporal modeling, motivated in part by a rich literature on theoretical properties. However, a well known drawback of GPs that limits their use…

Methodology · Statistics 2011-06-29 Anjishnu Banerjee , David Dunson , Surya Tokdar

Parameter identification and comparison of dynamical systems is a challenging task in many fields. Bayesian approaches based on Gaussian process regression over time-series data have been successfully applied to infer the parameters of a…

Machine Learning · Statistics 2019-03-04 Philippe Wenk , Alkis Gotovos , Stefan Bauer , Nico Gorbach , Andreas Krause , Joachim M. Buhmann

A new event generator is proposed for two processes e+e- -> nu nu-bar gamma and e+e- -> nu nu-bar gamma gamma where nu includes all the neutrino species. The exact matrix elements of single- and double-photon emission, generated by the…

High Energy Physics - Phenomenology · Physics 2009-10-31 Y. Kurihara , J. Fujimoto , T. Ishikawa , Y. Shimizu , T. Munehisa

We present a practical analysis of the fermion sign problem in fermionic path integral Monte Carlo (PIMC) simulations in the grand-canonical ensemble (GCE). As a representative model system, we consider electrons in a $2D$ harmonic trap. We…

Computational Physics · Physics 2021-09-01 Tobias Dornheim

In this paper we propose the first non-parametric Bayesian model using Gaussian Processes to make inference on Poisson Point Processes without resorting to gridding the domain or to introducing latent thinning points. Unlike competing…

Machine Learning · Statistics 2015-06-30 Yves-Laurent Kom Samo , Stephen Roberts

Gaussian Processes are widely used for regression tasks. A known limitation in the application of Gaussian Processes to regression tasks is that the computation of the solution requires performing a matrix inversion. The solution also…

Machine Learning · Computer Science 2017-08-22 Sourish Das , Sasanka Roy , Rajiv Sambasivan

The low-lying eigenvalues of a (sparse) hermitian matrix can be computed with controlled numerical errors by a conjugate gradient (CG) method. This CG algorithm is accelerated by alternating it with exact diagonalisations in the subspace…

High Energy Physics - Lattice · Physics 2008-11-26 Thomas Kalkreuter , Hubert Simma

Microscopic models of classical degrees of freedom coupled to non-interacting fermions occur in many different contexts. Prominent examples from solid state physics are descriptions of colossal magnetoresistance manganites and diluted…

Statistical Mechanics · Physics 2009-06-16 Alexander Weiße

There has been growing interest in investigating properties of elementary particles predicted by the standard model. Examples of such studies include exploring their low-energy analogs in condensed matter system, where they arise as…

Quantum Gases · Physics 2021-09-15 Shuai Li , Maksims Arzamasovs , Hongrong Li , Fuli Li , Bo Liu

Accurate assessment of systematic uncertainties is an increasingly vital task in physics studies, where large, high-dimensional datasets, like those collected at the Large Hadron Collider, hold the key to new discoveries. Common approaches…

Methodology · Statistics 2025-10-02 Alexis Romero , Kyle Cranmer , Daniel Whiteson