Publications

Order by: publication date number of citations

• MACK: Mismodeling addressed with contrastive knowledge

  Liam Rankin Sheldon, Dylan Sheldon Rankin, Philip Harris

  SciPost Phys. 18, 150 (2025) · published 6 May 2025 | Toggle abstract · pdf

  The use of machine learning methods in high energy physics typically relies on large volumes of precise simulation for training. As machine learning models become more complex they can become increasingly sensitive to differences between this simulation and the real data collected by experiments. We present a generic methodology based on contrastive learning which is able to greatly mitigate this negative effect. Crucially, the method does not require prior knowledge of the specifics of the mismodeling. While we demonstrate the efficacy of this technique using the task of jet-tagging at the Large Hadron Collider, it is applicable to a wide array of different tasks both in and out of the field of high energy physics.

  1 citation

• A tale of $Z$+jet: SMEFT effects and the Lam-Tung relation

  Rhorry Gauld, Ulrich Haisch, Joachim Weiss

  SciPost Phys. 18, 148 (2025) · published 6 May 2025 | Toggle abstract · pdf

  We derive constraints on dimension-six light-quark dipole operators within the Standard Model (SM) effective field theory, based on measurements of $Z$ production at SLC and LEP, as well as $Z$+jet production at the LHC. Our new constraints exclude the parameter space that could potentially explain the observed discrepancy between theoretical predictions and experimental data for the Lam-Tung relation. With these updated limits, we model-independently determine the maximum possible influence that beyond-SM contributions could have on the angular coefficients $A_0$ and $A_2$, which enter the Lam-Tung relation.

  1 citation

• Two portals to GeV sterile neutrinos: Dipole versus mixing

  Enrico Bertuzzo, Michele Frigerio

  SciPost Phys. 18, 140 (2025) · published 28 April 2025 | Toggle abstract · pdf

  Massive sterile neutrinos, also known as heavy neutral leptons, can have a mixing with active neutrinos, $\theta$, as well as a dipole coupling to the photon, $d$. We study the interplay between these two portals, considering the production from meson decays of sterile neutrinos with mass $0.1$ GeV $≲ M_N ≲ 10$ GeV, at beam-dump facilities such as NA62 and SHiP, and at the FASER2 experiment. These sterile neutrinos can be long-lived and decay into a photon in a distant detector, via the dipole operator. We find that all these experiments will be sensitive to values of $d$ which are presently unconstrained. The experimental reach varies strongly with the mass $M_N$ and the mixing $\theta$, and one observes specific correlations with the flavour of active neutrinos. The SHiP experiment will mark a jump in sensitivity: (i) it will probe a sterile dipole as small as $d\sim 10^{-8}\ \text{GeV}^{-1}$, thus testing new physics well above the electroweak scale; (ii) it may detect the active-sterile dipole to the level predicted by electroweak loops, if $\theta$ is close to the present bound.

  4 citations

• Identifying the quantum properties of hadronic resonances using machine learning

  Jakub Filipek, Shih-Chieh Hsu, John Kruper, Kirtimaan Mohan, Benjamin Nachman

  SciPost Phys. Core 8, 039 (2025) · published 28 April 2025 | Toggle abstract · pdf

  With the great promise of deep learning, discoveries of new particles at the Large Hadron Collider (LHC) may be imminent. Following the discovery of a new Beyond the Standard model particle in an all-hadronic channel, deep learning can also be used to identify its quantum numbers. Convolutional neural networks (CNNs) using jet-images can significantly improve upon existing techniques to identify the quantum chromodynamic (QCD) ('color') as well as the spin of a two-prong resonance using its substructure. Additionally, jet-images are useful in determining what information in the jet radiation pattern is useful for classification, which could inspire future taggers. These techniques improve the categorization of new particles and are an important addition to the growing jet substructure toolkit, for searches and measurements at the LHC now and in the future.

• Systematically constructing the likelihood for boosted $H\to gg$ decays

  Andrew J. Larkoski

  SciPost Phys. 18, 130 (2025) · published 17 April 2025 | Toggle abstract · pdf

  We study the binary discrimination problem of identification of boosted $H\to gg$ decays from massive QCD jets in a systematic expansion in the strong coupling. Though this decay mode of the Higgs is unlikely to be discovered at the LHC, we analytically demonstrate several features of the likelihood ratio for this problem through explicit analysis of signal and background matrix elements. Through leading-order, we prove that by imposing a constraint on the jet mass and measuring the energy fraction of the softer subjet an improvement of signal to background ratio that is independent of the kinematics of the jets at high boosts can be obtained, and is approximately equal to the inverse of the strong coupling evaluated at the Higgs mass. At next-to-leading order, we construct a powerful discrimination observable through a sort of anomaly detection approach by simply inverting the next-to-leading order $H\to gg$ matrix element with soft gluon emission, which is naturally infrared and collinear safe. Our analytic conclusions are validated in simulated data from all-purpose event generators and subsequent parton showering and demonstrate that the signal-to-background ratio can be improved by a factor of several hundred at high, but accessible, jet energies at the LHC.

