Publications

Order by: publication date number of citations

• Higgs associated production with a vector decaying to two fermions in the geoSMEFT

  Tyler Corbett, Adam Martin

  SciPost Phys. 16, 019 (2024) · published 19 January 2024 | Toggle abstract · pdf

  We present the inclusive calculations of a Higgs boson produced in association with massive vector bosons in the Standard Model Effective Field Theory (SMEFT) to order $1/\Lambda^4$ for the 13 TeV LHC. The calculations include the decay of the vector boson into massless constituents and are done using the geometric formulation of the SMEFT supplemented by the relevant dimension eight operators not included in the geoSMEFT. We include some discussion of distributions to motivate how detailed collider and experimental searches for SMEFT signals could be improved.

• Leading fermionic three-loop corrections to W-boson mass and Z-pole observables

  Lisong Chen, Ayres Freitas

  SciPost Phys. Proc. 7, 019 (2022) · published 21 June 2022 | Toggle abstract · pdf

  In this proceeding, we highlight the computation of leading fermionic three-loop corrections to electroweak precision observables (EWPOs) accomplished recently. We summarize the numerical analysis and provide an outlook.

• Sensitivity on the electromagnetic dipole moments of the tau-lepton at the CLIC

  Maria de los Ángeles Hernández-Ruíz, Ahmet A. Billur, Murat Köksal, Alejandro Gutiérrez-Rodríguez

  SciPost Phys. Proc. 1, 045 (2019) · published 22 February 2019 | Toggle abstract · pdf

  In this paper we established model independent bounds on the anomalous magnetic and electric dipole moments of the tau-lepton using the process $\gamma\gamma \to \tau^+\tau^-}$. We use data collected with the future $e^+ e^-$ linear collider such as the CLIC at $\sqrt{s}$ = 380, 1500, 3000 GeV, and we consider systematic uncertainties of $\delta_{sys}$ = 0$\%$, 3$\%$, 5$\%$. The theory predictions are a very good prospect for probing the dipole moments of the tau-lepton at the future $e^ + e^-$ linear collider at the $\gamma\gamma$ mode.

• Two-loop amplitude generation in OpenLoops

  Stefano Pozzorini, Natalie Schär, Max F. Zoller

  SciPost Phys. Proc. 7, 018 (2022) · published 21 June 2022 | Toggle abstract · pdf

  Numerical tools, such as OpenLoops, provide NLO scattering amplitudes for a very wide range of hard scattering amplitudes in a fully automated way. In order to match the numerical precision of current and future experiments, however, the higher precision of NNLO calculations is essential, and their automation in a similar tool highly desirable. In our approach, D-dimensional amplitudes are decomposed into loop-momentum tensor integrals with coefficients constructed in four dimensions and rational terms. We present a fully generic algorithm for the efficient numerical construction of the tensor coefficients, which constitutes an important building block for an automated NNLO tool.

• Spey: Smooth inference for reinterpretation studies

  Jack Y. Araz

  SciPost Phys. 16, 032 (2024) · published 26 January 2024 | Toggle abstract · pdf

  Statistical models serve as the cornerstone for hypothesis testing in empirical studies. This paper introduces a new cross-platform Python-based package designed to utilize different likelihood prescriptions via a flexible plug-in system. This framework empowers users to propose, examine, and publish new likelihood prescriptions without developing software infrastructure, ultimately unifying and generalising different ways of constructing likelihoods and employing them for hypothesis testing within a unified platform. We propose a new simplified likelihood prescription, surpassing previous approximation accuracies by incorporating asymmetric uncertainties. Moreover, our package facilitates the integration of various likelihood combination routines, thereby broadening the scope of independent studies through a meta-analysis. By remaining agnostic to the source of the likelihood prescription and the signal hypothesis generator, our platform allows for the seamless implementation of packages with different likelihood prescriptions, fostering compatibility and interoperability.

