NNPDF

NNPDF是用于识别部分子分布函数（英语：parton distribution functions）的首字母缩写词。

NNPDF

开发者	The NNPDF Collaboration
类型	粒子物理
网站	nnpdf.hepforge.org

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NNPDF is the acronym used to identify the parton distribution functions from the NNPDF Collaboration. NNPDF parton densities are extracted from global fits to data based on a combination of a Monte Carlo method for uncertainty estimation and the use of neural networks as basic interpolating functions.

Methodology

The NNPDF Collaboration strategy is summarized in this diagram.

NNPDF途径可以分为四个主要步骤：

• The generation of a large sample of Monte Carlo replicas of the original experimental data, in a way that central values, errors and correlations are reproduced with enough accuracy.
• The training (minimization of the $\chi ^{2}$) of a set of PDFs parametrized by neural networks on each of the above MC replicas of the data. PDFs are parametrized at the initial evolution scale $Q_{0}^{2}$ and then evolved to the experimental data scale $Q^{2}$ by means of the DGLAP equations. Since the PDF parametrization is redundant, the minimization strategy is based in genetic algorithms as well as gradient descent based minimizers.
• The neural network training is stopped dynamically before entering into the overlearning regime, that is, so that the PDFs learn the physical laws which underlie experimental data without fitting simultaneously statistical noise.
• Once the training of the MC replicas has been completed, a set of statistical estimators can be applied to the set of PDFs, in order to assess the statistical consistency of the results. For example, the stability with respect PDF parametrization can be explicitly verified.

The set of $N_{rep}$ PDF sets (trained neural networks) provides a representation of the underlying PDF probability density, from which any statistical estimator can be computed.

示例

• 
  NNPDF1.0 胶子

版本

NNPDF各版本：

PDF set	DIS 数据	Drell-Yan 数据	Jet 数据	LHC 数据	独立$s$和${\bar {s}}$参数	重夸克质量	NNLO
NNPDF3.1 （页面存档备份，存于互联网档案馆）	是	是	是	是	是	是	是
NNPDF3.0 （页面存档备份，存于互联网档案馆）	是	是	是	是	是	是	是
NNPDF2.3 （页面存档备份，存于互联网档案馆）	是	是	是	是	是	是	是
NNPDF2.2 （页面存档备份，存于互联网档案馆）	是	是	是	是	是	是	是
NNPDF2.1 （页面存档备份，存于互联网档案馆）	是	是	是	否	是	是	是
NNPDF2.0 （页面存档备份，存于互联网档案馆）	是	是	是	否	是	否	否
NNPDF1.2 （页面存档备份，存于互联网档案馆）	是	否	否	否	是	否	否
NNPDF1.0 （页面存档备份，存于互联网档案馆）	是	否	否	否	否	否	否

所有PDF集都可通过LHAPDF界面和NNPDF网页 （页面存档备份，存于互联网档案馆）获得。

外部链接

• The NNPDF Collaboration 主页 （页面存档备份，存于互联网档案馆）
• Download NNPDF Parton Distribution sets
• The NNPDF1.0 analysis （页面存档备份，存于互联网档案馆）
• The NNPDF Non-Singlet analysis （页面存档备份，存于互联网档案馆）
• NNPDF3.1 release （页面存档备份，存于互联网档案馆）
• NNPDF latest fitting code （页面存档备份，存于互联网档案馆）
• The LHAPDF interface （页面存档备份，存于互联网档案馆）