Related papers: A Bayesian Search for the Higgs Particle
Biclustering is a problem in machine learning and data mining that seeks to group together rows and columns of a dataset according to certain criteria. In this work, we highlight the natural relation that quantum computing models like boson…
This paper explores Bayesian estimation for categorical data, focusing on simple yet effective models that provide a foundation for applying more advanced methods accurately and reliably in real-world applications. We begin by revisiting…
The search for the Standard Model Higgs boson in the four lepton (electron and muon) final state with the ATLAS detector at the LHC is presented. The analysis strategy and the efficiency for selecting the signal and rejecting the background…
The Higgs boson was predicted in 1964 by British physicist Peter Higgs. The Higgs is the key to explain the origin of the mass of other elementary particles of Nature. However, only with the coming into operation of the LHC, in 2008, there…
Recent work has brought renewed attention to the possibility that the cross section for producing $n$ Higgs bosons grows large with $n$ at a sufficiently energetic hadron collider. In particular, this "Higgsplosion'" mechanism has been…
A search for Standard Model Higgs bosons produced in association with a high-energy photon and decaying to $b\bar{b}$ is performed using 133 fb$^{-1}$ of $\sqrt{s}=13$ TeV $pp$ collision data collected with the ATLAS detector at the Large…
This talk summarizes a method for analyzing the properties of any new scalar particle, which is systematic in the sense that it minimizes apriori theoretical assumptions about the properties of the scalar particle, leading to very…
Extensive searches for Higgs bosons and other new phenomena predicted by extensions of the Standard Model have been performed at LEP. A summary is given reviewing the principal aspects and presenting a selection of results.
The standard model has postulated the existence of a scalar boson, named the Higgs boson. This boson plays a central role in a symmetry breaking scheme called the Brout-Englert-Higgs mechanism (or the…
Recent searches for Higgs bosons in the context of extensions to the Standard Model of Particle Physics with the ATLAS detector at the Large Hadron Collider are discussed. All presented analyses use data recorded at a pp center-of-mass…
Identifying the Hamiltonian of a quantum system from experimental data is considered. General limits on the identifiability of model parameters with limited experimental resources are investigated, and a specific Bayesian estimation…
The production of a Higgs boson in association with a single top quark is one of a few channels which are sensitive for not yet excluded anomalous couplings of the Higgs boson to fermions. Multivariate analysis tools are used for the…
I describe ongoing work developing Bayesian methods for flexible modeling of arrival time series data without binning, aiming to improve detection and measurement of X-ray and gamma-ray pulsars, and of pulses in gamma-ray bursts. The…
Bayesian model selection methods provide a self-consistent probabilistic framework to test the validity of competing scenarios given a set of data. We present a case study application to strong gravitational lens parametric models. Our goal…
The Bayesian Block algorithm, originally developed for applications in astronomy, can be used to improve the binning of histograms in high energy physics. The visual improvement can be dramatic, as shown here with two simple examples. More…
The Bayesian evidence, crucial ingredient for model selection, is arguably the most important quantity in Bayesian data analysis: at the same time, however, it is also one of the most difficult to compute. In this paper we present a…
Prospective searches about Higgs physics and beyond the Standard Model are presented for the CMS and ATLAS experiments. Possible excesses of events in real data could be an indication of the existence of new particles, even with few hundred…
Identification of local structure in intensive data -- such as time series, images, and higher dimensional processes -- is an important problem in astronomy. Since the data are typically generated by an inhomogeneous Poisson process, an…
We propose a new solution to the hierarchy (naturalness) problem, concerning quantum corrections of the Higgs mass. Assuming the Higgs boson as a system with a self-similar internal structure, we calculate its two-point function and find…
This study investigates Bayesian ensemble learning for improving the quality of decision-making. We consider a decision-maker who selects an action from a set of candidates based on a policy trained using observations. In our setting, we…