Related papers: Fair Universe Higgs Uncertainty Challenge
This Report summarizes the results of the first 10 months' activities of the LHC Higgs Cross Sections Working Group. The main goal of the working group was to present the status-of-art on Higgs Physics at the LHC integrating all new results…
The ATLAS and CMS collaborations at the Large Hadron Collider (LHC) are studying the top quark in pp collisions at 7 and 8 TeV. Due to the large integrated luminosity, precision measurements of production cross-sections and properties are…
We study the uncertainties of the Higgs boson production cross section through the gluon fusion subprocess at the LHC (with $\sqrt s=7, 8$ and $14$ TeV) arising from the uncertainties of the parton distribution functions (PDFs) and of the…
Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and concern among software engineers. To tackle this issue, extensive research has been dedicated to conducting fairness testing of ML software, and this…
The Large Hadron Collider (LHC) provides data which give information on dark matter. In particular, measurements related to the Higgs sector lead to strong constraints on the invisible sector which are competitive with astrophysical limits.…
We describe the new developments in version 4 of the public computer code HiggsBounds. HiggsBounds is a tool to test models with arbitrary Higgs sectors, containing both neutral and charged Higgs bosons, against the published exclusion…
The Higgs field in the standard model (SM) may couple to new physics sectors related with dark matter and/or massive neutrinos. In this paper we propose a novel signature, the boosted di-Higgs boson plus \ET (which is either a dark matter…
The physics accessible at the high-luminosity phase of the LHC extends well beyond that of the earlier LHC program. This white paper, submitted as input to the Snowmass Community Planning Study 2013, contains preliminary studies of selected…
The study of the Higgs boson properties offers compelling perspectives for testing the effects of physics beyond the Standard Model and has deep implications for the LHC program and future colliders. Accurate determinations of the Higgs…
Reproducibility is a cornerstone of science. FAIR (findable, accessible, interoperable, and reusable) data is often a vital step towards testing the reproducibility of results. The implementation of FAIR principles in the astrophysical…
Experiments at the Large Hadron Collider (LHC) might test the picture of supersymmetric Grand Unification in particle physics. We argue that the identification of gaugino masses is the most promising step in this direction. Mass predictions…
The Higgs boson, discovered back in 2012 through collision data at the Large Hadron Collider (LHC) by ATLAS and CMS experiments, marked a significant inflection point in High Energy Physics (HEP). Today, it's crucial to precisely measure…
This thesis investigates three areas targeted at improving the reliability of machine learning; fairness in machine learning, strategic classification, and algorithmic robustness. Each of these domains has special properties or structure…
We introduce a new high dimensional algorithm for efficiency corrected, maximally Monte Carlo event generator independent fiducial measurements at the LHC and beyond. The approach is driven probabilistically using a Deep Neural Network on…
Machine learning models are central to people's lives and impact society in ways as fundamental as determining how people access information. The gravity of these models imparts a responsibility to model developers to ensure that they are…
We present up-to-date constraints on a generic Higgs parameter space. An accurate assessment of these exclusions must take into account statistical, and potentially signal, fluctuations in the data currently taken at the LHC. For this, we…
In this work we demonstrate that significant gains in performance and data efficiency can be achieved in High Energy Physics (HEP) by moving beyond the standard paradigm of sequential optimization or reconstruction and analysis components.…
A precision measurement of the LHC luminosity is a key ingredient for its physics program. In this contribution first of all we review the theoretical accuracy in the computation of LHC benchmark processes. Then we discuss the impact of…
In high-energy physics (HEP), both the exclusion and discovery of new theories depend not only on the acquisition of high-quality experimental data but also on the rigorous application of statistical methods. These methods provide…
Neural networks (NNs) are currently changing the computational paradigm on how to combine data with mathematical laws in physics and engineering in a profound way, tackling challenging inverse and ill-posed problems not solvable with…