Juan Rojo's Website

Software

This page collects the main research software projects we develop and maintain within my group together with various collaborators, together with the public code, data, and online tools associated with them and representative publications for each. All these tools are open source and hence freely available to the community.

Parton Distributions & QCD
LHC Neutrinos
Effective Field Theories & ML
Electron Microscopy
Jets

Parton distributions and QCD evolution codes

  • NNPDF. Within the NNPDF Collaboration we determine the parton distribution functions (PDFs) of the proton, a crucial ingredient for the physics programme of the LHC, using neural networks and the Monte Carlo replica method to faithfully propagate experimental and methodological uncertainties. The latest releases reach percent-level precision and approximate N³LO accuracy, and the framework has been extended to polarised and nuclear PDFs. Detailed information is available from the collaboration website, the open-source fitting code is on GitHub, and all NNPDF sets are distributed through the LHAPDF library.

    • Key references: R. D. Ball, …, J. Rojo et al., The path to proton structure at 1% accuracy (NNPDF4.0), Eur. Phys. J. C 82 (2022) 428, arXiv:2109.02653; An open-source machine learning framework for global analyses of parton distributions, Eur. Phys. J. C 81 (2021) 958, arXiv:2109.02671; The path to N³LO parton distributions, Eur. Phys. J. C 84 (2024) 659, arXiv:2402.18635.

  • Small-x gluon from LHC charm production. Fits based on the NNPDF3.0 global analysis supplemented with LHCb charm data at 5, 7, and 13 TeV, leading to an improved determination of the small-x gluon PDF relevant for neutrino astronomy, cosmic-ray physics, Monte Carlo event generators, and future high-energy colliders. The fits are available in the LHAPDF6 format for the N5+N7+N13 combination and the N7+R13/5 combination in the Nf=5 scheme, and for the N5+N7+N13 combination in the Nf=3 fixed-flavour-number scheme.
    Reference: R. Gauld, J. Rojo, Precision determination of the small-x gluon from charm production at LHCb, Phys. Rev. Lett. 118 (2017) 072001, arXiv:1610.09373.
  • HL-LHC and LHeC PDF projections. Projections of the ultimate PDF uncertainty reduction expected at the High-Luminosity LHC and the LHeC, obtained by profiling the PDF4LHC15 sets with HL-LHC and LHeC pseudo-data in various scenarios. The resulting sets can be downloaded in LHAPDF format from Zenodo, and have been used in HL-LHC studies such as the corresponding Yellow Report.
    Reference: R. Abdul Khalek, S. Bailey, J. Gao, L. Harland-Lang, J. Rojo, Towards Ultimate Parton Distributions at the High-Luminosity LHC, Eur. Phys. J. C 78 (2018) 962, arXiv:1810.03639.
  • APFEL and APFEL++. APFEL (A Parton distribution Function Evolution Library with QED corrections) performs PDF evolution up to NNLO in the QCD coupling and up to LO in the QED coupling, together with a range of related operations on parton distributions and a graphical interface for visualising PDFs, parton luminosities, and DIS structure functions. The code is available on GitHub. Its modern C++ successor, APFEL++, developed by V. Bertone, is available at github.com/vbertone/apfelxx.
    References: V. Bertone, S. Carrazza, J. Rojo, APFEL: A PDF Evolution Library with QED corrections, Comput. Phys. Commun. 185 (2014) 1647, arXiv:1310.1394; S. Carrazza, A. Ferrara, D. Palazzo, J. Rojo, APFEL Web: a web-based application for the graphical visualization of parton distribution functions, J. Phys. G 42 (2015) 057001, arXiv:1410.5456.
  • aMCfast. A fast interface to the MadGraph5_aMC@NLO program, based on the APPLgrid framework, providing automated fast NLO and NLO+parton-shower interfaces for arbitrary collider processes for the inclusion of hadron-collider data into global PDF analyses. Hosted on HepForge.
    Reference: V. Bertone, R. Frederix, S. Frixione, J. Rojo, M. Sutton, aMCfast: automation of fast NLO computations for PDF fits, JHEP 08 (2014) 166, arXiv:1406.7693.
  • HOPPET. A Higher Order Perturbative Parton Evolution Toolkit: a Fortran95 package that performs PDF evolution up to NNLO in QCD and a variety of related operations on parton distributions. Available from HepForge.
    Reference: G. P. Salam, J. Rojo, A Higher Order Perturbative Parton Evolution Toolkit (HOPPET), Comput. Phys. Commun. 180 (2009) 120, arXiv:0804.3755.
  • SMPDF. The SM-PDF package for the construction of specialised, minimal PDF sets tailored to specific LHC applications. It also includes the mc2hessian code, which generates Hessian sets from an input PDF set in the Monte Carlo representation. See arXiv:1602.00005.
    References: S. Carrazza, S. Forte, Z. Kassabov, J. Rojo, Specialized minimal PDFs for optimized LHC calculations, Eur. Phys. J. C 76 (2016) 205, arXiv:1602.00005; S. Carrazza, S. Forte, Z. Kassabov, J. I. Latorre, J. Rojo, An Unbiased Hessian Representation for Monte Carlo PDFs, Eur. Phys. J. C 75 (2015) 369, arXiv:1505.06736.

