中文
相关论文

相关论文: PDFFlow: parton distribution functions on GPU

200 篇论文

The formula for probability density functions (PDFs) has been extended to include PDF for energy dissipation rates in addition to other PDFs such as for velocity fluctuations, velocity derivatives, fluid particle accelerations, energy…

统计力学 · 物理学 2009-11-11 T. Arimitsu , N. Arimitsu

Several groups have recently investigated the flow of information in high-energy collisions, from the entanglement entropy of the proton yielding classical Shannon entropy of its parton distribution functions (pdfs), through jet splitting…

高能物理 - 唯象学 · 物理学 2023-08-11 Guillermo Benito-Calviño , Javier García-Olivares , Felipe J. Llanes-Estrada

Mesoscopic simulations of hydrocarbon flow in source shales are challenging, in part due to the heterogeneous shale pores with sizes ranging from a few nanometers to a few micrometers. Additionally, the sub-continuum fluid-fluid and…

We present the first open-source analysis of parton distribution functions (PDFs) of charged pions using xFitter, an open-source QCD fit framework to facilitate PDF extraction and analyses. Our calculations are implemented at…

In this article we present a review of the structure of the proton and the current status of our knowledge of the parton distribution functions (PDFs). The lepton-nucleon scattering experiments which provide the main constraints in PDF…

高能物理 - 实验 · 物理学 2013-03-20 Emmanuelle Perez , Eram Rizvi

A clear understanding of nuclear parton distribution functions (nPDFs) plays a crucial role in the interpretation of collider data taken at the Relativistic Heavy Ion Collider (RHIC), the Large Hadron Collider (LHC) and in the near future…

高能物理 - 唯象学 · 物理学 2022-07-13 P. Duwentäster , T. Ježo , M. Klasen , K. Kovařík , A. Kusina , K. F. Muzakka , F. I. Olness , R. Ruiz , I. Schienbein , J. Y. Yu

We present the MCscales approach for incorporating scale uncertainties in parton distribution functions (PDFs). The new methodology builds on the Monte Carlo sampling for propagating experimental uncertainties into the PDF space that…

高能物理 - 唯象学 · 物理学 2023-03-27 Zahari Kassabov , Maria Ubiali , Cameron Voisey

TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of…

Quantum electrodynamics and electroweak corrections are important ingredients for many theoretical predictions at the LHC. This paper documents APFEL, a new PDF evolution package that allows for the first time to perform DGLAP evolution up…

高能物理 - 唯象学 · 物理学 2015-06-17 Valerio Bertone , Stefano Carrazza , Juan Rojo

An important limitation in current fits of parton distribution functions (PDFs) is that PDF uncertainties do not include any source of theoretical uncertainty. Here we present a general method for incorporating theoretical uncertainties…

高能物理 - 唯象学 · 物理学 2018-10-05 R. L. Pearson , C. Voisey

We survey some of the recent developments in the extraction and application of heavy quark Parton Distribution Functions (PDFs). We also highlight some of the key HERA measurements which have contributed to these advances.

高能物理 - 唯象学 · 物理学 2015-06-03 K. Kovarik , T. Stavreva , A. Kusina , T. Jezo , F. I. Olness , I. Schienbein , J. Y. Yu

Nuclear parton distribution functions (nPDFs) can be determined in a global QCD analysis using a wide range of experimental data. In addition to older fixed-target deep inelastic scattering and Drell-Yan (DY) dilepton production data,…

高能物理 - 唯象学 · 物理学 2022-07-12 Ilkka Helenius , Marina Walt , Werner Vogelsang

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high-level abstractions for the design and training of both…

Large-scale deep learning benefits from an emerging class of AI accelerators. Some of these accelerators' designs are general enough for compute-intensive applications beyond AI and Cloud TPU is one such example. In this paper, we…

分布式、并行与集群计算 · 计算机科学 2019-11-19 Kun Yang , Yi-Fan Chen , Georgios Roumpos , Chris Colby , John Anderson

We present LO, NLO and NNLO sets of parton distribution functions (PDFs) of the proton determined from global analyses of the available hard scattering data. These MMHT2014 PDFs supersede the `MSTW2008' parton sets, but are obtained within…

高能物理 - 唯象学 · 物理学 2015-06-11 L. A. Harland-Lang , A. D. Martin , P. Motylinski , R. S. Thorne

In this talk, we present our recent next-to-leading order (NLO) nuclear parton distribution functions (nPDFs), which we call EPS09. As an extension to earlier NLO analyses, we supplement the deep inelastic scattering and Drell-Yan dilepton…

高能物理 - 唯象学 · 物理学 2009-11-18 Kari J. Eskola , Hannu Paukkunen , Carlos A. Salgado

SUePDF is a graphic-user-interface program written in MATLAB to achieve quantitative pair distribution functions (PDF) from electron diffraction data. The program facilitates the structural studies of amorphous materials and small…

材料科学 · 物理学 2017-08-24 Dung Trung Tran , Gunnar Svensson , Cheuk-Wai Tai

We study the gluon parton densities [parton distribution functions (PDFs), transverse momentum distributions (TMDs), generalized parton distributions (GPDs)] and form factors in soft-wall AdS/QCD. We show that the power behavior of gluon…

高能物理 - 唯象学 · 物理学 2021-05-18 Valery E. Lyubovitskij , Ivan Schmidt

Using realistic quark propagators and meson Bethe-Salpeter amplitudes based on the Dyson-Schwinger equations, we calculate the pion and kaon's valence parton distribution functions (PDF) through the modified impulse approximation. The PDFs…

核理论 · 物理学 2018-10-03 Chao Shi , Cedric Mezrag , Hong-shi Zong

We introduce SurfFlow, an open-source high-throughput workflow package designed for automated first-principles calculations of surface energies in arbitrary crystals. Our package offers a comprehensive solution capable of handling…

材料科学 · 物理学 2023-11-07 Firat Yalcin , Michael Wolloch