Related papers: Particle identification in the GlueX detector with…
The efficacy of particle identification is compared using artificial neutral networks and boosted decision trees. The comparison is performed in the context of the MiniBooNE, an experiment at Fermilab searching for neutrino oscillations.…
Experimental particle physics demands a sophisticated trigger and acquisition system capable to efficiently retain the collisions of interest for further investigation. Heterogeneous computing with the employment of FPGA cards may emerge as…
In this paper we recreate, and improve, the binary classification method for particles proposed in Roe et al. (2005) paper "Boosted decision trees as an alternative to artificial neural networks for particle identification". Such particles…
Particle identification (PID) capabilities are studied by using the Time Projection Chamber (TPC) and a Time-Of-Flight (TOF) detector together at STAR. The identification capability of charged hadrons is greatly extended compared with that…
The GlueX experiment was designed to search for and study the pattern of gluonic excitations in the meson spectrum produced through photoproduction reactions at a new tagged photon beam facility in Hall D at Jefferson Laboratory. The…
Particle Identification (PID) plays a key role in heavy flavor physics in high-energy physics experiments. However, its impact on Higgs physics is still not clear. In this note, we will explore some of the potential of PID to improve the…
The GlueX experiment takes place in experimental Hall D at Jefferson Lab (JLab). With a linearly polarized photon beam of up to 12 GeV energy, GlueX is a dedicated experiment to search for hybrid mesons via photoproduction reactions. The…
The GlueX experiment is located in experimental Hall D at Jefferson Lab (JLab) and provides a unique capability to search for hybrid mesons in high-energy photoproduction, utilizing a ~9 GeV linearly polarized photon beam. The initial,…
The ePIC detector is being designed as a general-purpose detector to deliver the full physics program of the Electron-Ion Collider (EIC) in BNL USA. Particle Identification (PID) plays a crucial role in the EIC physics program. Over a wide…
The particle identification (PID) of hadrons plays a crucial role in particle physics experiments, especially in flavor physics and jet tagging. The cluster-counting method, which measures the number of primary ionizations in gaseous…
The MAGNEX large acceptance magnetic spectrometer is installed at the Laboratori Nazionali del Sud of the Istituto Nazionale di Fisica Nucleare (INFN-LNS) in Catania. In the past, MAGNEX experimental campaigns were performed using ion beams…
Jet flavour identification algorithms are of paramount importance to maximise the physics potential of future collider experiments. This work describes a novel set of tools allowing for a realistic simulation and reconstruction of particle…
The PID problem in high energy physics experiments is analysed with Bayesian technique. The corresponding applicable method is presented.
The lepton identification is essential for the physics programs at high-energy frontier, especially for the precise measurement of the Higgs boson. For this purpose, a Toolkit for Multivariate Data Analysis (TMVA) based lepton…
The primary motivation of the GlueX experiment is to search for and ultimately study the pattern of gluonic excitations in the meson spectrum produced in gamma p collisions. Recent lattice QCD calculations predict a rich spectrum of hybrid…
We develop, discuss, and compare several inference techniques to constrain theory parameters in collider experiments. By harnessing the latent-space structure of particle physics processes, we extract extra information from the simulator.…
Machine learning techniques are now well established in experimental particle physics, allowing detector data to be analysed in new and unique ways. The identification of signals in particle observatories is an essential data processing…
We demonstrate a smart laser-diffraction analysis technique for particle mixture identification. We retrieve information about the size, geometry, and ratio concentration of two-component heterogeneous particle mixtures with an efficiency…
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The…
Since 2015, with the restart of the LHC for its second run of data taking, the LHCb experiment has been empowered with a dedicated computing model to select and analyse calibration samples to measure the performance of the particle…