Towards the determination of the photon parton distribution function constrained by LHC data

We provide a discussion of the impact of a subset of Drell-Yan data from LHC on the determination of the photon parton distribution function (PDF), using the NNPDF methodology. In previous work we have shown that the photon PDF determined from deep-inelastic scattering (DIS) data only has large uncertainties, suggesting the need for more data from other processes such as Drell-Yan, which unlike DIS, includes photon-induced contributions at leading order in QED. We describe the inclusion of ATLAS Drell-Yan W, Z data, which is a subset of the LHC data used in a final photon PDF determination, by means of a reweighting procedure. We show the impact of such data by comparing the reweighted photon PDF with the photon PDF from DIS, highlighting the reduction of uncertainties at medium/small-x. We conclude that the Drell-Yan data from LHC allows a reasonably accurate determination of the photon PDF.Comment: 5 pages, 10 figures, to appear in the proceedings of the XXI International Workshop on Deep-Inelastic Scattering and Related Subjects (DIS2013), Marseille, 22-26 April 201

Machine learning challenges in theoretical HEP

In these proceedings we perform a brief review of machine learning (ML) applications in theoretical High Energy Physics (HEP-TH). We start the discussion by defining and then classifying machine learning tasks in theoretical HEP. We then discuss some of the most popular and recent published approaches with focus on a relevant case study topic: the determination of parton distribution functions (PDFs) and related tools. Finally, we provide an outlook about future applications and developments due to the synergy between ML and HEP-TH.Comment: 7 pages, 3 figures, in proceedings of the 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2017

Disentangling electroweak effects in Z-boson production

Parton distributions with QED corrections open new scenarios for high precision physics. We recall the need for accurate and improved predictions which keeps into account higher order QCD corrections together with electroweak effects. We study predictions obtained with the improved Born approximation and the $G_{\mu}$ scheme by using two public codes: DYNNLO and HORACE. We focus our attention on the Drell-Yan Z-boson invariant mass distribution at low- and high-mass regions, recently measured by the ATLAS experiment and we estimate the impact of each component of the final prediction. We show that electroweak corrections are larger than PDF uncertainties for modern PDF sets and therefore such corrections are necessary to improve the extraction of future PDF sets.Comment: 5 pages, 4 figures, to appear in the proceedings of the Les Rencontres de Physique de la Vall\'ee d'Aoste, La Thuile 201

Modeling NNLO jet corrections with neural networks

We present a preliminary strategy for modeling multidimensional distributions through neural networks. We study the efficiency of the proposed strategy by considering as input data the two-dimensional next-to-next leading order (NNLO) jet k-factors distribution for the ATLAS 7 TeV 2011 data. We then validate the neural network model in terms of interpolation and prediction quality by comparing its results to alternative models.Comment: Proceedings for the Cracow Epiphany Conference 2017, final versio

Perturbative QCD description of jet data from LHC Run-I and Tevatron Run-II

We present a systematic comparison of jet predictions at the LHC and the Tevatron, with accuracy up to next-to-next-to-leading order (NNLO). The exact computation at NNLO is completed for the gluons-only channel, so we compare the exact predictions for this channel with an approximate prediction based on threshold resummation, in order to determine the regions where this approximation is reliable at NNLO. The kinematic regions used in this study are identical to the experimental setup used by recently published jet data from the ATLAS and CMS experiments at the LHC, and CDF and D0 experiments at the Tevatron. We study the effect of choosing different renormalisation and factorisation scales for the NNLO exact prediction and as an exercise assess their impact on a PDF fit including these corrections. Finally we provide numerical values of the NNLO k-factors relevant for the LHC and Tevatron experiments.Comment: 51 pages, 13 figures, 35 tables. Final version, matches published version in JHE

Jet grooming through reinforcement learning

We introduce a novel implementation of a reinforcement learning (RL) algorithm which is designed to find an optimal jet grooming strategy, a critical tool for collider experiments. The RL agent is trained with a reward function constructed to optimize the resulting jet properties, using both signal and background samples in a simultaneous multi-level training. We show that the grooming algorithm derived from the deep RL agent can match state-of-the-art techniques used at the Large Hadron Collider, resulting in improved mass resolution for boosted objects. Given a suitable reward function, the agent learns how to train a policy which optimally removes soft wide-angle radiation, allowing for a modular grooming technique that can be applied in a wide range of contexts. These results are accessible through the corresponding GroomRL framework.Comment: 11 pages, 10 figures, code available at https://github.com/JetsGame/GroomRL, updated to match published versio

Towards the compression of parton densities through machine learning algorithms

One of the most fascinating challenges in the context of parton density function (PDF) is the determination of the best combined PDF uncertainty from individual PDF sets. Since 2014 multiple methodologies have been developed to achieve this goal. In this proceedings we first summarize the strategy adopted by the PDF4LHC15 recommendation and then, we discuss about a new approach to Monte Carlo PDF compression based on clustering through machine learning algorithms.Comment: 4 pages, 4 figures, to appear in the proceedings of 50th Rencontres de Moriond, QCD and High Energy Interactions, La Thuile, Italy, March 201

APFEL: A PDF Evolution Library with QED corrections

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 to NNLO in QCD and to LO in QED, in the variable-flavor-number scheme and with either pole or MSbar heavy quark masses. APFEL consistently accounts for the QED corrections to the evolution of quark and gluon PDFs and for the contribution from the photon PDF in the proton. The coupled QCD+QED equations are solved in x-space by means of higher order interpolation, followed by Runge-Kutta solution of the resulting discretized evolution equations. APFEL is based on an innovative and flexible methodology for the sequential solution of the QCD and QED evolution equations and their combination. In addition to PDF evolution, APFEL provides a module that computes Deep-Inelastic Scattering structure functions in the FONLL general-mass variable-flavor-number scheme up to O($\alpha_s^2$). All the functionalities of APFEL can be accessed via a Graphical User Interface, supplemented with a variety of plotting tools for PDFs, parton luminosities and structure functions. Written in Fortran 77, APFEL can also be used via the C/C++ and Python interfaces, and is publicly available from the HepForge repository.Comment: 34 pages, 5 figures. Final version, to be published in CPC. Several corrections and improvements. Program available from http://apfel.hepforge.org

Doped Parton Distributions

Calculations of high-energy processes involving the production of b-quarks are typically performed in two different ways, the massive four-flavour scheme (4FS) and the massless five-flavour scheme (5FS). For processes where the combination of the 4FS and 5FS results into a matched calculation is technically difficult, it is possible to define a hybrid scheme known as the doped scheme, where above the b-quark threshold the strong coupling runs with $n_f=5$, as in the massless calculation, while the DGLAP splitting functions are those of the $n_f=4$ scheme. In this contribution we present NNPDF3.0 PDF sets in this doped scheme, compare them with the corresponding 4FS and 5FS sets, and discuss their relevance for LHC phenomenology.Comment: 5 pages, 5 figures, to appear in the proceedings of the 27th Rencontres de Blois on Particle Physics and Cosmology, Blois, May 31 to June 05, 201