PoS(Kruger 2010)013. Setting of the ATLAS Jet Energy Scale. Michele Petteni Simon Fraser University

Transcription

1 Setting of the ALAS Energy Scale Simon Fraser University he setting of the energy scale and its uncertainty in the ALAS detector is presented. After a brief introduction of the ALAS calorimeter and the reconstruction algorithms used in ALAS, the determination of the energy scale is described. Emphasis is given to the differing approaches adopted by ALAS. he current approach used for analysis is highlighted and results from early collision data are presented. he current energy scale for inclusive s with a transverse momentum of GeV, is determined with an uncertainty of -%. PoS(Kruger )1 Kruger : Workshop on Discovery Physics at the LHC December -, Kruger National Park, Mpumalanga, South Africa Speaker. On Behalf of the ALAS Collaboration c Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike Licence.

2 Setting of the ALAS Energy Scale 1. Introduction he determination of the energy scale is a central part of any physics analysis involving s in final states. he energy scale uncertainty is the dominant experimental systematic uncertainty in a number of physics analysis, such as the top mass measurement, and the measurement of the di- cross-section. he energy scale allows experiments to relate the energy and transverse momentum as measured in the calorimeter to the hadron level. hus aiming to correct for a variety of instrumental and detector effects, including the intrinsically different response of the calorimeter to electromagnetic and hadronic deposits, reconstruction effects, dead material, noise and pile-up, etc. In ALAS the energy scale is determined from Monte Carlo. he ALAS detector covers η <.9 around the collision point with layers of tracking detectors (covering η <.), calorimeters and muon chambers [1]. he calorimeter is composed of a high granularity liquid-argon electromagnetic sampling calorimeters (LAr), divided into three cryostats, which cover the pseudo-rapidity range η <.. he hadronic calorimetry in the range η < 1. is provided by a sampling calorimeter made of steel and scintillating tiles (ile). Enclosed in the end-cap cryostats ( η > 1.), LAr technology is also used for the hadronic calorimeters (HEC), matching the outer η limits of the end-cap electromagnetic calorimeters. he LAr forward calorimeters (FCal) is a liquid argon and tungsten/copper detector, and provides both electromagnetic and hadronic energy measurements out to η <.9. Reconstruction in ALAS ALAS uses a variety of reconstruction algorithms of which the anti-k t [] is the most commonly used. he anti-k t algorithm is a sequential recombination style algorithm which can take as input any -vector quantity. In ALAS, resolution parameters R =. and R =. are used. As inputs to the finder two clustering algorithms are adopted. For truth s all stable particles excluding muons and neutrinos are used. he clusters input to the finding are treated as if arising from massless particles. he topological clustering algorithm starts with seed cells required to have E > σ rms noise. Nearest neighbours with E >σ rms noise are added to the proto-cluster. If no neighbouring cells are found satisfying this requirement the proto-cluster is rejected. Neighbours are added until there are no more cells satisfying the neighbour requirement, at which point all the subsequent neighbouring cells are added as a "guard ring". A split-merge algorithm is applied to all final clusters. Due to the iterative nature of the algorithm, the topological clusters formed have no fixed size and no geometrical relation to the layout of the calorimeter. In order to provide an alternative fixed size signal definition, topological-towers are built by segmenting the topological clusters into a fixed size η φ =.1.1 grid. he physical size of the towers varies with η and longitudinal segmentation, but is generally the same size as this grid. PoS(Kruger )1. Determination of the Energy Scale he baseline for the energy scale determination is the electromagnetic () scale, as determined from the response of electrons in the LAr and ile calorimeters in test beam data. Subsequent

3 Setting of the ALAS Energy Scale Number of s ALAS Preliminary anti-k t R=. cluster s y <. MC QCD di-s Data s = ev 1 Number of constituents Number of clusters /. ALAS Preliminary Hadronic clusters in s anti-k t R=. cluster s LCW+JES y <.8, p > GeV Data MC QCD di-s 1 [mm] Cluster λ center Figure 1: (a) Number of constituents in s built with and topological clusters, and (b) distribution, λ center of the longitudinal centre of hadronic clusters in data (points) and Monte Carlo simulation (histograms). to this initial scale, s can be corrected on two levels, via the properties of the clusters or cells and using the kinematics. he level corrections can be derived independently of whether the constituent/cell level corrections are implemented. he constituent level corrections, however, also require an overall energy scale correction to be derived. Currently ALAS uses a energy scale calculated from di- Monte Carlo simulation..1 Constituent Level Corrections ALAS has adopted two methods for constituent based corrections: Global Cell Weighting (GCW) and Local Cluster Weighting (LCW) []. Both methods rely on the differences in shower profiles between electromagnetic and hadronic signals. Local Cluster Weighting is applied to the constituents before reconstruction. LCW differentiates hadronic and electromagnetic clusters based on shower depth, cell-energy density, cluster energy and η. Based on these variables the clusters can be weighted to correct for the hadronic response, dead material and out-of-cluster deposits using templates from the simulation of single pions. Fig 1 shows the Monte Carlo and data comparison for some of the inputs for the LCW. he cluster shapes match well although there is a shift of around one cluster for the number of constituents. here is good closure for most of the calorimeter except for the transition region between the central and end-cap cryostats, where discrepancies of up to % are observed. Global Cell Weighting is applied to s after reconstruction. Hadronic and energy deposits can be distinguished via the lower energy volume density, E/V, of the hadronic showers. Cell weights binned in E/V, η and calorimeter layer are calculated by minimising the energy resolution of reconstructed s in di- Monte Carlo. Hence by applying these weights to the cells of s in data, some of the difference between hadronic and response can be corrected for. Fig shows the E/V distribution for cells in a hadronic and calorimeter layer. here is good agreement between data and simulation in the hadronic layer, whereas the layer shows a slight deficit in data of cells with high energy density when compared to Monte Carlo. PoS(Kruger )1

