Study of The Diffractive Component of the Inclusive Z->e + e - and Z->     Cross Section Candidato: Marone Matteo Relatori: Dott.sa Arcidiacono Roberta Dott. Cartiglia Nicolo’ Scuola di dottorato in Scienza ed Alta Tecnologia, Indirizzo Fisica ed Astrofisica Ciclo XXIII, Ph.D. final dissertation

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Outline Introduction –LHC & CMS –ECAL Measurement of ECAL Thermal Stability –DCU –Results Study of the Diffractive Component –Pile-up Removal –Results 2/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation My Activity during Ph.D. My activity in ECAL: Installation and Commissioning Readout Software Development Detector Thermal Stability Analysis work: Diffractive Z Production /34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation LHC 4/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation CMS Detector Very good muon identification system Excellent electromagnetic calorimeter to resolve the energy of the electrons/photons Efficient tracker system to reconstruct the tracks and measure the momentum of the charged particles CMS physics goals: Perform precision measurements in the electroweak sector Higgs search Supersimmetry and new Physics 5/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Barrel crystals Pb/Si Preshower Barrel Supermodule ECAL 36 SuperModules, 1700 Crystal each 4 Endcap Dees, 3662 Crystals each 8 meters long 90 Tons of Crystal More than channels Endcap Barrel crystals Barrel Supermodule Trigger Light  Current AP D Crystal Energy  Light Current  Voltage  Bit MGPA ADC VFE Bit  Light FE DAQ Optical Fiber MB Physics reach of the ECAL, in particular the H->  discovery potential, depends on its excellent energy resolution. Requires high precision calibrations ECAL is an homogeneous calorimeter made of PbWO 4 crystals: 6/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Forward CMS W absorber & quartz plates from IP coverage -5.2 <  < -6.6 signal collection through Cherenkov photons 16 azimuthal segments in φ and 2 (EM) + 12 (HAD) long. segments. available on only one 11 m from IP Coverage 3 < |  < 5 Steel absorbers and embedded radiation-hard quartz fibers for fast collection of Cherenkov light Two calorimeters (minus and plus side) 7/34 Hadronic Forward Calorimeter CASTOR Calorimeter

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation ECAL Thermal stability: Hardware installation, calibration and commissioning Commissioning Read Out Software Development ECAL Thermal Stability

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Why Measure the Temperatures? ECAL response sensitive to variations of: Crystal transparency (irradiation) Intercalibration Temperature: ∂(LY)/∂T ~ -2%/ o K 1/M(∂M/∂T) ~ -2%/ o K High voltage: 1/M(∂M/∂V) ~ 3%/V affect the constant term M= Photodetector gain LY= Light Yeld Temperature stability within 0.05/0.1 o C Temperature monitoring system is needed 9/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Detector Control Units (DCU) Trigger Optical Fiber Light  Current APDCrystal Energy  Light Current  Voltage  Bit MGPA ADC VFE MB LVR MB VFE FE The DCUs are special ASIC chips able to read the following quantities: Very high granularity: 8 DCUs per TT ~ (1 each VFE and 3 in LVR boards) Useful tool to deeply investigate the status of the calorimeter Basic Read-out Geometry: 5X5 crystals (TT) 10/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation ECAL Thermal Stability A detailed study of temperature stability has been carried on during each collision period. DCU system provides one temperature reading every 10 (25) crystals. Temperature estimation obtained driving a known internal current through an external thermistor. The analysis has been performed using two independent monitoring system: DCU and Precision Temperature Monitoring (PTM) Results have been published in: CMS Paper (CFT ) “Performance and Operation of the CMS Electromagnetic Calorimeter” Published on Jinst R.Arcidiacono, M.Marone, “Ecal thermal stability during Cosmic Rays Run 2008”, CERN Detector Note number DN2010/003, Poor granularity: 4 sensor per SM Useful to calibrate the DCU sensors and to double check the results 11/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Results Very good spatial uniformity and stability in time. The RMS distribution of every temperature sensors estimates the detector thermal stability EB EE 12/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Results (2) Integration of the DCU in the readout (online) software Calibration of detector temperature thermistors Measured the Barrel and Endcaps temperature stability to be within the specification (0.05/0.1 o C). Measured the detector thermal time constant (in the “turn on” transition) to be ~2 hours in the barrel and ~6 in the Endcaps Help the ECAL community to investigate front end problems (APD leakage, dead channels,.. ) using the DCU data “ECAL Front-End Monitoring in the CMS experiment” presented at CHEP09: “International Conference On Computing In High Energy Physics And Nuclear Physics”, March /34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Data Analysis: Measurement of the Inclusive Z->e + e - and Z->     Cross Section Diffractive Z study

