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We present a Mathematica package AmpRed for the semi-automatic calculations of multi-loop Feynman amplitudes with high efficiency and precision. AmpRed implements the methods of integration by parts and differential equations in the…

High Energy Physics - Phenomenology · Physics 2025-04-14 Wen Chen

A Mathematica implementation of the program LERG-I is presented that performs the reduction of tensor integrals, encountered in one-loop Feynman diagram calculations, to scalar integrals. The program was originally coded in REDUCE and in…

High Energy Physics - Phenomenology · Physics 2009-10-28 Robin G. Stuart

Variational inference is an increasingly popular method in statistics and machine learning for approximating probability distributions. We developed LINFA (Library for Inference with Normalizing Flow and Annealing), a Python library for…

Machine Learning · Computer Science 2023-07-17 Yu Wang , Emma R. Cobian , Jubilee Lee , Fang Liu , Jonathan D. Hauenstein , Daniele E. Schiavazzi

Manifestly Lorentz covariant Feynman rules are given in terms of a "scalar" field for each helicity, dramatically simplifying the calculation of amplitudes with massless particles. The spinor helicity formalism is properly identified as a…

High Energy Physics - Phenomenology · Physics 2009-10-31 Gordon Chalmers , Warren Siegel

The Hopf algebra structure underlying Feynman diagrams which governs the process of renormalization in perturbative quantum field theory is reviewed. Recent progress is briefly summarized with an emphasis on further directions of research.

High Energy Physics - Theory · Physics 2008-11-26 Kurusch Ebrahimi-Fard , Dirk Kreimer

Organizations have realized the importance of data analysis and its benefits. This in combination with Machine Learning algorithms has allowed to solve problems more easily, making these processes less time-consuming. Neural networks are…

Neural and Evolutionary Computing · Computer Science 2022-04-19 Alvaro J. Garcia-Tejedor , Alberto Nogales

Daany is .NET and cross platform data analytics and linear algebra library written in C# supposed to be a tool for data preparation, feature engineering and other kind of data transformations and feature engineering. The library is…

Software Engineering · Computer Science 2021-07-09 Bahrudin Hrnjica

Numerous computer systems use dynamic control and data structures of unbounded size. These data structures have often the character of trees or they can be encoded as trees with some additional pointers. This is exploited by some currently…

Formal Languages and Automata Theory · Computer Science 2012-04-17 Ondřej Lengál

We introduce the GAMBIT Universal Model Machine (GUM), a tool for automatically generating code for the global fitting software framework GAMBIT, based on Lagrangian-level inputs. GUM accepts models written symbolically in FeynRules and…

FEniCS Mechanics is a Python package to facilitate computational mechanics simulations. The Python library dolfin, from the FEniCS Project, is used to formulate and numerically solve the problem in variational form. The general balance laws…

Computational Engineering, Finance, and Science · Computer Science 2019-01-30 Miguel A. Rodriguez , Christoph M. Augustin , Shawn C. Shadden

This paper studies generalization capabilities of neural networks (NNs) using new and improved PyTorch library Loss Landscape Analysis (LLA). LLA facilitates visualization and analysis of loss landscapes along with the properties of NN…

Machine Learning · Computer Science 2025-02-06 Nikita Gabdullin

A Feynman formula is a representation of a solution of an initial (or initial-boundary) value problem for an evolution equation (or, equivalently, a representation of the semigroup resolving the problem) by a limit of $n$-fold iterated…

Probability · Mathematics 2017-08-09 Yana A. Butko , René L. Schilling , Oleg G. Smolyanov

SModelS is an automatized tool enabling the fast interpretation of simplified model results from the LHC within any model of new physics respecting a $\mathbb{Z}_2$ symmetry. We here present a new version of SModelS that can use the full…

High Energy Physics - Phenomenology · Physics 2021-03-17 Gaël Alguero , Sabine Kraml , Wolfgang Waltenberger

This paper gives a complete selfcontained proof of our result announced in hep-th/9909126 showing that renormalization in quantum field theory is a special instance of a general mathematical procedure of extraction of finite values based on…

High Energy Physics - Theory · Physics 2009-10-31 Alain Connes , Dirk Kreimer

This book focuses on the use of algorithmic high-level synthesis (HLS) to build application-specific FPGA systems. Our goal is to give the reader an appreciation of the process of creating an optimized hardware design using HLS. Although…

Hardware Architecture · Computer Science 2018-05-11 Ryan Kastner , Janarbek Matai , Stephen Neuendorffer

This article describes haggies, a program for the generation of optimised programs for the efficient numerical evaluation of mathematical expressions. It uses a multivariate Horner-scheme and Common Subexpression Elimination to reduce the…

High Energy Physics - Phenomenology · Physics 2014-11-20 Thomas Reiter

We present an open-source tensor network Python library for quantum many-body simulations. At its core is an abelian-symmetric tensor, implemented as a sparse block structure managed by logical layer on top of dense multi-dimensional array…

Strongly Correlated Electrons · Physics 2025-03-05 Marek M. Rams , Gabriela Wójtowicz , Aritra Sinha , Juraj Hasik

We give a concise and pedagogical introduction to Feynman diagrams. After discussing a toy model which requires only undergraduate mathematics, we focus on relativistic quantum field theory. We review the derivation of Feynman rules from…

High Energy Physics - Phenomenology · Physics 2025-01-16 Stefan Weinzierl

We review recent developments in the study of multiple polylogarithms, including the Hopf algebra of the multiple polylogarithms and the symbol map, as well as the construction of single valued multiple polylogarithms and discuss an…

High Energy Physics - Theory · Physics 2019-10-02 Claude Duhr , Falko Dulat

In recent years a Hopf algebraic structure underlying the process of renormalization in quantum field theory was found. It led to a Birkhoff factorization for (regularized) Hopf algebra characters, i.e. for Feynman rules. In this work we…

High Energy Physics - Theory · Physics 2009-09-29 Kurusch Ebrahimi-Fard , Li Guo , Dirk Kreimer
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