Publications

Order by: publication date number of citations

• Constraining electroweakinos in the minimal Dirac gaugino model

  Mark D. Goodsell, Sabine Kraml, Humberto Reyes-González, Sophie L. Williamson

  SciPost Phys. 9, 047 (2020) · published 8 October 2020 | Toggle abstract · pdf

  Supersymmetric models with Dirac instead of Majorana gaugino masses have distinct phenomenological consequences. In this paper, we investigate the electroweakino sector of the Minimal Dirac Gaugino Supersymmetric Standard Model (MDGSSM) with regards to dark matter (DM) and collider constraints. We delineate the parameter space where the lightest neutralino of the MDGSSM is a viable DM candidate, that makes for at least part of the observed relic abundance while evading constraints from DM direct detection, LEP and lowenergy data, and LHC Higgs measurements. The collider phenomenology of the thus emerging scenarios is characterised by the richer electroweakino spectrum as compared to the Minimal Supersymmetric Standard Model (MSSM) -- 6 neutralinos and 3 charginos instead of 4 and 2 in the MSSM, naturally small mass splittings, and the frequent presence of long-lived particles, both charginos and/or neutralinos. Reinterpreting ATLAS and CMS analyses with the help of SModelS and MadAnalysis 5, we discuss the sensitivity of existing LHC searches for new physics to these scenarios and show which cases can be constrained and which escape detection. Finally, we propose a set of benchmark points which can be useful for further studies, designing dedicated experimental analyses and/or investigating the potential of future experiments.

  14 citations

• Precision-machine learning for the matrix element method

  Theo Heimel, Nathan Huetsch, Ramon Winterhalder, Tilman Plehn, Anja Butter

  SciPost Phys. 17, 129 (2024) · published 8 November 2024 | Toggle abstract · pdf

  The matrix element method is the LHC inference method of choice for limited statistics. We present a dedicated machine learning framework, based on efficient phase-space integration, a learned acceptance and transfer function. It is based on a choice of INN and diffusion networks, and a transformer to solve jet combinatorics. We showcase this setup for the CP-phase of the top Yukawa coupling in associated Higgs and single-top production.

  14 citations

• On the quark spectral function in QCD

  Jan Horak, Jan M. Pawlowski, Nicolas Wink

  SciPost Phys. 15, 149 (2023) · published 10 October 2023 | Toggle abstract · pdf

  We calculate the spectral function of light quark flavours in 2+1 flavour vacuum QCD in the isospin-symmetric approximation. We employ spectral Dyson-Schwinger equations and compute the non-perturbative quark propagator directly in real-time, using recent spectral reconstruction results from Gaussian process regression of gluon propagator data in 2+1 flavour lattice QCD. Our results feature a pole-like peak structure at time-like momenta larger than the propagator's gapping scale as well as a negative scattering continuum, which we exploit assuming an analytic pole-tail split during the iterative solution. The computation is augmented with a general discussion of the impact of the quark-gluon vertex and the gluon propagator on the analytic structure of the quark propagator. In particular, we investigate under which conditions the quark propagator shows unphysical complex poles. Our results offer a wide range of applications, encompassing the ab-initio calculation of transport as well as resonance properties in QCD.

  13 citations

• Resolving phase transitions with discontinuous Galerkin methods

  Eduardo Grossi, Nicolas Wink

  SciPost Phys. Core 6, 071 (2023) · published 25 October 2023 | Toggle abstract · pdf

  We demonstrate the applicability and advantages of Discontinuous Galerkin (DG) schemes in the context of the Functional Renormalization Group (fRG). We investigate the $O(N)$-model in the large $N$ limit. It is shown that the flow equation for the effective potential can be cast into a conservative form. We discuss results for the Riemann problem, as well as initial conditions leading to a first and second order phase transition. In particular, we unravel the mechanism underlying first order phase transitions, based on the formation of a shock in the derivative of the effective potential.

  13 citations

• What's anomalous in LHC jets?

