Related papers: Fair Universe Higgs Uncertainty Challenge
Some of the biggest achievements of the modern era of particle physics, such as the discovery of the Higgs boson, have been made possible by the tremendous effort in building and operating large-scale experiments like the Large Hadron…
The studies of the Higgs boson couplings based on the recent and upcoming LHC data open up a new window on physics beyond the Standard Model. In this paper, we propose a statistical guide to the consistent treatment of the theoretical…
While in the early 90s High Energy Physics (HEP) lead the computing industry by establishing the HTTP protocol and the first web-servers, the long time-scale for planning and building modern HEP experiments has resulted in a generally slow…
HEP data-processing frameworks are essential ingredients in getting from raw data to physics results. But they are often tricky to use well, and they present a significant learning barrier for the beginning HEP physicist. In addition,…
High-energy collider physics in the next decade will be dominated by the LHC, whose high-luminosity incarnation will take Higgs measurements and new particle searches to the next level. Several high-energy e+ e- colliders are being…
We consider the problem of how decision making can be fair when the underlying probabilistic model of the world is not known with certainty. We argue that recent notions of fairness in machine learning need to explicitly incorporate…
Due to the growing adoption of deep neural networks in many fields of science and engineering, modeling and estimating their uncertainties has become of primary importance. Despite the growing literature about uncertainty quantification in…
We study the problem of identifying the set of \emph{active} variables, termed in the literature as \emph{variable selection} or \emph{multiple hypothesis testing}, depending on the pursued criteria. For a general \emph{robust setting} of…
We review in this paper the research status on testing the completeness of Quantum mechanics in High Energy Physics, especially on the Bell Inequalities. We briefly introduce the basic idea of Einstein, Podolsky, and Rosen paradox and the…
The evaluation of fairness models in Machine Learning involves complex challenges, such as defining appropriate metrics, balancing trade-offs between utility and fairness, and there are still gaps in this stage. This work presents a novel…
Information geometry can be used to understand and optimize Higgs measurements at the LHC. The Fisher information encodes the maximum sensitivity of observables to model parameters for a given experiment. Applied to higher-dimensional…
LEP precision on electroweak measurements was sufficient not to hamper the extraction of Higgs couplings at the LHC. But the foreseen permille-level Higgs measurements at future lepton colliders might suffer from parametric electroweak…
A Higgs-compatible boson has been observed at the LHC at CERN. We briefly review the role of the Higgs in particle physics and describe some of the current challenges in understanding the fundamental structure of the universe. Is there…
Measuring the CP symmetry in the Higgs sector is one of the key tasks of the LHC and a crucial ingredient for precision studies, for example in the language of effective Lagrangians. We systematically analyze which LHC signatures offer…
Survival models are used in various fields, such as the development of cancer treatment protocols. Although many statistical and machine learning models have been proposed to achieve accurate survival predictions, little attention has been…
The integration of physics-based knowledge with machine learning models is increasingly shaping the monitoring, diagnostics, and prognostics of electrical transformers. In this two-part series, the first paper introduced the foundations of…
Due to the high energy and luminosity of the LHC, the ATLAS experiment has a huge discovery potential for new physics. A Standard Model Higgs boson can be discovered over the full range of allowed masses, and its mass should be measured…
Recent studies have shown that quantitative concepts from quantum information theory can play a role in analysing collider physics, including elucidating new physics. In this paper, we study various QI measures including magic, trace…
I will present a review of the field of Hanbury Brown-Twiss interferometry in relativistic heavy-ion collisions. The "HBT puzzle" is explored in detail, emphasizing recent theoretical attempts to understand the persisting puzzle. I also…
Composed Image Retrieval (CIR) enables image search by combining a reference image with modification text. Intrinsic noise in CIR triplets incurs intrinsic uncertainty and threatens the model's robustness. Probabilistic learning approaches…