Related papers: Unbinned multivariate observables for global SMEFT…
We present a novel strategy to uncover indirect signs of new physics in collider data using the Standard Model Effective Field Theory (SMEFT) framework, offering notably improved sensitivity compared to traditional global analyses. Our…
Unfolding is an important procedure in particle physics experiments which corrects for detector effects and provides differential cross section measurements that can be used for a number of downstream tasks, such as extracting fundamental…
Many analyses in particle and nuclear physics use simulations to infer fundamental, effective, or phenomenological parameters of the underlying physics models. When the inference is performed with unfolded cross sections, the observables…
$\texttt{HEPfit}$ is a flexible open-source tool which, given the Standard Model or any of its extensions, allows to $\textit{i)}$ fit the model parameters to a given set of experimental observables; $\textit{ii)}$ obtain predictions for…
We report codes for the Standard Model Effective Field Theory (SMEFT) in FeynRules -- the SMEFTsim package. The codes enable theoretical predictions for dimension six operator corrections to the Standard Model using numerical tools, where…
Machine-learned force fields (MLFFs), especially pre-trained foundation models, are transforming computational materials science by enabling ab initio-level accuracy at molecular dynamics scales. Yet their rapid rise raises a key question:…
Recasting phenomenological Lagrangians in terms of SM effective field theory (SMEFT) provides a valuable means of connecting potential BSM physics at momenta well above the electroweak scale to experimental signatures at lower energies. In…
We introduce a novel methodology for addressing systematic uncertainties in unbinned inclusive cross-section measurements and related collider-based inference problems. Our approach incorporates known analytic dependencies on parameters of…
The Standard Model Effective Field Theory (SMEFT) provides a systematic framework to probe indirect effects of heavy new physics via precision measurements. While SMEFT constraints have been extensively studied using purely leptonic $Z$…
We establish the bounds on Wilson coefficients of the Higgs effective field theory (HEFT) mandated by unitarity and analyticity. These positivity constraints can be projected into the space of the standard model effective field theory…
The Standard Model Effective Field Theory (SMEFT) is a widely utilized framework for exploring new physics effects in a model-independent manner. In previous studies, Drell-Yan collider data has emerged as a promising signature due to its…
Multivariate analyses play an important role in high energy physics. Such analyses often involve performing an unbinned maximum likelihood fit of a probability density function (p.d.f.) to the data. This paper explores a variety of unbinned…
Projecting measurements of the interactions of the known Standard Model (SM) states into an effective field theory (EFT) framework is an important goal of the LHC physics program. The interpretation of measurements of the properties of the…
Universal machine learning interatomic potentials (uMLIPs) are reshaping atomistic simulation as foundation models, delivering near \textit{ab initio} accuracy at a fraction of the cost. Yet the lack of reliable, general uncertainty…
The Standard Model effective field theory (SMEFT) provides a general framework to include the dynamics of the beyond standard model physics residing at a certain higher energy scale $\Lambda$. We study the top-quark production along with a…
Recognizing the potential of effective field theories to posit multiple BSM scenarios in similar footing, with a possibility to compare them, we inspect the effects of 11 single scalar-multiplet extensions of the SM on the combined set of…
A global analysis of the Standard Model Effective Field Theory (SMEFT) with SFitter is performed using measurements of single top quark production and top quark decay processes from ATLAS and CMS at center-of-mass energies of 7, 8 and 13…
An extension of the xFitter open-source program for QCD analyses is presented, allowing for a polynomial parameterization of the dependence of physical observables on theoretical parameters. This extension enables simultaneous determination…
A machine-learning-based framework for constructing generator-level observables optimized for parameter extraction in particle physics analyses is introduced, referred to as the Optimal Observable Machine (OOM). Unfoldable differential…
Accurate representations of unknown and sub-grid physical processes through parameterizations (or closure) in numerical simulations with quantified uncertainty are critical for resolving the coarse-grained partial differential equations…