Publications

Order by: publication date number of citations

• NuHepMC: A standardized event record format for neutrino event generators

  Steven Gardiner, Joshua Isaacson, Luke Pickering

  SciPost Phys. Codebases 57 (2025) · published 22 August 2025 | Toggle abstract · pdf

  Simulations of neutrino interactions are playing an increasingly important role in the pursuit of high-priority measurements for the field of particle physics. A significant technical barrier for efficient development of these simulations is the lack of a standard data format for representing individual neutrino scattering events. We propose and define such a universal format, named NuHepMC, as a common standard for the output of neutrino event generators. The NuHepMC format uses data structures and concepts from the HepMC3 event record library adopted by other subfields of high-energy physics. These are supplemented with an original set of conventions for generically representing neutrino interaction physics within the HepMC3 infrastructure.

  2 citations

• Codebase release 1.0 for NuHepMC

  Steven Gardiner, Joshua Isaacson, Luke Pickering

  SciPost Phys. Codebases 57-r1.0 (2025) · published 22 August 2025 | Toggle abstract · src

  Simulations of neutrino interactions are playing an increasingly important role in the pursuit of high-priority measurements for the field of particle physics. A significant technical barrier for efficient development of these simulations is the lack of a standard data format for representing individual neutrino scattering events. We propose and define such a universal format, named NuHepMC, as a common standard for the output of neutrino event generators. The NuHepMC format uses data structures and concepts from the HepMC3 event record library adopted by other subfields of high-energy physics. These are supplemented with an original set of conventions for generically representing neutrino interaction physics within the HepMC3 infrastructure.

  1 citation

• Physics-informed neural networks viewpoint for solving the Dyson-Schwinger equations of quantum electrodynamics

  Rodrigo Carmo Terin

  SciPost Phys. Core 8, 054 (2025) · published 20 August 2025 | Toggle abstract · pdf

  Physics-informed neural networks (PINNs) are employed to solve the Dyson-Schwinger equations of quantum electrodynamics (QED) in Euclidean space, with a focus on the non-perturbative generation of the fermion's dynamical mass function in the Landau gauge. By inserting the integral equation directly into the loss function, our PINN framework enables a single neural network to learn a continuous and differentiable representation of the mass function over a spectrum of momenta. Also, we benchmark our approach against a traditional numerical algorithm showing the main differences among them. Our novel strategy, which is expected to be extended to other quantum field theories, is the first step towards forefront applications of machine learning in high-level theoretical physics.

• How to unfold top decays

  Luigi Favaro, Roman Kogler, Alexander Paasch, Sofia Palacios Schweitzer, Tilman Plehn, Dennis Schwarz

  SciPost Phys. Core 8, 053 (2025) · published 18 August 2025 | Toggle abstract · pdf

  Using unfolded top-quark decay data we can measure the top quark mass, as well as search for unexpected kinematic effects. We present a new generative unfolding method for the two tasks and show how they both benefit from unbinned, high-dimensional unfolding. Unlike weight-based or iterative generative methods we include a targeted unbiasing with respect to the training data. This shows significant advantages over standard, iterative methods, in terms of applicability, flexibility and accuracy.

• State-of-the-art cross sections for $t\bar t H$: NNLO predictions matched with NNLL resummation and EW corrections

  Roger Balsach, Alessandro Broggio, Simone Devoto, Andrea Ferroglia, Rikkert Frederix, Massimiliano Grazzini, Stefan Kallweit, Anna Kulesza, Javier Mazzitelli, Leszek Motyka, Davide Pagani, Benjamin D. Pecjak, Chiara Savoini, Tomasz Stebel, Malgorzata Worek, Marco Zaro

  SciPost Phys. Comm. Rep. 10 (2025) · published 13 August 2025 | Toggle abstract · pdf

  We present new, state-of-the-art predictions for the associated production of the SM Higgs boson with top quarks, computed in accordance with the recommendations of the LHC Higgs Working Group. The NNLO QCD predictions, derived through suitable approximations of the two-loop virtual contribution, are supplemented with soft-gluon resummation up to NNLL accuracy. Two distinct resummation frameworks are employed – one based on direct QCD and the other on soft-collinear effective theory – and their features are compared in detail. These results are further combined with the complete-NLO corrections, yielding the most precise SM predictions for this process to date. The relevant sources of theoretical uncertainties are thoroughly estimated and discussed.

