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Large Language Models (LLMs) have intensified the need for low-precision formats that enable efficient, large-scale inference. The Open Compute Project (OCP) Microscaling (MX) standard is attractive due to its favorable hardware efficiency,…

Modern AI hardware, such as Nvidia's Blackwell architecture, is increasingly embracing low-precision floating-point (FP) formats to handle the pervasive activation outliers in Large Language Models (LLMs). Despite this industry trend, a…

Machine Learning · Computer Science 2025-10-30 Mengzhao Chen , Meng Wu , Hui Jin , Zhihang Yuan , Jing Liu , Chaoyi Zhang , Yunshui Li , Jie Huang , Jin Ma , Zeyue Xue , Zhiheng Liu , Xingyan Bin , Ping Luo

In this paper we present a new release of the FIESTA program (Feynman Integral Evaluation by a Sector decomposiTion Approach). FIESTA5 is performance-oriented - we implemented improvements of various kinds in order to make Feynman integral…

High Energy Physics - Phenomenology · Physics 2022-05-18 A. V. Smirnov , N. D. Shapurov , L. I. Vysotsky

While Monte Carlo event generators like WHIZARD have become indispensable tools in studying the impact of new physics on collider observables over the last decades, the implementation of new models in such packages has remained a rather…

High Energy Physics - Phenomenology · Physics 2012-05-09 Neil D. Christensen , Claude Duhr , Benjamin Fuks , Juergen Reuter , Christian Speckner

We present the manual for FeynMaster 2.1, a multitasking software for particle physics studies. This new version includes additional functions and is compatible with recent versions of related software. It can be downloaded in…

High Energy Physics - Phenomenology · Physics 2025-04-03 Duarte Fontes , Jorge C. Romão

We present the Feynman integral reduction program Kira 1.2 and describe its new features and other changes w.r.t. the previous versions. The main new features include a much faster equation generator, more flexible seed specification…

High Energy Physics - Phenomenology · Physics 2018-12-05 Philipp Maierhöfer , Johann Usovitsch

Tensor Networks have emerged as a prominent alternative to neural networks for addressing Machine Learning challenges in foundational sciences, paving the way for their applications to real-life problems. This paper introduces tn4ml, a…

We compute the complete one-loop renormalization group equations (RGEs) for all the four-fermion operators at dimension-8 Standard Model Effective Field Theory (SMEFT). We adopt the on-shell framework, where the RGEs are obtained from the…

High Energy Physics - Phenomenology · Physics 2025-12-29 Chao Wu , Ming-Lei Xiao , Jiang-Hao Yu , Yu-Hui Zheng

FORM, a symbolic manipulation system, has been widely used in a lot of calculations for High Energy Physics due to its high performance and fficient design. Mathematica, another computational software program, has also widely been used, but…

High Energy Physics - Phenomenology · Physics 2012-12-18 Feng Feng , Rolf Mertig

We present a new FORM program for analytically evaluating four-loop massless propagator-type Feynman integrals in an efficient way. Our program Forcer implements parametric reductions of the aforementioned class of Feynman integrals into a…

High Energy Physics - Phenomenology · Physics 2016-07-26 T. Ueda , B. Ruijl , J. A. M. Vermaseren

We present here the most recent version of FermiQCD, a collection of C++ classes, functions and parallel algorithms for lattice QCD, based on Matrix Distributed Processing. FermiQCD allows fast development of parallel lattice applications…

High Energy Physics - Lattice · Physics 2015-06-25 Massimo Di Pierro

Existing low-bit Microscaling (MX) formats, such as MXFP4, often suffer from substantial accuracy degradation due to the use of a shared scaling factor with the Power-of-Two format. In this work, we explore strategies that introduce minimal…

Hardware Architecture · Computer Science 2026-01-29 Weiming Hu , Zihan Zhang , Haoyan Zhang , Chen Zhang , Cong Guo , Yu Feng , Tianchi Hu , Guanglin Li , Guipeng Hu , Junsong Wang , Jingwen Leng

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

The SMEFTsim package is designed to enable automated computations in the Standard Model Effective Field Theory (SMEFT), where the SM Lagrangian is extended with a complete basis of dimension six operators. It contains a set of models…

High Energy Physics - Phenomenology · Physics 2021-08-19 Ilaria Brivio

We report on the new functionality of the open-source Mathematica package FeynCalc relevant for multiloop calculations. In particular, we focus on such tasks as topology identification by means of the Pak algorithm, search for equivalent…

High Energy Physics - Phenomenology · Physics 2021-12-30 Vladyslav Shtabovenko

In this paper, a new communication-efficient federated learning (FL) framework is proposed, inspired by vector quantized compressed sensing. The basic strategy of the proposed framework is to compress the local model update at each device…

Information Theory · Computer Science 2023-07-04 Yongjeong Oh , Yo-Seb Jeon , Mingzhe Chen , Walid Saad

We consider mixed four-point correlators of 1/2-BPS operators $\phi_{k}$ in SCFTs with eight real Poincar\'e supercharges, namely the 3d $\mathcal{N}=4$, 4d $\mathcal{N}=2$, 5d $\mathcal{N}=1$, and 6d $\mathcal{N}=(1,0)$ theories. Using the…

High Energy Physics - Theory · Physics 2026-04-13 Mitchell Woolley

In this paper, we present version 2.0 of cashocs. Our software automates the solution of PDE constrained optimization problems for shape optimization and optimal control. Since its inception, many new features and useful tools have been…

Optimization and Control · Mathematics 2025-10-14 Sebastian Blauth

As cutting-edge large language models (LLMs) continue to transform various industries, their fast-growing model size and sequence length have led to memory traffic and capacity challenges. Recently, AMD, Arm, Intel, Meta, Microsoft, NVIDIA,…

Hardware Architecture · Computer Science 2024-12-31 Yun-Chen Lo , Gu-Yeon Wei , David Brooks

The NeuroEvolution of Augmenting Topologies (NEAT) algorithm has received considerable recognition in the field of neuroevolution. Its effectiveness is derived from initiating with simple networks and incrementally evolving both their…

Neural and Evolutionary Computing · Computer Science 2025-04-14 Lishuang Wang , Mengfei Zhao , Enyu Liu , Kebin Sun , Ran Cheng