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In the wake of the growing popularity of machine learning in particle physics, this work finds a new application of geometric deep learning on Feynman diagrams to make accurate and fast matrix element predictions with the potential to be…

Computational Physics · Physics 2022-11-29 Harrison Mitchell , Alexander Norcliffe , Pietro Liò

The benefits of automating design cycles for Bayesian inference-based algorithms are becoming increasingly recognized by the machine learning community. As a result, interest in probabilistic programming frameworks has much increased over…

Machine Learning · Computer Science 2018-11-12 Marco Cox , Thijs van de Laar , Bert de Vries

We present an application that automatically writes the Helas library corresponding to the Feynman rules of any Lagrangian, renormalizable or not, in quantum field theory. The code, written in Python, takes the Universal FeynRules Output as…

High Energy Physics - Phenomenology · Physics 2012-08-02 Priscila de Aquino , William Link , Fabio Maltoni , Olivier Mattelaer , Tim Stelzer

In this talk we discuss mathematical structures associated to Feynman graphs. Feynman graphs are the backbone of calculations in perturbative quantum field theory. The mathematical structures -- apart from being of interest in their own…

Mathematical Physics · Physics 2009-12-23 Christian Bogner , Stefan Weinzierl

We propose a framework for calculating two-loop Feynman diagrams which appear within a renormalizable theory in the general mass case and at finite external momenta. Our approach is a combination of analytical results and of high accuracy…

High Energy Physics - Phenomenology · Physics 2009-10-30 A. Ghinculov , Y. -P. Yao

We present a user-friendly software for photonic analog quantum computing with an installable MATLAB package and the graphical user interface (GUI) that allows for convenient operation without requiring programming skills. Arbitrary…

Quantum Physics · Physics 2018-10-05 Hao Tang , Yan-Yan Zhu , Jun Gao , Marcus Lee , Peng-Cheng Lai , Xian-Min Jin

Starting from the parametric representation of a Feynman diagram, we obtain it's well defined value in dimensional regularisation by changing the integrals over parameters into contour integrals. That way we eventually arrive at a…

High Energy Physics - Phenomenology · Physics 2007-05-23 K. Knecht , H. Verschelde

We present a Feynman graph selection tool {\tt grcsel}, which is an interpreter written in C language. In the framework of {\tt GRACE}, it enables us to get a subset of Feynman graphs according to given conditions.

High Energy Physics - Phenomenology · Physics 2009-11-07 F. Yuasa , T. Kaneko , T. Ishikawa

This is a simple mathematical introduction into Feynman diagram technique, which is a standard physical tool to write perturbative expansions of path integrals near a critical point of the action. I start from a rigorous treatment of a…

Geometric Topology · Mathematics 2011-09-15 Michael Polyak

xloops is a program package that calculates Feynman diagrams by using computer algebra systems. In this paper it is shown which problems to be solved by computer algebra arise during such calculations, and how this problems are handled in…

High Energy Physics - Phenomenology · Physics 2007-05-23 Lars Brucher

New algebraic approach to analytical calculations of D-dimensional integrals for multi-loop Feynman diagrams is proposed. We show that the known analytical methods of evaluation of multi-loop Feynman integrals, such as integration by parts…

High Energy Physics - Theory · Physics 2010-04-05 A. P. Isaev

This paper is an introduction to the language of Feynman Diagrams. We use Reshetikhin-Turaev graphical calculus to define Feynman diagrams and prove that asymptotic expansions of Gaussian integrals can be written as a sum over a suitable…

Quantum Algebra · Mathematics 2013-09-30 Domenico Fiorenza , Riccardo Murri

A C-program DIANA (DIagram ANAlyser) for the automation of Feynman diagram evaluations is presented.

High Energy Physics - Phenomenology · Physics 2007-05-23 M. Tentyukov , J. Fleischer

In recent years, there has been increasing interest in automatic facial behavior analysis systems from computing communities such as vision, multimodal interaction, robotics, and affective computing. Building upon the widespread utility of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Jiewen Hu , Leena Mathur , Paul Pu Liang , Louis-Philippe Morency

We present SmeftFR, a Mathematica package designed to generate the Feynman rules for the Standard Model Effective Field Theory (SMEFT) including the complete set of gauge invariant operators up to dimension~6. Feynman rules are generated…

High Energy Physics - Phenomenology · Physics 2019-12-02 A. Dedes , M. Paraskevas , J. Rosiek , K. Suxho , L. Trifyllis

We introduce GraSPy, a Python library devoted to statistical inference, machine learning, and visualization of random graphs and graph populations. This package provides flexible and easy-to-use algorithms for analyzing and understanding…

Social and Information Networks · Computer Science 2019-10-25 Jaewon Chung , Benjamin D. Pedigo , Eric W. Bridgeford , Bijan K. Varjavand , Hayden S. Helm , Joshua T. Vogelstein

Last year we released version 2.0 of the Feynman integral reduction program Kira. In this contribution we first report on changes and new features since then and, secondly, on new features for upcoming releases.

High Energy Physics - Phenomenology · Physics 2023-02-23 Fabian Lange , Philipp Maierhöfer , Johann Usovitsch

Programming techniques which extend the capabilities of FeynArts and FormCalc are introduced and explained using examples from real applications.

High Energy Physics - Phenomenology · Physics 2009-11-11 T. Hahn , J. I. Illana

Information about the number of Feynman graphs for a given physical process in a given field theory is especially useful for confirming the result of a Feynman graph generator used in an automatic system of perturbative calculations. A…

High Energy Physics - Phenomenology · Physics 2018-11-13 T. Kaneko

The LanHEP program for Feynman rules generation in momentum representation is presented. It reads the Lagrangian written in a compact form, close to the one used in publications. It means that Lagrangian terms can be written with summation…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. V. Semenov
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