LHC neutrinos and event generation tools

  • POWHEG-DIS. An adaptation of the POWHEG-BOX-RES framework to neutrino-induced deep-inelastic scattering, providing predictions accurate at next-to-leading order (NLO) in QCD matched to parton showers (Pythia8) for the LHC far-forward experiments FASER and SND@LHC and for the proposed Forward Physics Facility. The code is available on GitHub.
    Reference: M. van Beekveld, S. Ferrario Ravasio, E. Groenendijk, P. Krack, J. Rojo, V. Schütze Sánchez, A Phenomenological Analysis of LHC Neutrino Scattering at NLO Accuracy Matched to Parton Showers, Eur. Phys. J. C 84 (2024) 1175, arXiv:2407.09611.
  • DIS with LHC muons. A framework to model neutral-current deep-inelastic scattering of the intense flux of TeV-energy muons reaching the LHC far-forward detectors, enabling a muon-DIS programme at FASER with strong kinematic overlap with the Electron-Ion Collider. The code is available on GitHub.
    Reference: R. Francener, V. P. Goncalves, F. Kling, P. Krack, J. Rojo, Deep-Inelastic Scattering at TeV Energies with LHC Muons, Eur. Phys. J. C 85 (2025) 1098, arXiv:2506.13889.
  • NNfluxnu (NNνflux). An NNPDF-based code to extract the LHC forward neutrino fluxes directly from the neutrino scattering event rates measured by FASER and SND@LHC. A feed-forward neural network provides a theory-agnostic parametrisation of the flux, validated through closure tests and applied to the first determination of the LHC neutrino flux from FASER data. The code is available on GitHub.
    Reference: J. John, F. Kling, J. Koorn, P. Krack, J. Rojo, A First Determination of the LHC Neutrino Fluxes from FASER Data, JHEP 11 (2025) 106, arXiv:2507.06022.
  • NNSFν. A framework for the determination of inelastic neutrino structure functions across the complete range of energies relevant for phenomenology, from oscillation measurements in the GeV range to astroparticle physics in the EeV range. Accessible from its GitHub page, it provides fast interpolation grids in the LHAPDF format for neutrino structure functions valid over the full range of (x, Q, A) values, together with driver codes and look-up tables for inclusive neutrino cross-sections for all relevant target materials.
    Reference: A. Candido, A. Garcia, G. Magni, T. Rabemananjara, J. Rojo, R. Stegeman, Neutrino Structure Functions from GeV to EeV Energies, JHEP 05 (2023) 149, arXiv:2302.08527.
  • NuPropEarth. A Monte Carlo event generator that evaluates the impact of matter effects in the propagation of high-energy neutrinos, with the neutrino-nucleon cross-sections provided by the HEDIS module of GENIE. NuPropEarth allows studying the dependence of the neutrino attenuation rates on the cross-section model, the Earth model, the incidence angle, and the spectral index of the incoming flux. The code is publicly available from its GitHub repository.
    Reference: A. Garcia, R. Gauld, A. Heijboer, J. Rojo, Complete predictions for high-energy neutrino propagation in matter, JCAP 09 (2020) 025, arXiv:2004.04756.
  • BGR18 UHE neutrino-nucleus cross-sections. A state-of-the-art calculation of the ultra-high-energy (UHE) neutrino-nucleus scattering cross-sections in the Standard Model, including small-x BFKL resummation effects and the constraints from charm production at LHCb. The structure-function grids and the corresponding integrator code are publicly available here.
    Reference: V. Bertone, R. Gauld, J. Rojo, Neutrino Telescopes as QCD Microscopes, JHEP 01 (2019) 217, arXiv:1808.02034.
  • PromptNuFlux. A state-of-the-art calculation of the prompt atmospheric neutrino flux for a wide range of neutrino energies and several models of the cosmic-ray flux, including the full associated theory uncertainty. The code is available from HepForge.
    Reference: R. Gauld, J. Rojo, L. Rottoli, S. Sarkar, J. Talbert, The prompt atmospheric neutrino flux in the light of LHCb, JHEP 02 (2016) 130, arXiv:1511.06346.

