Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMultivariate side-band subtraction using probabilistic event weights
103
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
A common situation in experimental physics is to have a signal which can not be separated from a non-interfering background through the use of any cut. In this paper, we describe a procedure for determining, on an event-by-event basis, a quality factor ($Q$-factor) that a given event originated from the signal distribution. This procedure generalizes the side-band subtraction method to higher dimensions without requiring the data to be divided into bins. The $Q$-factors can then be used as event weights in subsequent analysis procedures, allowing one to more directly access the true spectrum of the signal.
rate research
Read More
Background treatment is crucial to extract physics from precision experiments. In this paper, we introduce a novel method to assign each event a signal probability. This could then be used to weight the events contribution to the likelihood during fitting. To illustrate the effect of this method, we test it with MC samples. The consistence between the constructed background and the background from MC truth shows that the background subtraction method with probabilistic event weights is feasible in partial wave analysis at BES III.
Principal Component Analysis (PCA) is a common multivariate statistical analysis method, and Probabilistic Principal Component Analysis (PPCA) is its probabilistic reformulation under the framework of Gaussian latent variable model. To improve the robustness of PPCA, it has been proposed to change the underlying Gaussian distributions to multivariate $t$-distributions. Based on the representation of $t$-distribution as a scale mixture of Gaussians, a hierarchical model is used for implementation. However, although the robust PPCA methods work reasonably well for some simulation studies and real data, the hierarchical model implemented does not yield the equivalent interpretation. In this paper, we present a set of equivalent relationships between those models, and discuss the performance of robust PPCA methods using different multivariate $t$-distributed structures through several simulation studies. In doing so, we clarify a current misrepresentation in the literature, and make connections between a set of hierarchical models for robust PPCA.
Results on event-by-event fluctuations of the mean transverse momentum and net charge in Pb-Au collisions, measured by the CERES Collaboration at CERN-SPS, are presented. We discuss the centrality and beam energy dependence and compare our data to cascade calculations.
The event-by-event analysis of high energy nuclear collisions aims at revealing the richness of the underlying event structures and provide unique measures of dynamical fluctuations associated with QGP phase transition. The major challenge in these studies is to separate the dynamical fluctuations from the many other sources which contribute to the measured values. We present the fluctuations in terms of event multiplicity, mean transverse momentum, elliptic flow, source sizes, particle ratios and net charge distributions. In addition, we discuss the effect of long range correlations, disoriented chiral condensates and presence of jets. A brief review of various probes used for fluctuation studies and available experimental results are presented.
The latest NA49 results on event-by-event transverse momentum fluctuations are presented for central Pb+Pb interactions over the whole SPS energy range (20A - 158A GeV). Two different methods are applied: evaluating the $Phi_{p_{T}}$ fluctuation measure and studying two-particle transverse momentum correlations. The obtained results are compared to predictions of the UrQMD model. The results on the energy dependence are compared to the NA49 data on the system size dependence. The NA61 (SHINE, NA49-future) strategy of searching of the QCD critical end-point is also discussed.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
