Related papers: A Bayesian Search for the Higgs Particle
A major goal of the future Large Hadron Collider will be the Higgs boson search. In this paper the discovery In this paper the discovery potential is described as a function of the Higgs mass showing that a Standard Model Higgs boson can be…
The Higgs particle is a new elementary particle predicted in the Standard Model of the elementary particle physics. It plays a special role in the theory of mass generation of quarks, leptons, and gauge bosons. In this article, theoretical…
New physics theories often depend on a large number of free parameters. The precise values of those parameters in some cases drastically affect the resulting phenomenology of fundamental physics processes, while in others finite variations…
In almost every scientific field, an experiment involves collecting data and then analysing it. The analysis stage will often consist in trying to extract some physical parameter and estimating its uncertainty; this is known as Parameter…
We present Bayesian Binary Search (BBS), a novel probabilistic variant of the classical binary search/bisection algorithm. BBS leverages machine learning/statistical techniques to estimate the probability density of the search space and…
Hierarchical models are increasingly used in many applications. Along with this increased use comes a desire to investigate whether the model is compatible with the observed data. Bayesian methods are well suited to eliminate the many…
We consider the issue of reporting the result of search experiment in the most unbiased and efficient way, i.e. in a way which allows an easy interpretation and combination of results and which do not depend on whether the experimenters…
Bayesian model selection provides a powerful and mathematically transparent framework to tackle hypothesis testing, such as detection tests of gravitational waves emitted during the coalescence of binary systems using ground-based laser…
Various Higgs factories are proposed to study the Higgs boson precisely and systematically in a model-independent way. In this study, the Particle Flow Network and ParticleNet techniques are used to classify the Higgs decays into…
We have reached a new era of particle physics in which the properties of the Higgs boson, in particular its mass, turned into precision observables. Therefore, it is necessary to have accurate predictions of these properties in models for…
In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data. The resulting method is…
The data analysis problem of coherently searching for unmodeled gravitational-wave bursts in the data generated by a global network of gravitational-wave observatories has been at the center of research for almost two decades. As data from…
In 1964, a new particle was proposed by several groups to answer the question of where the masses of elementary particles come from; this particle is usually referred to as the Higgs particle or the Higgs boson. In July 2012, this Higgs…
The discovery of the Higgs boson at the Large Hadron Collider marked a significant milestone in particle physics. The Higgs mechanism, a key theoretical framework, provides profound insights into the origin of particle masses and the…
Higgs boson is a fundamental particle, and the classification of Higgs signals is a well-known problem in high energy physics. The identification of the Higgs signal is a challenging task because its signal has a resemblance to the…
The prospects for discovering Higgs particles and studying their fundamental properties at future high--energy electron--positron and photon-photon colliders are reviewed. Both the Standard Model Higgs boson and the Higgs particles of its…
The experimental problem of converting a measured binomial quantity, the fraction of events in a sample that pass a cut, into a physical binomial quantity, the fraction of events originating from a signal source, is described as a system of…
We summarize the status of the Standard Model with special emphasis on the extraction of the Higgs boson mass using Bayesian inference.
These lectures concern two topics that are becoming increasingly important in the analysis of High Energy Physics (HEP) data: Bayesian statistics and multivariate methods. In the Bayesian approach we extend the interpretation of probability…
The Higgs boson is the most important, though yet undiscovered ingredient of the standard model of particle physics. Its detection is therefore one of the most important goals of high energy physics that can guide future research in…