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Related papers: A Feynman graph selection tool in GRACE system

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A computer program has been developed which generates Feynman graphs automatically for scattering and decay processes in non-Abelian gauge theory of high-energy physics. A new acceleration method is presented for both generating and…

High Energy Physics - Theory · Physics 2009-10-28 Toshiaki Kaneko

We present python libraries for Feynman graphs manipulation. The key feature of these libraries is usage of generalization of graph representation offered by B. G. Nickel et al. In this approach graph is represented in some unique…

High Energy Physics - Phenomenology · Physics 2014-10-03 D. Batkovich , Yu. Kirienko , M. Kompaniets , S. Novikov

For the study of reactions in High Energy Physics (HEP) automatic computation systems have been developed and are widely used nowadays. GRACE is one of such systems and it has achieved much success in analyzing experimental data. Since we…

High Energy Physics - Phenomenology · Physics 2009-10-31 F. Yuasa , J. Fujimoto , T. Ishikawa , M. Jimbo , T. Kaneko , K. Kato , S. Kawabata , T. Kon , Y. Kurihara , M. Kuroda , N. Nakazawa , Y. Shimizu , H. Tanaka

Algorithm of constructing Feynman amplitudes in the framework of minimal supersymmetic extension of the standard model is presented, which can be easily implemented in GRACE, the program of automatic generation of Feynman amplitudes. The…

High Energy Physics - Phenomenology · Physics 2007-05-23 M. Kuroda

A C-program DIANA (DIagram ANAlyser) for the automatic Feynman diagram evaluation is presented. It consists of two parts: the analyzer of diagrams and the interpreter of a special text manipulating language. This language is used to create…

High Energy Physics - Phenomenology · Physics 2011-01-25 M. Tentyukov , J. Fleischer

A package for drawing publication-quality Feynman diagrams written in GLE is described.

High Energy Physics - Phenomenology · Physics 2022-11-30 A. G. Grozin

Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. However, their immense number of parameters and complex transformer-based architectures result in significant resource…

Databases · Computer Science 2026-04-15 Tianhao Tang , Haoyang Li , Lei Chen

Machine Learning (ML) systems are a building part of the modern tools which impact our daily life in several application domains. Due to their black-box nature, those systems are hardly adopted in application domains (e.g. health, finance)…

Machine Learning · Computer Science 2022-10-24 Mario Alfonso Prado-Romero , Giovanni Stilo

Despite the recent development in the topic of explainable AI/ML for image and text data, the majority of current solutions are not suitable to explain the prediction of neural network models when the datasets are tabular and their features…

Machine Learning · Computer Science 2020-10-27 Thai Le , Suhang Wang , Dongwon Lee

A C-program DIANA (DIagram ANAlyser) for the automatic Feynman diagram evaluation is presented.

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

In Linguistics, a grapheme is a written unit of a writing system corresponding to a phonological sound. In Natural Language Processing tasks, written language is analysed through two different mediums, word analysis, and character analysis.…

Computation and Language · Computer Science 2024-04-03 Samuel Rose , Chandrasekhar Kambhampati

With an integrated software package {\tt GRACE}, it is possible to generate Feynman diagrams, calculate the total cross section and generate physics events automatically. We outline the hybrid method of parallel computation of the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Fukuko Yuasa , Tadashi Ishikawa , Setsuya Kawabata , Denis Perret-Gallix , Kazuhiro Itakura , Yukihiko Hotta , Motoi Okuda

We describe the main building blocks of a generic automated package for the calculation of Feynman diagrams. These blocks include the generation and creation of a model file, the graph generation, the symbolic calculation at an intermediate…

High Energy Physics - Phenomenology · Physics 2008-11-26 G. Belanger , F. Boudjema , J. Fujimoto , T. Ishikawa , T. Kaneko , K. Kato , Y. Shimizu

Applications on inference of biological networks have raised a strong interest in the problem of graph estimation in high-dimensional Gaussian graphical models. To handle this problem, we propose a two-stage procedure which first builds a…

Statistics Theory · Mathematics 2012-02-17 Christophe Giraud , Sylvie Huet , Nicolas Verzelen

This paper proposes a programmable relation extraction method for the English language by parsing texts into semantic graphs. A person can define rules in plain English that act as matching patterns onto the graph representation. These…

Computation and Language · Computer Science 2020-11-06 Alberto Cetoli

We propose the Graph Context Encoder (GCE), a simple but efficient approach for graph representation learning based on graph feature masking and reconstruction. GCE models are trained to efficiently reconstruct input graphs similarly to a…

Machine Learning · Computer Science 2021-06-21 Oriel Frigo , Rémy Brossard , David Dehaene

Grey literature is essential to software engineering research as it captures practices and decisions that rarely appear in academic venues. However, collecting and assessing it at scale remains difficult because of their heterogeneous…

Graph embedding methods transform high-dimensional and complex graph contents into low-dimensional representations. They are useful for a wide range of graph analysis tasks including link prediction, node classification, recommendation and…

Machine Learning · Computer Science 2019-12-03 Bhagya Hettige , Yuan-Fang Li , Weiqing Wang , Wray Buntine

A recent paper by Drewes, Hoffmann, and Minas (GCM 2023 proceedings) has shown that certain graph languages can be defined and efficiently recognized by finite automata when strings over typed symbols are interpreted as graphs. This…

Formal Languages and Automata Theory · Computer Science 2025-03-27 Mattia De Rosa , Mark Minas

We present GLEAM (Galaxy Line Emission & Absorption Modeling), a Python tool for fitting Gaussian models to emission and absorption lines in large samples of 1D extragalactic spectra. GLEAM is tailored to work well in batch mode without…

Instrumentation and Methods for Astrophysics · Physics 2021-03-08 Andra Stroe , Victor-Nicolae Savu
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