Publications

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Precision calibration of calorimeter signals in the ATLAS experiment using an uncertainty-aware neural network

ATLAS Collaboration

SciPost Phys. 19, 155 (2025) · published 16 December 2025 | · pdf

The ATLAS experiment at the Large Hadron Collider explores the use of modern neural networks for a multi-dimensional calibration of its calorimeter signal defined by clusters of topologically connected cells (topo-clusters). The Bayesian neural network (BNN) approach not only yields a continuous and smooth calibration function that improves performance relative to the standard calibration but also provides uncertainties on the calibrated energies for each topo-cluster. The results obtained by using a trained BNN are compared to the standard local hadronic calibration and to a calibration provided by training a deep neural network. The uncertainties predicted by the BNN are interpreted in the context of a fractional contribution to the systematic uncertainties of the trained calibration. They are also compared to uncertainty predictions obtained from an alternative estimator employing repulsive ensembles.
Characterizing the hadronization of parton showers using the HOMER method

Benoît Assi, Christian Bierlich, Philip Ilten, Tony Menzo, Stephen Mrenna, Manuel Szewc, Michael K. Wilkinson, Ahmed Youssef, Jure Zupan

SciPost Phys. 19, 125 (2025) · published 11 November 2025 | · pdf

We update the HOMER method, a technique to solve a restricted version of the inverse problem of hadronization – extracting the Lund string fragmentation function $f(z)$ from data using only observable information. Here, we demonstrate its utility by extracting $f(z)$ from synthetic Pythia simulations using high-level observables constructed on an event-by-event basis, such as multiplicities and shape variables. Four cases of increasing complexity are considered, corresponding to $e^+e^-$ collisions at a center-of-mass energy of $90≥v$ producing either a string stretched between a $q$ and $\bar{q}$ containing no gluons; the same string containing one gluon $g$ with fixed kinematics; the same but the gluon has varying kinematics; and the most realistic case, strings with an unrestricted number of gluons that is the end-result of a parton shower. We demonstrate the extraction of $f(z)$ in each case, with the result of only a relatively modest degradation in performance of the HOMER method with the increased complexity of the string system.
Learning selection cuts with gradients

Mike Hance, Juan Robles

SciPost Phys. Core 8, 079 (2025) · published 7 November 2025 | · pdf

Many analyses in high-energy physics rely on selection thresholds (cuts) applied to detector, particle, or event properties. Initial cut values can often be guessed from physical intuition, but cut optimization, especially for multiple features, is commonly performed by hand, or skipped entirely in favor of multivariate algorithms like BDTs or neural networks. We revisit this problem, and develop a cut optimization approach based on gradient descent. Cut thresholds are learned as parameters of a network with a simple architecture, and can be tuned to achieve a target signal efficiency through the use of custom loss functions. Contractive terms in the loss can be used to ensure a smooth evolution of cuts as functions of efficiency, particle kinematics, or event features. The method is used to classify events in a search for Supersymmetry, and the performance is compared with common classification tools. An implementation of this approach is available in a public code repository and python package.
Higgs production via vector-boson fusion at the LHC

Gaetano Barone, Jiayi Chen, Stephane Cooperstein, Nikita Dolganov, Silvia Ferrario Ravasio, Yacine Haddad, Stefan Höche, Barbara Jäger, Alexander Karlberg, Alexander Mück, Mathieu Pellen, Christian T. Preuss, Daniel Reichelt, Simon Reinhardt, Marco Zaro

SciPost Phys. Comm. Rep. 13 (2025) · published 5 November 2025 | · pdf

In this article, we summarise the recent experimental measurements and theoretical work on Higgs boson production via vector-boson fusion at the LHC. Along with this, we provide state-of-the-art predictions at fixed order as well as with parton-shower corrections within the Standard Model at $13.6\,\text{TeV}$. The results are presented in the form of multi-differential distributions as well as in the Simplified Template Cross Section bins. All materials and outputs of this study are available on public repositories. Finally, following findings in the literature, recommendations are made to estimate theoretical uncertainties related to parton-shower corrections.
Phase space compression of a positive muon beam in two spatial dimensions

A. Antognini, N. J. Ayres, I. Belosevic, V. Bondar, A. Eggenberger, M. Hildebrandt, R. Iwai, K. Kirch, A. Knecht, G. Lospalluto, J. Nuber, A. Papa, M. Sakurai, I. Solovyev, D. Taqqu, T. Yan

