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Large formal mathematical libraries consist of millions of atomic inference steps that give rise to a corresponding number of proved statements (lemmas). Analogously to the informal mathematical practice, only a tiny fraction of such…

Artificial Intelligence · Computer Science 2014-02-17 Cezary Kaliszyk , Josef Urban

Computing the full Hessian matrix -- the matrix of second-order derivatives for an entire Large Language Model (LLM) is infeasible due to its sheer size. In this technical report, we aim to provide a comprehensive guide on how to accurately…

Machine Learning · Computer Science 2025-04-08 Ivan Ilin

Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Since its introduction, it has been one of the most used CPU and GPU mathematical compilers -…

Symbolic Computation · Computer Science 2016-05-10 The Theano Development Team , Rami Al-Rfou , Guillaume Alain , Amjad Almahairi , Christof Angermueller , Dzmitry Bahdanau , Nicolas Ballas , Frédéric Bastien , Justin Bayer , Anatoly Belikov , Alexander Belopolsky , Yoshua Bengio , Arnaud Bergeron , James Bergstra , Valentin Bisson , Josh Bleecher Snyder , Nicolas Bouchard , Nicolas Boulanger-Lewandowski , Xavier Bouthillier , Alexandre de Brébisson , Olivier Breuleux , Pierre-Luc Carrier , Kyunghyun Cho , Jan Chorowski , Paul Christiano , Tim Cooijmans , Marc-Alexandre Côté , Myriam Côté , Aaron Courville , Yann N. Dauphin , Olivier Delalleau , Julien Demouth , Guillaume Desjardins , Sander Dieleman , Laurent Dinh , Mélanie Ducoffe , Vincent Dumoulin , Samira Ebrahimi Kahou , Dumitru Erhan , Ziye Fan , Orhan Firat , Mathieu Germain , Xavier Glorot , Ian Goodfellow , Matt Graham , Caglar Gulcehre , Philippe Hamel , Iban Harlouchet , Jean-Philippe Heng , Balázs Hidasi , Sina Honari , Arjun Jain , Sébastien Jean , Kai Jia , Mikhail Korobov , Vivek Kulkarni , Alex Lamb , Pascal Lamblin , Eric Larsen , César Laurent , Sean Lee , Simon Lefrancois , Simon Lemieux , Nicholas Léonard , Zhouhan Lin , Jesse A. Livezey , Cory Lorenz , Jeremiah Lowin , Qianli Ma , Pierre-Antoine Manzagol , Olivier Mastropietro , Robert T. McGibbon , Roland Memisevic , Bart van Merriënboer , Vincent Michalski , Mehdi Mirza , Alberto Orlandi , Christopher Pal , Razvan Pascanu , Mohammad Pezeshki , Colin Raffel , Daniel Renshaw , Matthew Rocklin , Adriana Romero , Markus Roth , Peter Sadowski , John Salvatier , François Savard , Jan Schlüter , John Schulman , Gabriel Schwartz , Iulian Vlad Serban , Dmitriy Serdyuk , Samira Shabanian , Étienne Simon , Sigurd Spieckermann , S. Ramana Subramanyam , Jakub Sygnowski , Jérémie Tanguay , Gijs van Tulder , Joseph Turian , Sebastian Urban , Pascal Vincent , Francesco Visin , Harm de Vries , David Warde-Farley , Dustin J. Webb , Matthew Willson , Kelvin Xu , Lijun Xue , Li Yao , Saizheng Zhang , Ying Zhang

Various fields of science and engineering rely on linear algebra for large scale data analysis, modeling and simulation, machine learning, and other applied problems. Linear algebra computations often dominate the execution time of such…

Mathematical Software · Computer Science 2014-08-07 Boyana Norris , Sa-Lin Bernstein , Ramya Nair , Elizabeth Jessup

I describe a mathematical framework for the efficient processing of the very large sets of Feynman diagrams contributing to the scattering of many particles. I reexpress the established numerical methods for the recursive construction of…

High Energy Physics - Phenomenology · Physics 2023-07-21 Thorsten Ohl

In this paper we present an exact finite-length analysis of frameless ALOHA that is obtained through a dynamical programming approach. Monte Carlo simulations are performed in order to verify the analysis. Two examples are provided that…

Information Theory · Computer Science 2016-11-22 Francisco Lázaro , Čedomir Stefanović

