Related papers: A Bayesian Search for the Higgs Particle
Bayesian hierarchical Poisson models are an essential tool for analyzing count data. However, designing efficient algorithms to sample from the posterior distribution of the target parameters remains a challenging task for this class of…
We present a Bayesian method for the identification and classification of objects from sets of astronomical catalogs, given a predefined classification scheme. Identification refers here to the association of entries in different catalogs…
The PC algorithm is a popular method for learning the structure of Gaussian Bayesian networks. It carries out statistical tests to determine absent edges in the network. It is hence governed by two parameters: (i) The type of test, and (ii)…
The statistical methods used by the ATLAS Collaboration for setting upper limits or establishing a discovery are reviewed, as they are fundamental ingredients in the search for new phenomena. The analyses published so far adopted different…
The Power Law Process, also known as Non-Homogeneous Poisson Process, has been used in various aspects, one of which is the software reliability assessment. Specifically, by using its intensity function to compute the rate of change of a…
Non-standard decays of the Higgs boson produced at the Large Hadron Collider can lead to signatures which can easily be missed due to non-adapted trigger or search strategies. Keeping electroweak symmetry breaking Standard Model-like we…
We present some of the most recent results from the CMS Collaboration on searches for Higgs-like particles in models beyond the Standard Model. Several rare and exotic decay modes of the Higgs boson are explored. The results of the searches…
Clustering is a powerful tool in data analysis, but it is often difficult to find a grouping that aligns with a user's needs. To address this, several methods incorporate constraints obtained from users into clustering algorithms, but…
We present an introduction to some concepts of Bayesian data analysis in the context of atomic physics. Starting from basic rules of probability, we present the Bayes' theorem and its applications. In particular we discuss about how to…
Over the past 10 years Bayesian methods have rapidly grown more popular as several computationally intensive statistical algorithms have become feasible with increased computer power. In this paper, we begin with a general description of…
We present a hierarchical Bayesian inference approach to estimating the structural properties and the phase space center of a globular cluster (GC) given the spatial and kinematic information of its stars based on lowered isothermal cluster…
There are many issues that can cause problems when attempting to infer model parameters from data. Data and models are both imperfect, and as such there are multiple scenarios in which standard methods of inference will lead to misleading…
I briefly review the Higgs sector in the Standard Model and its minimal Supersymmetric extension, the MSSM. After summarizing the properties of the Higgs bosons and the present experimental constraints, I will discuss the prospects for…
The application of Bayesian methods in cosmology and astrophysics has flourished over the past decade, spurred by data sets of increasing size and complexity. In many respects, Bayesian methods have proven to be vastly superior to more…
Results are reported from a search for non-standard-model Higgs boson decays to pairs of new light bosons, each of which decays into the oppositely charged dimuon final state. The new bosons may be produced either promptly or via a decay…
The Higgs boson, a fundamental scalar, was discovered at CERN in 2012 with mass 125 GeV, a mass that turned out to be a remarkable choice of Nature. In the Standard Model of particle physics, the Higgs boson is closely linked to the…
This report introduces general ideas and some basic methods of the Bayesian probability theory applied to physics measurements. Our aim is to make the reader familiar, through examples rather than rigorous formalism, with concepts such as:…
Gaussian boson sampling (GBS), a computational problem conjectured to be hard to simulate on a classical machine, has been at the forefront of recent years' experimental and theoretical efforts to demonstrate quantum advantage. The…
A procedure with a Bayesan approach for calculating upper limits to gravitational wave bursts from coincidence experiments with multiple detectors is described.
We assess the current state of searches at the LHC for additional Higgs bosons in light of both direct limits and indirect bounds coming from coupling measurements of the Standard Model-like Higgs boson. Given current constraints, we…