Effective field theories and machine learning

  • SMEFiT. SMEFiT is an open-source framework for global analyses of the Standard Model Effective Field Theory (SMEFT), combining Higgs, top-quark, diboson, and electroweak precision data into simultaneous determinations of the Wilson coefficients, with a methodology based on Monte Carlo replicas and Nested Sampling. Its proof of concept was the most systematic SMEFT analysis of the top-quark sector to date, and current applications quantify the new-physics reach of future colliders such as the FCC-ee. Documentation and tutorials are available from the SMEFiT website and the code from its GitHub repository.
    Key references: T. Giani, G. Magni, J. Rojo, SMEFiT: a flexible toolbox for global interpretations of particle physics data, Eur. Phys. J. C 83 (2023) 393, arXiv:2302.06660; E. Celada, …, J. Rojo et al., Mapping the SMEFT at high-energy colliders: from LEP and the (HL-)LHC to the FCC-ee (SMEFiT3.0), JHEP 09 (2024) 091, arXiv:2404.12809; N. P. Hartland, …, J. Rojo et al., A Monte Carlo global analysis of the SMEFT: the top quark sector, JHEP 04 (2019) 100, arXiv:1901.05965.
  • ML4EFT. A general open-source framework for the integration of unbinned, high-dimensional observables into global fits of particle physics data. It uses machine-learning regression and classification to parametrise high-dimensional likelihood ratios, and can be integrated into global analyses of, for example, the SMEFT and parton distributions. Code, pre-trained models, documentation, and tutorials are available here.
    Reference: R. Gomez Ambrosio, J. ter Hoeve, M. Madigan, J. Rojo, V. Sanz, Unbinned multivariate observables for global SMEFT analyses from machine learning, JHEP 03 (2023) 033, arXiv:2211.02058.

ML for Electron Microscopy

  • EELSfitter. An open-source Python framework for the analysis and interpretation of Electron Energy Loss Spectroscopy (EELS) measurements in Transmission Electron Microscopy. It builds a model-independent parametrisation of the zero-loss peak (ZLP) intensity distribution using neural networks and the Monte Carlo replica method, and implements an efficient ZLP-subtraction strategy for applications such as bandgap determination in nanomaterials. The code is available from its GitHub repository and the documentation here.
    References: L. Roest, S. van Heijst, L. Maduro, J. Rojo, S. Conesa-Boj, Charting the low-loss region in Electron Energy Loss Spectroscopy with machine learning, Ultramicroscopy 222 (2021) 113202, arXiv:2009.05050; A. Brokkelkamp, J. ter Hoeve, I. Postmes, S. van Heijst, L. Maduro, A. V. Davydov, S. Krylyuk, J. Rojo, S. Conesa-Boj, Spatially Resolved Band Gap and Dielectric Function in 2D Materials from Electron Energy Loss Spectroscopy, J. Phys. Chem. A 126 (2022) 1255, arXiv:2202.12572.

Jet reconstruction

  • JetQuality. An online tool to check the performance of a wide variety of jet-clustering definitions for kinematic reconstruction at hadron colliders, available here.
    Reference: M. Cacciari, J. Rojo, G. P. Salam, G. Soyez, Quantifying the performance of jet definitions for kinematic reconstruction at the LHC, JHEP 12 (2008) 032, arXiv:0810.1304.