• Sifting composite from elementary models at FCCee and CePC

  Giacomo Cacciapaglia, Aldo Deandrea, Abhishek M. Iyer, Andres Pinto

  SciPost Phys. 14, 170 (2023) · published 26 June 2023 | Toggle abstract · pdf

  New Physics models with either an elementary or composite origin are often associated with a similar imprint in a direct search at colliders, case in point being the production of a light pseudoscalar in association with a monochromatic photon from the decay of a Z boson at future $e+e-$ colliders. We exploit the correlation between the discovery of a signal in the Z decays and electroweak precision measurements as a tool to distinguish a composite model from an elementary scalar one. Our results offer an appealing and rich physics case for future colliders and demonstrate how a lepton collider at the Z mass can be a discovery machine for new physics in the Higgs sector.

• Exploring unsupervised top tagging using Bayesian inference

  Ezequiel Alvarez, Manuel Szewc, Alejandro Szynkman, Santiago A. Tanco, Tatiana Tarutina

  SciPost Phys. Core 6, 046 (2023) · published 28 June 2023 | Toggle abstract · pdf

  Recognizing hadronically decaying top-quark jets in a sample of jets, or even its total fraction in the sample, is an important step in many LHC searches for Standard Model and Beyond Standard Model physics as well. Although there exists outstanding top-tagger algorithms, their construction and their expected performance rely on Montecarlo simulations, which may induce potential biases. For these reasons we develop two simple unsupervised top-tagger algorithms based on performing Bayesian inference on a mixture model. In one of them we use as the observed variable a new geometrically-based observable $\tilde{A}_{3}$, and in the other we consider the more traditional $\tau_{3}/\tau_{2}$ $N$-subjettiness ratio, which yields a better performance. As expected, we find that the unsupervised tagger performance is below existing supervised taggers, reaching expected Area Under Curve AUC $\sim 0.80-0.81$ and accuracies of about 69\% $-$ 75\% in a full range of sample purity. However, these performances are more robust to possible biases in the Montecarlo that their supervised counterparts. Our findings are a step towards exploring and considering simpler and unbiased taggers.

• Roy Glauber and asymptotic diffraction theory

  Per Osland

  SciPost Phys. Proc. 3, 016 (2020) · published 25 February 2020 | Toggle abstract · pdf

  This is a review of Glauber's asymptotic diffraction theory, in which diffractive scattering is described in terms of interference between semiclassical amplitudes, resulting from a stationary-phase approximation. Typically two such amplitudes are sufficient to accurately describe elastic scattering, but the stationary points are located at complex values of the impact parameter. Their separation controls the interference pattern, and their offsets from the real axis determine the overall fall-off with momentum transfer. Asymptotically, at large momentum transfers, the stationary points move towards singularities of the profile function. I also include some reminiscences from our collaboration.

• Annual modulation of dark matter signals: Experimental results and new ideas

  Felix Kahlhoefer

  SciPost Phys. Proc. 12, 004 (2023) · published 3 July 2023 | Toggle abstract · pdf

  Direct detection experiments searching for the scattering of dark matter particles off nuclei expect an annual modulation in their event rate. In this presentation, I will review the theoretical predictions and the experimental status of the search for annual modulations, with a focus on ongoing and planned experiments using NaI detectors. In particular, I will discuss the interpretation of the DAMA signal and related model-building efforts.

• To profile or to marginalize - A SMEFT case study

  Ilaria Brivio, Sebastian Bruggisser, Nina Elmer, Emma Geoffray, Michel Luchmann, Tilman Plehn

  SciPost Phys. 16, 035 (2024) · published 29 January 2024 | Toggle abstract · pdf

  Global SMEFT analyses have become a key interpretation framework for LHC physics, quantifying how well a large set of kinematic measurements agrees with the Standard Model. This agreement is encoded in measured Wilson coefficients and their uncertainties. A technical challenge of global analyses are correlations. We compare, for the first time, results from a profile likelihood and a Bayesian marginalization for a given data set with a comprehensive uncertainty treatment. Using the validated Bayesian framework we analyse a series of new kinematic measurements. For the updated dataset we find and explain differences between the marginalization and profile likelihood treatments.