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We present preliminary results on the determination of spin-dependent, or polarised, Parton Distribution Functions (PDFs) from all relevant inclusive polarised DIS data. The analysis is performed within the NNPDF approach, which provides a…

高能物理 - 唯象学 · 物理学 2012-06-26 Emanuele R. Nocera , Stefano Forte , Giovanni Ridolfi , Juan Rojo

Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, offer compact and effective alternatives to full model fine-tuning by introducing low-rank updates to pre-trained weights. However, most existing approaches rely on global low…

机器学习 · 计算机科学 2025-09-25 Babak Barazandeh , Subhabrata Majumdar , Om Rajyaguru , George Michailidis

The Fortran LHAPDF library has been a long-term workhorse in particle physics, providing standardised access to parton density functions for experimental and phenomenological purposes alike, following on from the venerable PDFLIB package.…

高能物理 - 唯象学 · 物理学 2015-06-23 Andy Buckley , James Ferrando , Stephen Lloyd , Karl Nordstrom , Ben Page , Martin Ruefenacht , Marek Schoenherr , Graeme Watt

The xPDFsuite software program is described. It is for processing and analyzing atomic pair distribution functions (PDF) from X-ray powder diffraction data. It provides a convenient GUI for SrXplanr and PDFgetX3, allowing the users to…

材料科学 · 物理学 2015-02-25 Xiaohao Yang , Pavol Juhas , Christopher L. Farrow , Simon J. L. Billinge

Fine-tuning large-scale pre-trained models is inherently a resource-intensive task. While it can enhance the capabilities of the model, it also incurs substantial computational costs, posing challenges to the practical application of…

计算与语言 · 计算机科学 2024-06-27 Yulong Mao , Kaiyu Huang , Changhao Guan , Ganglin Bao , Fengran Mo , Jinan Xu

We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators. PDFs are essential for the calculation of particle physics observables through Monte Carlo…

高能物理 - 唯象学 · 物理学 2021-05-19 Stefano Carrazza , Juan M. Cruz-Martinez , Marco Rossi

We present a new set of parton distributions, NNPDF3.1, which updates NNPDF3.0, the first global set of PDFs determined using a methodology validated by a closure test. The update is motivated by recent progress in methodology and available…

Parameter-efficient fine-tuning (PEFT) is a flexible and efficient method for adapting large language models (LLMs) to downstream tasks. Among these methods, weight-decomposed low-rank adaptation (DoRA) is a promising approach that…

机器学习 · 计算机科学 2025-08-05 Peijia Qin , Ruiyi Zhang , Pengtao Xie

We present PDFFlow, a new software for fast evaluation of parton distribution functions (PDFs) designed for platforms with hardware accelerators. PDFs are essential for the calculation of particle physics observables through Monte Carlo…

高能物理 - 唯象学 · 物理学 2020-12-16 Marco Rossi , Stefano Carrazza , Juan M. Cruz-Martinez

Using parton density functions (PDFs) with threshold-resummation improvement, we consistently calculate higgsino/gaugino and slepton pair production at next-to-leading order and next-to-leading logarithmic accuracy at the LHC. The smaller…

高能物理 - 唯象学 · 物理学 2019-09-16 J. Fiaschi , M. Klasen

Parton distribution functions (PDFs) at large $x$ are challenging to extract from experimental data, yet they are essential for understanding hadron structure and searching for new physics beyond the Standard Model. Within the framework of…

高能物理 - 唯象学 · 物理学 2025-03-03 Xiangdong Ji , Yizhuang Liu , Yushan Su , Rui Zhang

We study the one-point probability distribution function (PDF) for matter density averaged over spherical cells. The leading part to the PDF is defined by spherical collapse dynamics, whereas the next-to-leading part comes from the…

宇宙学与河外天体物理 · 物理学 2023-08-08 Anton Chudaykin , Mikhail M. Ivanov , Sergey Sibiryakov

We study the probability distribution function (PDF) of the order parameter of the three-dimensional $O(N)$ model at criticality using the functional renormalisation group. For this purpose, we generalize the method introduced in [Balog et…

统计力学 · 物理学 2025-03-28 Adam Rançon , Bertrand Delamotte , Lovro Šaravanja , Ivan Balog

Representing the parton distribution functions (PDFs) of the proton and other hadrons through flexible, high-fidelity parametrizations has been a long-standing goal of particle physics phenomenology. This is particularly true since the…

高能物理 - 唯象学 · 物理学 2024-06-21 Brandon Kriesten , T. J. Hobbs

Parameter-efficient fine-tuning (PEFT) is a popular method for tailoring pre-trained large language models (LLMs), especially as the models' scale and the diversity of tasks increase. Low-rank adaptation (LoRA) is based on the idea that the…

计算与语言 · 计算机科学 2025-05-27 Pengjie Ren , Chengshun Shi , Shiguang Wu , Mengqi Zhang , Zhaochun Ren , Maarten de Rijke , Zhumin Chen , Jiahuan Pei

This document is intended as a study of benchmark cross sections at the LHC (at 7 TeV) at NLO using modern parton distribution functions currently available from the 6 PDF fitting groups that have participated in this exercise. It also…

Parameter-efficient fine-tuning (PEFT) has become increasingly important as foundation models continue to grow in both popularity and size. Adapter has been particularly well-received due to their potential for parameter reduction and…

计算机视觉与模式识别 · 计算机科学 2024-06-07 Minglei Li , Peng Ye , Yongqi Huang , Lin Zhang , Tao Chen , Tong He , Jiayuan Fan , Wanli Ouyang

We introduce a generalized definition of parton distribution functions (PDFs) for a more consistent all-order treatment of power corrections. We present a new set of modified DGLAP evolution equations for nuclear PDFs, and show that the…

高能物理 - 唯象学 · 物理学 2008-11-26 Zhong-Bo Kang , Jian-Wei Qiu

A general spherical harmonics method is described for extracting anisotropic pair distribution functions (PDF) in this work. In the structural study of functional crystallized materials, the investigation of the local structures under the…

材料科学 · 物理学 2022-07-05 Guanjie Zhang , Hui Liu , Jun Chen , He Lin , Nan Zhang

Principal component analysis (PCA) for binary data, known as logistic PCA, has become a popular alternative to dimensionality reduction of binary data. It is motivated as an extension of ordinary PCA by means of a matrix factorization, akin…

机器学习 · 统计学 2020-09-08 Andrew J. Landgraf , Yoonkyung Lee