  Thorsten Buss, Barry M. Dillon, Thorben Finke, Michael Krämer, Alessandro Morandini, Alexander Mück, Ivan Oleksiyuk, Tilman Plehn

  SciPost Phys. 15, 168 (2023) · published 17 October 2023 | Toggle abstract · pdf

  Searches for anomalies are a significant motivation for the LHC and help define key analysis steps, including triggers. We discuss specific examples how LHC anomalies can be defined through probability density estimates, evaluated in a physics space or in an appropriate neural network latent space, and discuss the model-dependence in choosing an appropriate data parameterisation. We illustrate this for classical k-means clustering, a Dirichlet variational autoencoder, and invertible neural networks. For two especially challenging scenarios of jets from a dark sector we evaluate the strengths and limitations of each method.

  13 citations

• Phases of cold holographic QCD: Baryons, pions and rho mesons

  Nicolas Kovensky, Aaron Poole, Andreas Schmitt

  SciPost Phys. 15, 162 (2023) · published 13 October 2023 | Toggle abstract · pdf

  We improve the holographic description of isospin-asymmetric baryonic matter within the Witten-Sakai-Sugimoto model by accounting for a realistic pion mass, computing the pion condensate dynamically, and including rho meson condensation by allowing the gauge field in the bulk to be anisotropic. This description takes into account the coexistence of baryonic matter with pion and rho meson condensates. Our main result is the zero-temperature phase diagram in the plane of baryon and isospin chemical potentials. We find that the effective pion mass in the baryonic medium increases with baryon density and that, as a consequence, there is no pion condensation in neutron-star matter. Our improved description also predicts that baryons are disfavored at low baryon chemical potentials even for arbitrarily large isospin chemical potential. Instead, rho meson condensation sets in on top of the pion condensate at an isospin chemical potential of about $9.4 m_\pi$. We further observe a highly non-monotonic phase boundary regarding the disappearance of pion condensation.

  13 citations

• Jet diffusion versus JetGPT – Modern networks for the LHC

  Anja Butter, Nathan Huetsch, Sofia Palacios Schweitzer, Tilman Plehn, Peter Sorrenson, Jonas Spinner

  SciPost Phys. Core 8, 026 (2025) · published 3 March 2025 | Toggle abstract · pdf

  We introduce two diffusion models and an autoregressive transformer for LHC physics simulations. Bayesian versions allow us to control the networks and capture training uncertainties. After illustrating their different density estimation methods for simple toy models, we discuss their advantages for Z plus jets event generation. While diffusion networks excel through their precision, the transformer scales best with the phase space dimensionality. Given the different training and evaluation speed, we expect LHC physics to benefit from dedicated use cases for normalizing flows, diffusion models, and autoregressive transformers.

  13 citations

• Ephemeral Learning - Augmenting Triggers with Online-Trained Normalizing Flows

  Anja Butter, Sascha Diefenbacher, Gregor Kasieczka, Benjamin Nachman, Tilman Plehn, David Shih, Ramon Winterhalder

  SciPost Phys. 13, 087 (2022) · published 7 October 2022 | Toggle abstract · pdf

  The large data rates at the LHC require an online trigger system to select relevant collisions. Rather than compressing individual events, we propose to compress an entire data set at once. We use a normalizing flow as a deep generative model to learn the probability density of the data online. The events are then represented by the generative neural network and can be inspected offline for anomalies or used for other analysis purposes. We demonstrate our new approach for a toy model and a correlation-enhanced bump hunt.

  12 citations

• A spectator-model way to transverse-momentum-dependent gluon distribution functions

  Alessandro Bacchetta, Francesco Giovanni Celiberto, Marco Radici, Pieter Taels

  SciPost Phys. Proc. 8, 040 (2022) · published 12 July 2022 | Toggle abstract · pdf

  We present exploratory analyses of the 3D gluon content of the proton via a study of unpolarized and polarized gluon TMDs at twist-2, calculated in a spectator model for the parent nucleon. Our approach embodies a flexible parametrization for the spectator-mass function, suited to describe both moderate and small-$x$ effects. All these studies can serve as a useful guidance in the investigation of the gluon dynamics inside nucleons and nuclei, which constitutes one of the major goals of new-generation colliding machines, as the EIC, the HL-LHC, NICA, and the FPF.

  12 citations

• Birdtracks for SU(N)

  Stefan Keppeler

  SciPost Phys. Lect. Notes 3 (2018) · published 27 September 2018 | Toggle abstract · pdf

  I gently introduce the diagrammatic birdtrack notation, first for vector algebra and then for permutations. After moving on to general tensors I review some recent results on Hermitian Young operators, gluon projectors, and multiplet bases for SU(N) colour space.

  12 citations