NNPDF

NNPDF. The NNPDF collaboration is a major research group in high-energy physics focused on determining the fundamental structure of the proton through the framework of parton distribution functions (PDFs). It is renowned for pioneering a novel, data-driven methodology using artificial neural networks to represent PDFs without imposing strong theoretical biases. The collaboration's global efforts involve physicists from institutions like the University of Oxford, the University of Edinburgh, and CERN, producing essential inputs for precision calculations at facilities such as the Large Hadron Collider.

Overview

The primary objective is to provide precise, robust sets of parton distribution functions, which describe the momentum distributions of quarks and gluons inside the proton. These functions are non-perturbative inputs required for making theoretical predictions in quantum chromodynamics (QCD) for processes observed in particle colliders. The collaboration's work is integral to the physics programs of experiments like ATLAS and CMS, enabling tests of the Standard Model and searches for new physics. Their results are widely used by the theoretical and experimental particle physics community for interpreting data from the Tevatron and the Large Hadron Collider.

Methodology

The approach is distinguished by its use of artificial neural networks as unbiased interpolants to represent the functional form of the PDFs. This technique minimizes theoretical assumptions about the underlying shape, relying instead on the experimental data to determine the probability distribution in the space of possible functions. The fitting procedure incorporates a comprehensive database of global data from deep-inelastic scattering experiments like those at HERA, fixed-target experiments, and collider data from the Tevatron. The analysis rigorously accounts for uncertainties using the Monte Carlo method and Bayesian inference, producing results that satisfy the theoretical constraints of QCD evolution as governed by the Dokshitzer–Gribov–Lipatov–Altarelli–Parisi equations.

Applications

The PDF sets are critical for calculating precise cross-sections for processes like Higgs boson production, top quark pair production, and vector boson scattering at the Large Hadron Collider. They are used to set constraints on fundamental parameters of the Standard Model, such as the strong coupling constant, and to reduce theoretical uncertainties in global analyses. Furthermore, these functions provide essential benchmarks for studies of nucleon structure in experiments at the future Electron-Ion Collider and are employed in analyses of ultra-high-energy cosmic ray interactions observed by observatories like the Pierre Auger Observatory.

Comparison with other PDF sets

Unlike traditional global analysis groups such as CTEQ and MSTW, which often use parameterized functional forms with specific theoretical choices, the neural network methodology aims to provide a more flexible and assumption-free extraction. Comparisons are routinely performed within frameworks like the PDF4LHC working group, which provides recommendations for the particle physics community. These exercises highlight differences in the treatment of data sets, theoretical uncertainties, and the propagation of errors, contributing to a deeper understanding of proton structure. The collaboration also participates in benchmarking workshops organized by the Les Houches physics school.

Development and releases

The collaboration was formally established following pioneering work by researchers at the University of Oxford and the University of Edinburgh. Major releases have included NNPDF2.0, NNPDF3.0, and NNPDF4.0, each incorporating larger data sets, improved methodological refinements, and extended perturbative order calculations, including next-to-next-to-leading order (NNLO) QCD. Development is supported by extensive use of high-performance computing resources at institutions like CINECA and through European funding initiatives. The collaboration actively engages with the broader community through presentations at major conferences like the International Conference on High Energy Physics and publications in journals such as the European Physical Journal C. Category:High-energy physics Category:Particle physics collaborations Category:Quantum chromodynamics