Chrome Extension
WeChat Mini Program
Use on ChatGLM

QCD Static Force in Gradient Flow

Journal of High Energy Physics(2022)SCI 2区SCI 1区

Technische Universität München

Cited 6|Views23
Abstract
We review our recent study on the QCD static force using gradient flow at next-to-leading order in the strong coupling. The QCD static force has the advantage of being free of the O (Λ QCD ) renormalon appearing in the static potential but suffers from poor convergence in the lattice QCD computations. It is expected that the gradient flow formalism can improve the convergence. Based on our next-to-leading-order calculations, we explore the properties of the static force for arbitrary flow time t , as well as in the limit t → 0, which may be useful for lattice QCD simulations.
More
Translated text
Key words
NLO Computations
PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
KG WILSON
1974

被引用9530 | 浏览

Brambilla Nora, Excellence Cluster ORIGINS, Müller Daniel,Vairo Antonio
2020

被引用23 | 浏览

Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:本文探讨了使用梯度流在强耦合下的次领先阶计算QCD静态力,提出梯度流方法能够改善其在格点QCD计算中的收敛性。

方法】:通过次领先阶梯度流计算QCD静态力,分析不同流动时间t下静态力的性质。

实验】:文中未提供具体实验细节,但通过理论计算分析得到结果,未提及使用的数据集名称。