Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 10,000 papers for “Particle identification”

Particle identification

H. Kolanoski, N. Wermes · 2020

Abstract The identity of a particle is fixed by its mass, lifetime and quantum numbers such as charge, spin, parity and flavour. A particle’s identity can be inferred by observing its interactions in matter, as for example the shower development of an electron or a photon, the specific energy loss of charged particles, the emission of radiation by a particle or the penetration capability of a muon. The mass of a particle can be determined by measurements of specific energy loss, time-of-flight or Cherenkov radiation when combined with a momentum measurement. High energy electrons can be separated from heavier particles through transition radiation. For particles which decay in the detector the mass can often be kinematically reconstructed from the decay products and the lifetime can be determined by the reconstruction of secondary vertices.

Cited by 0

Particle Identification

K. Hanagaki, J. Tanaka, M. Tomoto et al. · Lecture notes in physics · 2022

Abstract In this chapter, we discuss the method of particle identification, which is also called object identification because what we reconstruct or identify is usually not a particle but an object such as a charged particle trajectory, a jet that is a cluster of many particles, missing transverse energy and so on.

Cited by 2Open access

Particle Identification

Physics Requirement · 2007

Introduction E xcellent particle identification for hadrons and leptons over a large range of solid angle and momentum is an essential requirement for meeting the physics objectives of BABAR. In particular, measurements of CP violation require particle identification, both to reconstruct exclusive final states and to tag the quark content of the other B in the event. Information from the drift chamber, calorimeter, and the instrumented flux return can be used to identify most of the leptons and many of the hadrons. However, these systems are not sufficient to distinguish charged pions from kaons with momenta greater than about 0.7 GeV=c, or protons above 1.3 GeV=c, as is required to obtain efficient tagging and event reconstruction. To meet these requirements, dedicated particle identification will be provided by a combination of Cherenkov counters: a ring-imaging detector

Cited by 0

Particle identification

Lippmann, Christian · arXiv (Cornell University) · 2011

Particle IDentification (PID) is fundamental to particle physics experiments. This paper reviews PID strategies and methods used by the large LHC experiments, which provide outstanding examples of the state-of-the-art. The first part focuses on the general design of these experiments with respect to PID and the technologies used. Three PID techniques are discussed in more detail: ionization measurements, time-of-flight measurements and Cherenkov imaging. Four examples of the implementation of these techniques at the LHC are given, together with selections of relevant examples from other experiments and short overviews on new developments. Finally, the Alpha Magnetic Spectrometer (AMS 02) experiment is briefly described as an impressive example of a space-based experiment using a number of familiar PID techniques.

Cited by 0Open access

Particle identification

C. Grupen, B. Shwartz · Cambridge University Press eBooks · 2023

A summary is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Cited by 1Open access

CLAS12 Particle Identification

S. Stepanyan · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2010

as part of the CLAS12 reconstruction software to provide the tracking code with recommended track candidates. The resulting software achieved accuracy of greater than 99% and resulted in an end-to-end speedup of 35% compared to existing algorithms.

Cited by 0Open access

ALICE Particle Identification

Hussein Ezzelarab, Nada · CERN Document Server (European Organization for Nuclear Research) · 2014

During my stay at CERN, I have attended lectures mornings and worked on my research project under orienting guidance of my supervisors afternoons. The lectures were informative and pedagog- ically well-prepared and presented. Their contents was an excellent combination of theoretical and experimental topics in high-energy physics. Furthermore, I was privileged to visit the ALICE, CMS and LHCb detectors and the LINIAC accelerator. I have participated in workshop on ”MadGraph software”. I was furnished with excellent experiences and cultural exchanges with good colleagues from different countries. I got opportunities to know what the other students have done, in which projects they were involved and how they performed their scientific researches, especially regarding LHC data analysis. For my own project, I have to prove excellent experience with C++ and of course LINUX, ROOT and AliROOT. Tools such as Histograms, Graphs, Fitting, trees and many others were very essential. Furthermore, I am very proud getting a fruitful training in GIANT 3 but I exclusively use PYTHIA8 in order to generate pp collisions at different energies. we have to initialize fitting parameters for thee individual Gaussian fits for π ± , K ± and p(anti-p), Then we integrate over each component in order to extract the number of counts. The results are very convincing. They are nicely comparable with the published measurements.

Cited by 0Open access

Particle Identification with BELLE

Asish Satpathy · ArXiv.org · 1999

The working principle and performance of the BELLE particle identification device (PID), based on a hybrid system consisting of an array of high precision scintillator Time of Flight and silica Aerogel Counters, is discussed. The performances achieved in the beam tests are satisfactory and Monte Carlo tests of meeting physics objectives of BELLE are promising. Prior to the real experiment which is expected to commence in spring 1999, the BELLE PID is taking cosmic ray data for calibration and fine tuning.

Cited by 0Open access

Pileup per particle identification

Published For Sissa Springer, Daniele Bertolini, A Philip Harris et al. · 2014

Abstract: We propose a new method for pileup mitigation by implementing “pileup per particle identification ” (PUPPI). For each particle we first define a local shape α which probes the collinear versus soft diffuse structure in the neighborhood of the particle. The former is indicative of particles originating from the hard scatter and the latter of particles originating from pileup interactions. The distribution of α for charged pileup, assumed as a proxy for all pileup, is used on an event-by-event basis to calculate a weight for each particle. The weights describe the degree to which particles are pileup-like and are used to rescale their four-momenta, superseding the need for jet-based corrections. Furthermore, the algorithm flexibly allows combination with other, possibly experimental, probabilis-tic information associated with particles such as vertexing and timing performance. We demonstrate the algorithm improves over existing methods by looking at jet pT and jet mass. We also find an improvement on non-jet quantities like missing transverse energy.

Cited by 0

Pileup Per Particle Identification

Bertolini, Daniele, Harris, Philip, Low, Matthew et al. · arXiv (Cornell University) · 2014

We propose a new method for pileup mitigation by implementing "pileup per particle identification" (PUPPI). For each particle we first define a local shape $α$ which probes the collinear versus soft diffuse structure in the neighborhood of the particle. The former is indicative of particles originating from the hard scatter and the latter of particles originating from pileup interactions. The distribution of $α$ for charged pileup, assumed as a proxy for all pileup, is used on an event-by-event basis to calculate a weight for each particle. The weights describe the degree to which particles are pileup-like and are used to rescale their four-momenta, superseding the need for jet-based corrections. Furthermore, the algorithm flexibly allows combination with other, possibly experimental, probabilistic information associated with particles such as vertexing and timing performance. We demonstrate the algorithm improves over existing methods by looking at jet $p_T$ and jet mass. We also find an improvement on non-jet quantities like missing transverse energy.

Cited by 1Open access

Update in particle identification

Ullaland, O · CERN Bulletin · 2003

The main emphasis in particle identification during the last years has been on the perfection of the techniques and to include, from the conceptual design of the hardware, the need of the offline algorithms and the calibration systems. We will in this overview article concentrate on the main advances from the LEP time to the LHC epoch.

Cited by 0

Progress with Particle Identification

Ullaland, O · CERN Document Server (European Organization for Nuclear Research) · 2002

Some aspects of Transition Radiation andTime of Flight measurement

Cited by 0Open access