SciPost Phys. Core 8, 071 (2025) · published 20 October 2025 | · pdf

We present the first demonstration of simultaneous phase space compression in two spatial dimensions of a positive muon beam, the first stage of the novel high-brightness muon beam under development by the muCool collaboration at the Paul Scherrer Institute. The keV-energy, sub-mm size beam would enable a factor $10^5$ improvement in brightness for precision $\mu$SR, and atomic and particle physics measurements with positive muons. This compression is achieved within a cryogenic helium gas target with a strong density gradient, placed in a homogeneous magnetic field, under the influence of a complex electric field. In the next phase, the muon beam will be extracted into vacuum.
Towards universal unfolding of detector effects in high-energy physics using denoising diffusion probabilistic models

Camila Pazos, Shuchin Aeron, Pierre-Hugues Beauchemin, Vincent Croft, Zhengyan Huan, Martin Klassen, Taritree Wongjirad

SciPost Phys. Core 8, 064 (2025) · published 2 October 2025 | · pdf

Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel approach to multidimensional object-wise unfolding using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, incorporating distribution moments as conditioning information, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions, while enabling the unfolding of a wide range of measured distributions with improved adaptability and accuracy.
A data-driven method to estimate the antiproton background in Mu2e

Namitha Chithirasreemadam, Simone Donati, Pavel Murat, on behalf of the Mu2e collaboration

SciPost Phys. Proc. 17, 025 (2025) · published 23 July 2025 | · pdf

The Mu2e experiment will search for the CLFV process of neutrinoless, coherent conversion of muon to electron in the field of an Al nucleus. One of the expected backgrounds is antiprotons produced by the proton beam at the Production Target and annihilating in the Stopping Target to produce signal-like electrons. Although not a dominant background, it has a large uncertainty and cannot be suppressed by the timing cuts used to reduce the prompt background. However, at Mu2e energies, $p\bar{p}$ annihilation is the only source of events with multiple, simultaneous particles coming from the Stopping Target. We utilized this unique feature and developed a novel approach to reconstruct multi-track events and estimate the antiproton background.
An alternative evaluation of the leading-order hadronic contribution to the muon $g-2$ with MUonE

Riccardo N. Pilato

SciPost Phys. Proc. 17, 024 (2025) · published 23 July 2025 | · pdf

The MUonE experiment proposes a novel approach to determine the hadronic contribution to the muon $g-2$, $a_\mu^\text{HLO}$, based on the measurement of the hadronic running of the QED coupling through the analysis of $\mu-e$ elastic scattering events. This could clarify the tensions in the current evaluations of $a_\mu^\text{HLO}$, which are limiting the comparison between theory and experiment for the muon $g-2$. The measurement will be performed at CERN’s North Area by scattering a 160 GeV muon beam on the atomic electrons of a low-Z target. The status and future plans of the experiment will be presented. Furthermore, an alternative method to extract $a_\mu^\text{HLO}$ from MUonE data will be discussed.
Measurement of the muon magnetic anomaly to 0.20 ppm by the Muon g-2 experiment at Fermilab

Lorenzo Cotrozzi, on behalf of the Muon g-2 collaboration

SciPost Phys. Proc. 17, 022 (2025) · published 23 July 2025 | · pdf

The Muon $g-2$ experiment at Fermilab aims to measure the muon magnetic moment anomaly, $a_{\mu}=(g-2)/2$, with a final accuracy of 0.14 parts per million (ppm). The experiment’s first result was published in 2021, based on data collected in 2018, and in 2023 a new result was published based on two more years of data taking, 2019 and 2020. The combination of the two results from Fermilab and the previous one from Brookhaven National Laboratory brought the uncertainty on the experimental measurement of $a_{\mu}$ to the unprecedented value of 0.19 ppm. This paper will present details about the improvements of statistical and systematic uncertainties on $a_{\mu}$ since the 2021 result.
TAMBO: Searching for tau neutrinos in the Peruvian Andes

William G. Thompson, on behalf of the TAMBO collaboration.

SciPost Phys. Proc. 17, 021 (2025) · published 23 July 2025 | · pdf

TAMBO is a planned next-generation neutrino observatory sensitive to 1-100 PeV Earth-skimming tau neutrinos. This tau neutrino specificity will provide a high-purity sample of astrophysical neutrinos whose locations on the sky can then be used to improve the sensitivities of all-flavor neutrino observatories. The observatory will be located in a deep canyon and will comprise an array of water-Cherenkov and plastic scintillator air-shower detectors. In this proceeding, I will summarize the current status of the updated TAMBO simulation package, which is currently being used for detector optimization and reconstruction studies.

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