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Diffractive Physics at LHC The study of hard diffraction at LHC is feasible and it will offer the possibility to explore and test the ideas and models developed at much lower energies. Diffraction: inherently present in p-p collisions (30% of  tot ) Pomeron (IP): successful description within Regge theory of diffractive scattering 15/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Data Samples The data are divided in two periods: Pythia 6 (tune D6T and Z2) has been used to simulate the Drell-Yan (DY) events decaying into ee (μμ) PomPyt has been used to simulate: –Single Diffractive Z boson production –Dissociative (or Double Diffractive) How do we select the diffractive over the non diffractive part? 16/34 X X X

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Rapidity Gaps In diffraction the hadronization of the final states X and Y happens independently. If s is large enough, then there is a gap in rapidity in between LHC, s, M X and M y are very large The particles can easily cover a large zone of the CMS detector total acceptance We select diffractive events requiring visible rapidity gap Since gaps are exponentially suppressed in QCD fragmentation, a cut on rapidity gap increases the relative fraction of diffractive events. 17/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Z Candidates Selection Pass HLT trigger (Cluster E t >15 GeV) Reconstructed within the fiducial region Track trajectory, estrapolated to match the ECAL Cluster Reject Barrel Spikes EWK standard isolation criteria HLT trigger muon p t >9 GeV  <2.1 X 2 /NDOF < 10 Two muon stations fired 10 hit in the tracker and 2 in the pixel detector Transverse parameter < 2mm EWK standard Isolation Criteria Known problem in the ECAL calibration. No further conditions on the Z mass are requested Z -> ee Z ->  18/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Definition of the Variables We use the following variables: SumHF: the energy deposit in the HF  Max : max η of energy deposits in the detector  : fractional momentum loss of the scattered proton in the diffractive event MinHF: the minimum deposit in one HF side (+/−) 19/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation The conventional way to recognize a diffractive event is to look for rapidity gap in its particle flow. Since gaps are exponentially suppressed in QCD fragmentation5, the cut on rapidity gap increases the relative fraction of diffractive events. Diffractive Selection with MC In the data, LRG suppressed by the presence of the Pile-up We select events requiring HF=0 (2 units of gap) CMS Ln(M 2 x ) We have studied which was the best size of the rapidity gap to reject the background and select signal 20/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Pile-up The number of PU events follows a Poisson distribution A possible way to remove PU can be to require only one vertex in the event. The number of events having one vertex decreases when luminosity increases. PU interaction can be classified into: “hard” PU. Visible interactions (2.4<  ). Can be removed requiring 1 vertex “soft” PU. Interaction not detected and therefore not removed by the one vertex selection To correct for this loss of selection efficiency a method is presented 21/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation The conventional way to recognize a diffractive event is to look for rapidity gap in its particle flow. Since gaps are exponentially suppressed in QCD fragmentation5, the cut on rapidity gap increases the relative fraction of diffractive events. Event reweight Events collected at higher luminosity have less probability of being selected. Fit the fraction of events with no energy in HF as a function of the BX inst. luminosity. assign to each event a weight One vertex only 22/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation The conventional way to recognize a diffractive event is to look for rapidity gap in its particle flow. Since gaps are exponentially suppressed in QCD fragmentation5, the cut on rapidity gap increases the relative fraction of diffractive events.  distribution in diffractive events Using PomPyt, we simulate the  distribution with and without the HF=0 cut The simulations show that the diffractive signal is contained within the kinematic region [0-0.03]  Limiting the analysis to this kinematic region will also produce a good signal enhancement. 23/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Diffractive events have been selected requiring: energy below a minimum threshold in HF- or HF+ calorimeters only one vertex with a quality cut to avoid reconstruction of fake vertices Value of ζ within 0 < ζ < 0.03 Final Selection To measure the signal, the kinematic region has to be split in a certain number of bins 24/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Migration The reconstructed ζ is almost always underestimated if compared with the true value, because of: incomplete detector coverage particle thresholds. Consequently a migration from high ζ gen values to small ζ rec value is expected. To evaluate the impact of the migration effect, we have studied the resolution, purity and the migration maps. We chose then number of bins requiring the following limits: Influence the number of  bins 25/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Resolution ζ measured is, on average 30% lower than the generated value, and its resolution is 28%. kinematic region divided in two equal bins (0≤ ζ ≤0.015 and 0.015≤ ζ ≤0.03). Migration maps, purity and efficiency have been checked to be good Absolute Resolution Relative Resolution 26/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Unfolding of data distributions We have used the Pythia 6 D6T and Z2 Monte Carlo samples, generated without pile-up events: necessary to remove the pile-up contribution from the data events before being able to compare Example: MinHF Unfolding 1)Divide the distribution in energy bins 2)For each bin, calculate the fraction of events as a function of BX Instantaneous Lumi 3)Extrapolate to zero Lumi to obtain the pile-up free number of events 27/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Which MC fits better? Discrepancy between data and Monte Carlo in the description of the energy flow in the forward region. Impossible to choose one single Monte Carlo model for the description of the non diffractive part Forced to use two Pythia tunes, D6T and Z2 28/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Selected Events Data and MC events which pass the above selection: Different behavior of the two Pythia tunes. The number of selected data events is small, especially if compared to the Z2 tune prediction. Diffractive PomPyt events which pass the diffractive selection cuts is very large compared to data 29/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation ni Signal Significance Significance defined as: Assuming D6T to be the correct background description, then we would have a significance of about 2.6 σ. Considering the Z2 tune, this value drops down to ∼ 0 σ. To assess at 3 σ the presence of a signal, we would need ∼ 11 pb −1. The 5 σ signal is instead assessed with ∼ 29 pb −1. 30/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Cross Section Measurement Cross Section evaluated as: Where, A is the acceptance L the (effective) integrated Lumi  Z the efficiency of the Z boson selection  D efficiency of the diffractive selection 31/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Prospects for 2011 The request of no energy in both CASTOR (-6.6≤ η ≤-5.2) and HF calorimeters corresponds to a gap of ∼ 3.5 units, which makes this selection virtually background-free. CASTOR calorimeter has suffered of intermittent calibration problem during This study shows the possibility to use this cut to obtain a cross section measurement during /34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Conclusions In this thesis we have proposed and employed a novel method to select diffractive events. We have derived a weight function that weights diffractive events on the probability of having a rapidity gap at a given luminosity The extraction of the diffractive signal from the events that pass our selection criteria is further complicated by the current discrepancy between data and Monte Carlo in the description of the energy flow in the forward region. This mismatch, which is actually quite important, did not allow us to choose one single Monte Carlo model for the description of the non diffractive part but has forced us to use two Pythia tunes, D6T and Z2, which bracket the range of uncertainties. 33/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Conclusions (2) Within these constrains, and due to the quite low luminosity, we were not able to establish the presence of diffractive Z production, but only to see a production excess over one of the two Pythia tunes prediction. We are confident that the tools developed for this analysis can be applied to the much larger sample of the 2011 data, and we are looking forward to do the analysis in the next few months. 34/34

