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Developer(s) | The NNPDF Collaboration |
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Stable release | 4.0
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Type | Particle physics |
Website | nnpdf |
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.
The NNPDF approach can be divided into four main steps:
The set of PDF sets (trained neural networks) provides a representation of the underlying PDF probability density, from which any statistical estimator can be computed.
The image below shows the gluon at small-x from the NNPDF1.0 analysis, available through the LHAPDF interface
The NNPDF releases are summarised in the following table:
PDF set | DIS data | Drell-Yan data | Jet data | LHC data | Independent param. of and | Heavy Quark masses | NNLO |
---|---|---|---|---|---|---|---|
NNPDF4.0 | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
NNPDF3.1 | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
NNPDF3.0 | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
NNPDF2.3 | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
NNPDF2.2 | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
NNPDF2.1 | Yes | Yes | Yes | No | Yes | Yes | Yes |
NNPDF2.0 | Yes | Yes | Yes | No | Yes | No | No |
NNPDF1.2 | Yes | No | No | No | Yes | No | No |
NNPDF1.0 | Yes | No | No | No | No | No | No |
All PDF sets are available through the LHAPDF interface and in the NNPDF webpage.