4 Setting of the ALAS Energy Scale B ilebar1 mm ] N / ( E /V) [MeV 8 ALAS Preliminary anti-k t R=. cluster s Data s = ev MC QCD di-s mm ] N / ( E /V) [MeV ALAS Preliminary anti-k t R=. cluster s Data s = ev MC QCD di-s log [ E /V / (MeV / mm ) ] log [ E /V / (MeV / mm ) ] log [ E /V / (MeV / mm ) ] log [ E /V / (MeV / mm ) ] Figure : Cell energy density distributions used in the GCW calibration scheme in data (points) and Monte Carlo simulation (histograms) for cells in (a) the second layer of the barrel electromagnetic calorimeter and (b) in the second layer of the barrel hadronic ile calorimeter. Monte Carlo simulation distributions are normalized to the number of cells in data distributions. Response ALAS Preliminary R=. cluster s, y <. anti k t GeV < p < GeV 1 GeV < p < 1 GeV GeV < p < GeV 8 GeV < p < GeV Figure : energy response as a function of the fraction of the electromagnetic-scale energy deposited in the first layer of the ile calorimeter. f tile PoS(Kruger )1. Level Corrections he purpose of the energy scale (JES) is to correct the energy of s, either at the -scale or after constituent based calibrations, back to particle level. he current ALAS method derives the JES as a function of η and reconstructed p using the truth level information in di- Monte Carlo as a reference []. A further technique, Global Sequential Calibration (GSC), can also be applied using level quantities. he aim of GSC is not to correct the scale itself but to reduce fluctuations in the response in order to reduce the overall energy resolution. It uses the same technique as the main JES derivation but parametrises the response in a sequence of secondary variables. As the correction is applied after calibration, no additional energy scale is required.

5 ] ] Setting of the ALAS Energy Scale Number of s /.1 1 ALAS Preliminary anti-k t R=. cluster s +JES y <.8, p > GeV Data s = ev MC QCD di-s [GeV /de dn ALAS Preliminary anti-k t R=. cluster s +JES p > GeV,.1< y <.8 Data s = ev MC QCD di-s [GeV /de dn ALAS Preliminary anti-k t R=. cluster s +JES p > GeV, y <. Data s = ev MC QCD di-s Width E in E [GeV] 1 E in ile Barrel [GeV] (a) (b) Figure : Distribution in data (points) and Monte Carlo simulation (histograms) for a) width distribution, b) energy deposited by s second layer of the end-cap electromagnetic calorimeter and c) that deposited in the second layer of the hadronic calorimeter in the central region. Average JES correction ALAS Preliminary Monte Carlo QCD s AntiK, R=. s. < η <.8.1 < η <.8, p [GeV] Figure : Average energy scale correction as a function of transverse momentum at the electromagnetic scale p, for s in the central barrel (black circles) and endcap (red triangles) regions Fig show the dependence of the response on the fractional energy in the ile layer, one the variables used in the GSC method. It is clear that in parametrising the response as a function of this variable the overall response will have a smaller spread, and hence a more accurate determination. Fig show the data and Monte Carlo distributions of the inputs used in GSC. It can be seen that the width seen in data is not properly described by the Monte Carlo. Further tuning of the Monte Carlo is needed for the width to be described properly. (c) PoS(Kruger )1. Energy Scale Derivation Fig shows the Energy Scale correction for anti-k t, R =. scale s as derived in PYHIA di- Monte Carlo. he JES uncertainty is displayed in Fig a). his uncertainty is calculated by re-deriving the response after varying the Monte Carlo under different detector configurations, dead material budgets, noise in the calorimeter and via using an in-situ η inter-