In a recent paper \cite{ft} a new powerful method to calculate Feynman diagrams was proposed. It consists in setting up a Taylor series expansion in the external momenta squared. The Taylor coefficients are obtained from the original…

High Energy Physics - Phenomenology · Physics 2016-09-01 J. Fleischer , O. V. Tarasov

Graph domain adaptation has emerged as a promising approach to facilitate knowledge transfer across different domains. Recently, numerous models have been proposed to enhance their generalization capabilities in this field. However, there…

Machine Learning · Computer Science 2025-03-14 Zhen Zhang , Meihan Liu , Bingsheng He

We present MadAnalysis 5, an analysis package dedicated to phenomenological studies of simulated collisions occurring in high-energy physics experiments. Within this framework, users are invited, through a user-friendly Python interpreter,…

High Energy Physics - Phenomenology · Physics 2015-05-27 Eric Conte , Béranger Dumont , Benjamin Fuks , Thibaut Schmitt

We argue that the Mellin-Barnes representations of Feynman diagrams can be used for obtaining linear systems of homogeneous differential equations for the original Feynman diagrams with arbitrary powers of propagators without recourse to…

High Energy Physics - Theory · Physics 2015-06-05 Mikhail Yu. Kalmykov , Bernd A. Kniehl

The Higgs discovery and the lack of any other hint for new physics favor a description of non-standard Higgs physics in terms of an effective field theory. We present an implementation of a general Higgs effective Lagrangian containing…

High Energy Physics - Phenomenology · Physics 2014-04-29 Adam Alloul , Benjamin Fuks , Veronica Sanz

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 introduce a tensor network library designed for classical and quantum physics simulations called Cytnx (pronounced as sci-tens). This library provides almost an identical interface and syntax for both C++ and Python, allowing users to…

Mathematical Software · Computer Science 2025-03-19 Kai-Hsin Wu , Chang-Teng Lin , Ke Hsu , Hao-Ti Hung , Manuel Schneider , Chia-Min Chung , Ying-Jer Kao , Pochung Chen

Recently proposed Feynman-diagram (FD) gauge propagator for massless and massive gauge bosons is obtained from a light-cone (LC) gauge propagator, by choosing the gauge vector along the opposite direction of the gauge boson three-momentum.…

High Energy Physics - Phenomenology · Physics 2023-11-21 Junmou Chen , Kaoru Hagiwara , Junichi Kanzaki , Kentarou Mawatari , Ya-Juan Zheng

Distributed, large-scale quantum computing will need architectures that combine matter-based qubits with photonic links, but today's software stacks target either gate-based chips or linear-optical devices in isolation. We introduce Optyx,…

We present new versions of the Mathematica package FeynCalc and the FeynHelpers add-on that represent an important contribution to the collection of public codes for semi-automatic evaluation of multiloop Feynman diagrams. FeynHelpers…

High Energy Physics - Phenomenology · Physics 2025-12-24 Vladyslav Shtabovenko

PyArmadillo is a linear algebra library for the Python language, with the aim of closely mirroring the programming interface of the widely used Armadillo C++ library, which in turn is deliberately similar to Matlab. PyArmadillo hence…

Mathematical Software · Computer Science 2021-10-22 Jason Rumengan , Terry Yue Zhuo , Conrad Sanderson

Our goal in this paper is to present a generalization of the spectral zeta regularization for general Feynman amplitudes. Our method uses complex powers of elliptic operators but involves several complex parameters in the spirit of the…

Mathematical Physics · Physics 2017-12-12 Nguyen Viet Dang , Bin Zhang

Fully Homomorphic Encryption (FHE) refers to a set of encryption schemes that allow computations to be applied directly on encrypted data without requiring a secret key. This enables novel application scenarios where a client can safely…

Machine Learning · Computer Science 2018-10-02 Roshan Dathathri , Olli Saarikivi , Hao Chen , Kim Laine , Kristin Lauter , Saeed Maleki , Madanlal Musuvathi , Todd Mytkowicz

This paper introduces PyGAD, an open-source easy-to-use Python library for building the genetic algorithm. PyGAD supports a wide range of parameters to give the user control over everything in its life cycle. This includes, but is not…

Neural and Evolutionary Computing · Computer Science 2021-06-14 Ahmed Fawzy Gad