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Spares

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Read-out detector software The digitized data from the FE are read by the the off-detector electronics, consisting of 54 Readout Units each comprising three type of VME boards: Clock and Control System (CCS) Trigger Concentrator Card (TCC) Data Concentrator Card (DCC). Data reduction is achieved using a Selective Readout algorithm based on the classification of the detector in high al low interest regions (SRP) The ECAL Online software is responsible for the operation of the ECAL detector during data taking. The system is built on top of the CMS data acquisition frameworks (XDAQ) and interfaced with the run control (RCMS). In parallel, other relevant front end parameters are read out by the DCU system, heavily used during the commissioning phase

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Off-Detector Electronics CCS (clock and control system) : LHC clock and control signals + front-end initialization TCC (trigger concentration card): Encoding of TT Regional Calorimeter TT TT importance transmission to SRP (at Level 1 rate) DCC (data concentration card): Data reduction Transmission to central DAQ (at Level 1 rate) Overall the off-detector electronics is made by 18 VME-9U and 1 VME-6U crates controlled by 28 crate mounted PCs SRP (Selective Readout Protocol): send to the DCC the list of trigger towers to be read out

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation APD: currents (1 DCU for xtal = 1700/SM)‏ temperatures (1 DCU every 10 xtals = 170 values/SM): VFE & LVR: DCU internal temperatures (8x68 values /SM)‏ MEM box: VDD_1, VDD_2, 2.5 V, Vinj (4X2 values / SM)‏ DCU internal temperatures (1x2 values /SM)‏ LVR: 3 thermistors 2.5 V (12x68 values / SM)‏ 4.3 V (2X68 values / SM)‏ 0.1 V – inhibit (1X68 values /SM) What is monitored

