Related papers: A Bayesian Search for the Higgs Particle

The Minimal Supersymmetric extension of the Standard Model (MSSM) predicts the existence of three neutral and two charged Higgs bosons. Searches for these MSSM Higgs bosons are presented, based on proton-proton collisions recorded in 2011…

The structure of the Higgs sector is a major issue in the quest of a detailed description of the electroweak interactions. Most of the effort is devoted to the study of the standard model--like Higgs boson at 126 GeV, however the…

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…

Bayesian optimal design is a well-established approach to planning experiments. A distribution for the responses, i.e. a statistical model, is assumed which is dependent on unknown parameters. A utility function is then specified giving…

A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over…

The 40 years old Standard Model, the theory of particle physics, seems to describe all experimental data very well. All of its elementary particles were identified and studied apart from the Higgs boson until 2012. For decades many…

The search for Higgs boson pair ($HH$) production is at the core of the ATLAS experimental program, as it probes the Brout-Englert-Higgs mechanism, as well as new physics beyond the Standard Model. Based on the proton-proton collision data…

We present a Bayesian approach to machine learning with probabilistic programs. In our approach, training on available data is implemented as inference on a hierarchical model. The posterior distribution of model parameters is then used to…

Fast and reliable localization of high-energy transients is crucial for characterizing the burst properties and guiding the follow-up observations. Localization based on the relative counts of different detectors has been widely used for…

A Bayesian probability based approach is applied to the problem of detecting and parameterizing oscillations in the upper solar atmosphere for the first time. Due to its statistical origin, this method provides a mechanism for determining…

A Bayesian approach is developed to determine quantum mechanical potentials from empirical data. Bayesian methods, combining empirical measurements and "a priori" information, provide flexible tools for such empirical learning problems. The…

BPS, the Bayesian Problem Solver, applies probabilistic inference and decision-theoretic control to flexible, resource-constrained problem-solving. This paper focuses on the Bayesian inference mechanism in BPS, and contrasts it with those…

Vector boson fusion proposed initially as an alternative channel for finding heavy Higgs has now established itself as a crucial search scheme to probe different properties of the Higgs boson or for new physics. We explore the merit of…

We develop a new method for stochastic optimization using the Bayesian statistics approach. More precisely, we optimize parameters of chess engines as those data are available to us, but the method should apply to all situations where we…

An optimal choice of proper kinematical variables is one of the main steps in using neural networks (NN) in high energy physics. Our method of the variable selection is based on the analysis of a structure of Feynman diagrams (singularities…

Bi-clustering is a useful approach in analyzing biological data when observations come from heterogeneous groups and have a large number of features. We outline a general Bayesian approach in tackling bi-clustering problems in moderate to…

The search for the Higgs boson is one of the main physics goals of the Large Hadron Collider (LHC) and its two multi-purpose experiments, ATLAS and CMS. Vector boson fusion is the second largest production process for a standard model Higgs…

Table of contents 1. Introduction 2. Theory 3. Searches at LEP2 4. Results 5. Futur colliders 6. Final remarks

Eleven years ago, the Higgs boson was discovered at the LHC. I briefly survey the status of Higgs boson physics today and explore some of the implications for future Higgs studies. Although current experimental measurements are consistent…

We present a Bayesian data fusion method to approximate a posterior distribution from an ensemble of particle estimates that only have access to subsets of the data. Our approach relies on approximate probabilistic inference of model…