1 Hadronic In-Situ Calibration of the ATLAS Detector N. Davidson The University of Melbourne.
Published byModified over 5 years ago
Presentation on theme: "1 Hadronic In-Situ Calibration of the ATLAS Detector N. Davidson The University of Melbourne."— Presentation transcript:
1 Hadronic In-Situ Calibration of the ATLAS Detector N. Davidson The University of Melbourne
2 The ATLAS Experiment ● One of two general purpose detectors built on the LHC ring. ● The LHC will provide 14 TeV p-p collisions starting from 2008 with a short run late 2007 of 900GeV and lower luminosity. ● Motivation for the experiment: – A search for the Higgs Boson – Potential to detect new physics beyond the Standard Model – Make precision measurements and further test the Standard Model
3 Importance of Jets in ATLAS Physics ● Quantitative measurements involving jets in the final state require a good reconstruction of jet energy. ● As well as Standard Model channels, jets are predicted in many discovery channels. The Higgs boson in the high mass region Physics beyond the standard model e.g. Supersymmetry SUSY signal Standard Model Background Requiring cuts on 4 high momentum jets + Missing Energy Source: ATLAS Physics TDR POOR JET CALIBRATION = BAD PHYSICS
4 Jet Reconstruction Jets Tower or Cluster Energies Summed Calibrated TowersCalibrated Clusters Hadronic Calibration Calibrated Jets Jet calibration Calorimeter Cells Energy deposited TowersClusters Cell energies summed and calibrated to the electromagnetic scale
5 Energy before calibration Jet Calibration ● Energy lost at the hadronic level: ● Shower in the calorimeter creates invisible and escaping particles ● Energy is lost in dead material ● Energy lost at the jet level: ● Particles at large angles to the main jet ● Low energy particles do not make it to the calorimeter ● Goal of calibration: ● Improve the resolution ● Correct the energy scale (goal is to within 1%).
6 Jet Calibration cont. ● Methods for ATLAS: – Derive weightings based on: ● Test Beam. Test a number of calorimeter modules with a beam of known particles and energy, then apply weighing scheme to all modules. ● Monte Carlo Simulation. – Uses physics events once the detector is in place and running: in-situ calibration ● Use known mass resonance. e.g. W->jj events. ● Use momentum balance method. e.g. Z + j or gamma + j ● The single hadron energy scale will also be checked: E/p method.
7 E/p Method ● Transfer of the inner detector absolute energy scale (0.5%) to the calorimeter by requiring E/p = 1. ● Uses isolated (single) charged hadrons. Calorimeter Energy (E) taken as the sum of cells or clusters within some volume of the calorimeter Inner Detector Momentum (p) taken from track of charged particle
8 Events with Single Charged Hadrons ● τ→π ± υυ provide a good candidate for E > 15 GeV. ● Minimum Bias covers E < 15 GeV ← My Work ● What is minimum bias? – Most scattering between protons is soft and only of interest for QCD studies. – Is present in all 'interesting' events with pile up as a background of low energy particles. p p ?
9 Attribute of Minimum Bias - Pythia simulation data ● With a large number of charged light hadrons such as pions: – 37% charged pions, 7% charged kaons, 5% protons, 1% leptons – the remaining 50% composed of neutral particles. Number of Tracks Max. at 1GeV coverage when Track P > 2GeV z Area of calorimeter constant with
10 The Ideal Single Hadron Case Vs. Minimum Bias Simulated 3GeV Pion in the calorimeter Simulated 3Gev Pion in a minimum bias Event Energy in Towers (MeV) ● Energy deposited in the calorimeters due to extra particles in minimum bias, leads to a biased E/p.
11 Results for 3GeV single pion ideal case ● Energy in the calorimeters was reconstructed by summing the energy of uncalibrated clusters within a cone of radius ΔR 2 =Δ 2 +Δη 2 For < 1.0 Region in which 99% of energy is contained in the cone
12 Results for Minimum Bias ● Initial track isolation requirement to remove impact of charged particles of R track isolation > 1.0 ● However, between 10±5% of tracks are not reconstructed which leads to a source of contamination from charged particles looking identical to the single hadrons.
13 This and neutral particle contamination can be reduced by limiting the number of clusters in the cone to 1. Reduces the mean E/p from 0.8 to 0.55 However, taking single cluster hadrons biases the result 5% lower than the ideal case. E/p distribution for single hadrons from minimum bias Contamination only contributes 1% to the total mean Cone ΔR=0.5
14 Taking a smaller cone size gives a similar result For cone size 0.2: Mean E/p total: 0.59 Mean E/p without contamination from neutral particles: 0.54 However there will always be a trade-off with the cone size. Decreasing cone size decreases the energy from contaminating particles. But also decreases the energy of the single hadron. Could potentially take larger cone and remove neutral contamination with selection based on variables of cluster shape. eg. Energy density Fraction of energy in the electromagnetic vs. hadronic calorimeters. A potential new approach being looked into is to examine E/p distributions for various cone sizes in order to estimate the contamination (and then subtract it)
15 Extra Notes The method will also be applied to a check of the Jet Calibration. The method can be used from late 2007 when ATLAS will take data on a short run at 900GeV and lower luminosity 1,000,000 minimum bias events per day expected A check of the E/p method can be done by comparing the results in the overlapping energy between minimum bias and events. Different methods used to reduce the bias caused from contaminating particles in the event.
16 Conclusions ● In many scenarios mass measurements involving final state jets will depend heavily on a precise knowledge of the jet energy scale. ● A check of the single hadron energy scale calibration is a vital step in determining the jet scale within to 1%. ● Work from simulations has shown isolated charged hadrons can be found in minimum bias event at LHC energies of 14TeV and their energy scale can be measured to within 5%. ● Work will continue to try to improve this to the level of 1%.