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation DCU Software Architecture DCUConverter DCU Reader CondDB PC Storage Data PC Storage Data Files Converter DCS – Detector Control System Soap Write Calibrations XDAQ CondDB 8/22 DATA

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Detector Calibration Calibrations aim at the best estimate of the energy of e and  ’s Energy deposited over multiple crystals: E e/  = F e/  G  i c i A i Amplitude in ADC counts A i Intercalibration: uniform single channel response to a reference c i Global scale calibration G Particle-specific corrections (containment, clustering for e/  ’s) F e/  Intercalibration together with global scale feeds directly into the constant term

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation DCU graphical interface 14/28

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Z-> ee In situ Intercalibration The electromagnetic shower spreads over several crystals. linear system associated to a huge matrix have to be inverted in order to get the single inter-calibration factor Single region intercalibration coefficient can be obtained with an iterative method Can be used to tune Barrel/Endcap

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation 2000 ADC 2100 ADC Problem1: the same photon (or electron) gives a different answer (in ADC counts) depending upon the crystals it hits. each crystal has a specific light yield each photodetector has its specific gain Solution: find coefficients which make every crystal answer in the same way Intercalibration Intercalibration has been achieved in several ways, with different precision: EXAMPLE:BARREL - Using data collected in the laboratories : 4.5-6% - Cosmic ray (all): expose each SM to cosmic rays: 1-2 % - TestBeam (9 SM): electrons at a given E in each crystal ~ 0.3 %

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Z->ee events selection At the nominal LHC c.m. energy, the leptonic Z cross section is ~2nb: Decreasing to 0.9nb at 7 TeV Main background is due to QCD Dijets and γ + Jet: High transverse momentum leptons are the strong signature for Z decay ChannelCross section (nb) QCD Dijets~5x10 5 γ + Jet~2x10 2 (Leptonic) 24/28

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Problem2: the ECAL response depends on the energy of the incoming particles itself. The “linearity” of the calorimeter must be studied at the level of the per mille. Solution: find absolute references to tune the energy scale Z and W decays, J/Psi, pi Zero and others. Global scale

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Energy reconstruction in ECAL Brem Clustering The measurement of the electron E is hampered by the amount of tracker material and by the strong magnetic field. Electrons radiate brem. photons in the azimuthal direction Φ The ECAL “superclustering” is designed to take into account the spread and the brem ~ 35% of the photons radiate more than 70% of their energy ε ~ 99% for p>7GeV 26/28

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation 5/22 Temperature Measurements This chip drives an internal (known) current across a thermistor glued on the back of the crystals The thermistor temperature response has been studied prior in laboratory The in situ read-out circuit differs from the one used in calibration Another calibration has been performed using an independent monitoring system: Precision Temperature Monitoring PTM

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Z->ee variables H/E < 0.1 pb

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation ECAL Dead Channels ECAL shows a certain number of problems ( 1% of dead channels, DAQ related errors). Any missing channel directly affects the energy reconstruction. Therefore systematic studies are necessary to tune the official reconstruction algorithm with the real data. 27/28

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Cross Section Measurement We measure the inelastic pp cross section using pile-up (PU) events: The probability of having n pileup depends on the total  (pp) cross section. The pile-up depends on the “Luminosity per bunch crossing (L bx )”: max. during 2010 = ~ cm -2 s -1  Cross checked using the number of triggers in each bunch (L *  = N events) Pile up events are recorded by a high efficient stable trigger (e.g. Double ee, pt > 10GeV) The goal of the analysis is to count the number of vertices as a function of luminosity

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Result - fits Using the correction functions, we unfold the measured vertex distributions to obtain the correct distributions which we fit with a Poissonian function: PU= # Vertexes –1

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Results - Cross section For each of the PU distribution we obtain a value of the cross section and then these 9 values are averaged

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Proton Dissociation Diffractive events in which the proton, after the Pomeron exchange, splits into a leading baryon and into a system of particles (Y) It is interesting to calculate the Ratio Dissociative/Diffractive ~ 1/2.5

Torino- June 20 th 2011 Matteo Marone –Ph.D. Final Dissertation Migration Studies: Other Results Requiring 2 bins, migration map, efficiency and purity are within the limits 27/34