• Lectures in quantum gravity

  Ivano Basile, Luca Buoninfante, Francesco Di Filippo, Benjamin Knorr, Alessia Platania, Anna Tokareva

  SciPost Phys. Lect. Notes 98 (2025) · published 7 August 2025 | Toggle abstract · pdf

  Formulating a quantum theory of gravity lies at the heart of fundamental theoretical physics. This collection of lecture notes encompasses a selection of topics that were covered in six mini-courses at the Nordita PhD school "Towards Quantum Gravity". The scope was to provide a coherent picture, from its foundation to forefront research, emphasizing connections between different areas. The lectures begin with perturbative quantum gravity and effective field theory. Subsequently, two ultraviolet-complete approaches are presented: Asymptotically safe gravity and string theory. Finally, elements of quantum effects in black hole spacetimes are discussed.

  2 citations

• Attention to the strengths of physical interactions: Transformer and graph-based event classification for particle physics experiments

  Luc Builtjes, Sascha Caron, Polina Moskvitina, Clara Nellist, Roberto Ruiz de Austri, Rob Verheyen, Zhongyi Zhang

  SciPost Phys. 19, 028 (2025) · published 28 July 2025 | Toggle abstract · pdf

  A major task in particle physics is the measurement of rare signal processes. Even modest improvements in background rejection, at a fixed signal efficiency, can significantly enhance the measurement sensitivity. Building on prior research by others that incorporated physical symmetries into neural networks, this work extends those ideas to include additional physics-motivated features. Specifically, we introduce energy-dependent particle interaction strengths, derived from leading-order SM predictions, into modern deep learning architectures, including Transformer Architectures (Particle Transformer), and Graph Neural Networks (Particle Net). These interaction strengths, represented as the SM interaction matrix, are incorporated into the attention matrix (transformers) and edges (graphs). Our results in event classification show that the integration of all physics-motivated features improves background rejection by $10\%-40\%$ over baseline models, with an additional gain of up to $9\%$ due to the SM interaction matrix. This study also provides one of the broadest comparisons of event classifiers to date, demonstrating how various architectures perform across this task. A simplified statistical analysis demonstrates that these enhanced architectures yield significant improvements in signal significance compared to a graph network baseline.

  1 citation

• Tau data-based evaluations of the hadronic vacuum polarization contribution to the muon g-2

  Pere Masjuan, Alejandro Miranda, Pablo Roig

  SciPost Phys. Proc. 17, 023 (2025) · published 23 July 2025 | Toggle abstract · pdf

  We review the $\tau$ data-driven computation of Euclidean windows for the hadronic vacuum polarization contribution to the muon anomalous magnetic moment ($a_\mu$), which agree with the lattice results, making the difference of the $e^+e^-$ data-driven methods with them more intriguing. This conundrum needs to be solved by next year, when the final FNAL $a_\mu$ measurement will be published, in order to extract firm conclusions on possible new physics effects.

• Matter effect in $P_{\mu \tau}$ at long baselines

  Srubabati Goswami, Supriya Pan, Animesh Chatterjee

  SciPost Phys. Proc. 17, 017 (2025) · published 23 July 2025 | Toggle abstract · pdf

  In the simple two-generation case, the probability $P_{\mu \tau}$ is not affected by interactions of neutrinos in matter. But for three-generation case, at baselines of the order of 9000 km, matter effects become important for this channel. This is a genuine three-flavour effect. We study how the presence of non-standard interactions (NSI) alters the $P_{\mu \tau}$ at these baselines. We observe large deviations from the standard matter effect. In particular, we find energies and baselines for which the phases governing the NSIs do not play any role. This may facilitate a better determination of NSI parameters if tau neutrinos can be detected.

• Leptophilic portals to new physics at colliders

  P. S. Bhupal Dev

  SciPost Phys. Proc. 17, 007 (2025) · published 23 July 2025 | Toggle abstract · pdf

  Observed neutrino oscillations imply that the global lepton flavor symmetry of the Standard Model must be broken. Therefore, searches for lepton flavor violation (LFV) are promising probes of new physics beyond the Standard Model. High-energy colliders provide a powerful tool to study LFV effects, which are complementary to the low-energy charged LFV searches. Here we discuss the possibility of LFV signals at colliders arising from exotic Higgs decays, and from leptophilic scalar and vector portal scenarios.