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Related papers: Algorithm FIRE -- Feynman Integral REduction

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We present a novel benchmark application of a quantum algorithm to Feynman loop integrals. The two on-shell states of a Feynman propagator are identified with the two states of a qubit and a quantum algorithm is used to unfold the causal…

High Energy Physics - Phenomenology · Physics 2022-06-01 Selomit Ramírez-Uribe , Andrés E. Rentería-Olivo , Germán Rodrigo , German F. R. Sborlini , Luiz Vale Silva

Up to the moment there are two known algorithms of sector decomposition: an original private algorithm of Binoth and Heinrich and an algorithm made public lastyear by Bogner and Weinzierl. We present a new program performing the sector…

High Energy Physics - Phenomenology · Physics 2009-03-24 A. V. Smirnov , M. N. Tentyukov

The program FeynRules is a Mathematica package developed to facilitate the implementation of new physics theories into high-energy physics tools. Starting from a minimal set of information such as the model gauge symmetries, its particle…

High Energy Physics - Phenomenology · Physics 2014-06-13 Adam Alloul , Neil D. Christensen , Celine Degrande , Claude Duhr , Benjamin Fuks

We present a new interface called FeynHelpers that connects FeynCalc, a Mathematica package for symbolic semi-automatic evaluation of Feynman diagrams and calculations in quantum field theory (QFT) to Package-X and FIRE. The former provides…

Computational Physics · Physics 2018-01-30 Vladyslav Shtabovenko

A new method of divergence subtraction in Feynman parametric integrals is presented. The method is suitable for calculating the lepton anomalous magnetic moments (AMM) in quantum electrodynamics (QED). The subtraction procedure eliminates…

High Energy Physics - Phenomenology · Physics 2022-09-07 Sergey Volkov

We provide algorithms for symbolic integration of hyperlogarithms multiplied by rational functions, which also include multiple polylogarithms when their arguments are rational functions. These algorithms are implemented in Maple and we…

High Energy Physics - Theory · Physics 2015-01-06 Erik Panzer

We present algorithms to work with iterated Eisenstein integrals that have recently appeared in the computation of multi-loop Feynman integrals. These algorithms allow one to analytically continue these integrals to all regions of the…

High Energy Physics - Theory · Physics 2020-03-18 Claude Duhr , Lorenzo Tancredi

Over the last year significant progress was made in the understanding of the computation of Feynman integrals using differential equations. These lectures give a review of these developments, while not assuming any prior knowledge of the…

High Energy Physics - Phenomenology · Physics 2015-06-23 Johannes M. Henn

This work investigates in detail the performance and advantages of a new quantum Monte Carlo integrator, dubbed Quantum Fourier Iterative Amplitude Estimation (QFIAE), to numerically evaluate for the first time loop Feynman integrals in a…

High Energy Physics - Phenomenology · Physics 2024-11-20 Jorge J. Martínez de Lejarza , Leandro Cieri , Michele Grossi , Sofia Vallecorsa , Germán Rodrigo

We describe how Groebner bases can be used to solve the reduction problem for Feynman integrals, i.e. to construct an algorithm that provides the possibility to express a Feynman integral of a given family as a linear combination of some…

High Energy Physics - Lattice · Physics 2009-11-11 A. V. Smirnov , V. A. Smirnov

This document is a contribution to the proceedings of the MathemAmplitudes 2019 conference held in December 2019 in Padova, Italy. A key step in modern high energy physics scattering amplitudes computation is to express the latter in terms…

High Energy Physics - Phenomenology · Physics 2021-02-03 Hjalte Frellesvig , Luca Mattiazzi

Using integration by parts relations, Feynman integrals can be represented in terms of coupled systems of differential equations. In the following we suppose that the unknown Feynman integrals can be given in power series representations,…

Symbolic Computation · Computer Science 2016-08-19 Jakob Ablinger , Arnd Behring , Johannes Bluemlein , Abilio de Freitas , Carsten Schneider

Deep neural networks trained on nonstationary data must balance stability (i.e., retaining prior knowledge) and plasticity (i.e., adapting to new tasks). Standard reinitialization methods, which reinitialize weights toward their original…

Machine Learning · Computer Science 2026-04-02 Isaac Han , Sangyeon Park , Seungwon Oh , Donghu Kim , Hojoon Lee , Kyung-Joong Kim

The demand for precision predictions in the field of high energy physics has dramatically increased over recent years. Experiments conducted at the LHC, as well as precision measurements at the intensity frontier such as Belle II require…

High Energy Physics - Phenomenology · Physics 2022-09-28 Marvin Gerlach , Florian Herren , Martin Lang

This paper provides technical details regarding the application of the FLAME methodology to derive algorithms hand in hand with their proofs of correctness for the computation of the $ L T L^T $ decomposition (with and without pivoting) of…

Mathematical Software · Computer Science 2025-04-11 Robert van de Geijn , Maggie Myers , RuQing G. Xu , Devin Matthews

In modern quantum field theory, one of the most important tasks is the calculation of loop integrals. Loop integrals appear when evaluating the Feynman diagrams with one or more loops by integrating over the internal momenta. Even though…

High Energy Physics - Theory · Physics 2020-06-24 Maxim Bezuglov

The FLAME methodology makes it possible to derive provably correct algorithms from a formal description of a linear algebra problem. So far, the methodology has been successfully used to automate the derivation of direct algorithms such as…

Numerical Analysis · Computer Science 2018-03-28 Henrik Barthels

We describe a strategy to solve differential equations for Feynman integrals by powers series expansions near singular points and to obtain high precision results for the corresponding master integrals. We consider Feynman integrals with…

High Energy Physics - Phenomenology · Physics 2018-04-04 Roman N. Lee , Alexander V. Smirnov , Vladimir A. Smirnov

Nature-inspired metaheuristic algorithms, especially those based on swarm intelligence, have attracted much attention in the last ten years. Firefly algorithm appeared in about five years ago, its literature has expanded dramatically with…

Optimization and Control · Mathematics 2013-08-20 Xin-She Yang , Xingshi He

The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved…

Neural and Evolutionary Computing · Computer Science 2013-12-24 Iztok Fister , Iztok Fister , Xin-She Yang , Janez Brest
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