6 Setting of the ALAS Energy Scale Relative JES Systematic Uncertainty AntiK t R=., JES Calibration,.< η <.8 Monte Carlo QCD s Underlying event (PYHIA, Perugia) ALPGEN, Herwig, Jimmy Additional Dead Material Noise hresholds JES calibration non-closure Fragmentation (PYHIA, Professor) Shifted Beam Spot Hadronic Shower Model LAr/ile Absolute Scale otal JES Uncertainty ALAS Preliminary p [GeV] Relative JES Calorimeter Uncertainty AntiK R=., JES Calibration,.< η <.8 E/p data, Monte Carlo QCD s MC-based calorimeter uncertainty Single particle uncertainty ALAS Preliminary p [GeV] Figure : Relative energy scale systematic uncertainty as a function of p for s in the central calorimeter barrel region (a) he total uncertainty is shown as the solid light blue area. he individual sources are also shown, with statistical errors if applicable, (b) due to the calorimeter measurement estimated from single particle analysis (hatched) and from Monte Carlo studies (solid). calibration to extend the uncertainty to the forward region. In addition different models for the hadronic shower, fragmentation and underlying event and an overall generator dependence are used. he dominant contributions to the uncertainty are the dead material description and the hadronic shower modelling, each of which contributes % at low p. At a slightly lower level of % are contributions from the noise description, the absolute -scale determination from test beam measurements and from the η inter-calibration between the different cryostat regions. he energy scale uncertainty is smaller the % for s with a p > GeV. Due to the uncertainty of the modelling of the Monte Carlo in the forward region (η >.), the energy scale uncertainty has been assessed to η <. using di- balance measurements derived from data []. he current energy scale does not include flavour dependence or corrections for the isolation. he effect of in-time pile-up was taken into account directly from data, using measurements of tower energy density as a function of the number of additional multiple interactions..1 Closure ests he calorimeter uncertainty is verified using the single hadron response as measured from minimum bias data []. he momentum computed from isolated tracks is used to calculate the response, E/p, for single particles. his is then extrapolated to a energy scale uncertainty via Monte Carlo pseudo-experiments. he comparison of the two calorimeter uncertainties is shown in Fig b), where the reduction in the uncertainty measurement from the in-situ method is evident. Fig displays the Data-MC double ratio of energy, as a function of p for the three additional calibration methods. As one can see there is good closure between the Monte Carlo and data and also between the different methods. he overall disagreement in the input distributions has a % impact on the energy scale. hese will improve with a better tuning of the Monte Carlo. PoS(Kruger )1. Conclusions he first determination of the energy scale with the ALAS detector has been performed. he energy scale is derived from Monte Carlo and applied to calibrated s. his method

7 1 Setting of the ALAS Energy Scale > /E <E GS 1. y <. ALAS Preliminary Data s= ev MC QCD di-s < E GCW+JES / E > 1. y <. ALAS Preliminary Data s= ev MC QCD di-s < E LCW+JES / E > 1. y <. ALAS Preliminary Data s= ev MC QCD di-s GS p [GeV] (a) p GCW+JES [GeV] (b) p LCW+JES [GeV] Figure : Mean calibrated energy over uncalibrated energy as a function of calibrated p for s constructed from topological clusters calibrated with (a) the global sequential, (b) the global cell energydensity weighting, and (c) local cluster weighting calibration schemes. gives a precision of % for s with p > GeV. In-situ methods, used as a cross-check, have already demonstrated a better precision. he switch to using calibrated cell inputs is also expected to give a smaller energy resolution. he precision of the measurement will increase with a better Monte Carlo modelling and with a more accurate calibration from Z peak measurements. he use of in-situ methods, such as γ + s, multi- balance and track s, is expected to not only to provide a valuable cross-check of the energy scale but also to improve the uncertainty especially for high-p t s. A significant reduction of the systematic uncertainty is to be expected in the near future []. References [1] he ALAS Collaboration, he ALAS Experiment at the CERN Large Hadron Collider JINS, S8, (8) [] M. Cacciari, G. P. Salam and G. Soyez, he anti-k t clustering algorithm, JHEP (8) [hep-ph/8.1189] [] he ALAS Collaboration, Properties of s and Inputs to Reconstruction and Calibration with the ALAS Detector Using Proton-Proton Collisions at s = ev, AL-CONF-- () [] he ALAS Collaboration, energy scale and its systematic uncertainty in ALAS for s produced in proton-proton collisions at sqrts = ev, AL-CONF--8 () [] he ALAS Collaboration, energy resolution and selection efficiency relative to track s from in-situ techniques with the ALAS Detector Using Proton-Proton Collisions at a Center of Mass Energy sqrts = ev, AL-CONF-- () [] he ALAS Collaboration, In-situ pseudo-rapidity inter-calibration to evaluate energy scale uncertainty and calorimeter performance in the forward region, AL-CONF-- () [] he ALAS Collaboration, energy scale and its systematic uncertainty in proton-proton collisions at sqrt(s)= ev in ALAS data, AL-CONF1- (11) (c) PoS(Kruger )1