• Full event particle-level unfolding with variable-length latent variational diffusion

  Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson

  SciPost Phys. 18, 117 (2025) · published 1 April 2025 | Toggle abstract · pdf

  The measurements performed by particle physics experiments must account for the imperfect response of the detectors used to observe the interactions. One approach, unfolding, statistically adjusts the experimental data for detector effects. Recently, generative machine learning models have shown promise for performing unbinned unfolding in a high number of dimensions. However, all current generative approaches are limited to unfolding a fixed set of observables, making them unable to perform full-event unfolding in the variable dimensional environment of collider data. A novel modification to the variational latent diffusion model (VLD) approach to generative unfolding is presented, which allows for unfolding of high- and variable-dimensional feature spaces. The performance of this method is evaluated in the context of semi-leptonic $t\bar{t}$ production at the Large Hadron Collider.

  10 citations

• Renormalisation group effects in SMEFT for di-Higgs production

  Gudrun Heinrich, Jannis Lang

  SciPost Phys. 18, 113 (2025) · published 31 March 2025 | Toggle abstract · pdf

  We study the effects of renormalisation group running for the Wilson coefficients of dimension-6 operators contributing to Higgs boson pair production in gluon fusion within Standard Model Effective Field Theory (SMEFT). The running of these Wilson coefficients has been implemented in the NLO QCD code ggHH_SMEFT, which is publicly available within the Powheg-Box-V2 framework.

  5 citations

• Scaling laws in jet classification

  Joshua Batson, Yonatan Kahn

  SciPost Phys. Core 8, 034 (2025) · published 28 March 2025 | Toggle abstract · pdf

  We demonstrate the emergence of scaling laws in the benchmark top versus QCD jet classification problem in collider physics. Six distinct physically-motivated classifiers exhibit power-law scaling of the binary cross-entropy test loss as a function of training set size, with distinct power law indices. This result highlights the importance of comparing classifiers as a function of dataset size rather than for a fixed training set, as the optimal classifier may change considerably as the dataset is scaled up. We speculate on the interpretation of our results in terms of previous models of scaling laws observed in natural language and image datasets.

  3 citations

• Codebase release 1.0 for Kolya

  Matteo Fael, Ilija S. Milutin, K. Keri Vos

  SciPost Phys. Codebases 55-r1.0 (2025) · published 25 March 2025 | Toggle abstract · src

  We introduce the code kolya, an open-source tool for phenomenological analyses of inclusive semileptonic $B\to X_c l\bar \nu_l$ decays. It contains a library to compute predictions for the total rate and various kinematic moments within the framework of the heavy quark expansion, utilizing the so-called kinetic scheme. The library currently includes power corrections up to $1/m_b^5$. All available QCD perturbative corrections are implemented via interpolation grids for fast numerical evaluation. We also include effects from new physics parameterized as Wilson coefficients of dimension-six operators in the weak effective theory below the electroweak scale. The library is interfaced to CRunDec for easy evaluation of the quark masses and strong coupling constant at different renormalization scales. The library is developed in Python and does not require compilation. The code is flexible and can be extended to other kinds of inclusive decays such as $B$ meson lifetimes, $B \to X_u l\bar \nu_l$ and $D$ meson decays.

  1 citation

• Kolya: An open-source package for inclusive semileptonic B decays

  Matteo Fael, Ilija S. Milutin, K. Keri Vos

  SciPost Phys. Codebases 55 (2025) · published 25 March 2025 | Toggle abstract · pdf

  We introduce the code kolya, an open-source tool for phenomenological analyses of inclusive semileptonic $B\to X_c l\bar \nu_l$ decays. It contains a library to compute predictions for the total rate and various kinematic moments within the framework of the heavy quark expansion, utilizing the so-called kinetic scheme. The library currently includes power corrections up to $1/m_b^5$. All available QCD perturbative corrections are implemented via interpolation grids for fast numerical evaluation. We also include effects from new physics parameterized as Wilson coefficients of dimension-six operators in the weak effective theory below the electroweak scale. The library is interfaced to CRunDec for easy evaluation of the quark masses and strong coupling constant at different renormalization scales. The library is developed in Python and does not require compilation. The code is flexible and can be extended to other kinds of inclusive decays such as $B$ meson lifetimes, $B \to X_u l\bar \nu_l$ and $D$ meson decays.

  1 citation