Jet-Met November-7-2002 G. Bernardi LPNHE - Paris Run Selection for p11 data -August-October = Post-Mixing Data, -Runs 161972 to 166782, p11.11, p11.12,

Slides:



Advertisements
Similar presentations
CBM Calorimeter System CBM collaboration meeting, October 2008 I.Korolko(ITEP, Moscow)
Advertisements

Reunion de groupe 29 oct. 2002G. Bernardi, LPNHE- Paris Reunion D0 Paris Programme de travail pour Calib On-line Prochaines etapes des etudes sur le bruit.
R. Zitoun, Stony Brook and LAPP CTF Meeting10 February Much Noise About Nothing? Robert Zitoun Stony Brook and LAPP CTF Meeting February 10, 2003.
Gregorio Bernardi / Paris 1 WH,ZH, WW and advanced techniques Higgs Sensitivity DØ Gregorio Bernardi.
Electromagnetic shower in the AHCAL selection criteria data / MonteCarlo comparison of: handling linearity shower shapes CALICE collaboration meeting may.
November 3rd, 2006 CALICE-UK, Manchester - A.-M. Magnan - 1 Noise studies DESY + CERN TB overview Anne-Marie Magnan Imperial College London.
Conveners Oct G. Bernardi LPNHE - Paris Why do we need Jet-id ? Because there are noise/fake jets What are the Noise/Fake jets ? 1)Noise jets (partly.
ADM Nov G. Bernardi for CALGO CALGO  TMBfix CALGO recommends to implement in the next TMBfixing: 1)New Hot Cell Killer 2)Restore ICR region to.
October 31, 2008METDQM Study1 Summary from MET DQM Plot Scanning.
Validation of DC3 fully simulated W→eν samples (NLO, reconstructed in ) Laura Gilbert 01/08/06.
Jan 17, 2007 Measuring Mass Difference using soft τ P T Slope 1 Measuring Mass Difference at LHC using soft τ P T Slope Alfredo Gurrola in collaboration.
Sept 30 th 2004Iacopo Vivarelli – INFN Pisa FTK meeting Z  bb measurement in ATLAS Iacopo Vivarelli, Alberto Annovi Scuola Normale Superiore,University.
ECAL Testbeam Meeting, Rome 28 March 2007 Toyoko Orimoto Adolf Bornheim, Chris Rogan, Yong Yang California Institute of Technology Lastest Results from.
Photon reconstruction and calorimeter software Mikhail Prokudin.
Using Track based missing Et tools to reject fake MET background Zhijun Liang,Song-Ming Wang,Dong liu, Rachid Mazini Academia Sinica 8/28/20151 TWiki page.
Exponential Functions. Our presentation today will consists of two sections. Our presentation today will consists of two sections. Section 1: Exploration.
Energy Flow and Jet Calibration Mark Hodgkinson Artemis Meeting 27 September 2007 Contains work by R.Duxfield,P.Hodgson, M.Hodgkinson,D.Tovey.
W  eν The W->eν analysis is a phi uniformity calibration, and only yields relative calibration constants. This means that all of the α’s in a given eta.
Mark Thomson Timing, Tungsten and High Energy Jets.
H → ZZ →  A promising new channel for high Higgs mass Sara Bolognesi – Torino INFN and University Higgs meeting 23 Sept – CMS Week.
Non-identified Two Particle Correlations from Run I Understanding drift chamber tracking – Tracker and candidatory – Two particle efficiencies/ghosts A.
Reconstruction techniques, Aart Heijboer, OWG meeting, Marseille nov Reconstruction techniques Estimators ML /   Estimator M-Estimator Background.
August 30, 2006 CAT physics meeting Calibration of b-tagging at Tevatron 1. A Secondary Vertex Tagger 2. Primary and secondary vertex reconstruction 3.
Gael Rospabe Lapp 15/04/08 CaloSoft Meeting 1 Ecal calibration using  0 Sabine Elles/ Marie-Noëlle Minard/ Gaël Rospabé.
October 14, 2004 Single Spin Asymmetries 1 Single Spin Asymmetries for charged pions. Overview  One physics slide  What is measured, kinematic variables.
8/26/02 D0 Calorimeter Task Force Stephanie Beauceron LPNHE - Paris 1 Offline zero suppression Aim: Understand the huge value of Missing E T at 1.5  Principally.
News from Jet/Etmiss Monica. Jet/Etmiss meeting yesterday (25/5) at P&P week – Mostly review of conf notes for ICHEP10 – Good review to check where we.
1 Bunch length measurement with the luminous region : status B. VIAUD, C. O’Grady B. VIAUD, C. O’Grady One problem in some data collections One problem.
Study of Standard Model Backgrounds for SUSY search with ATLAS detector Takayuki Sasaki, University of Tokyo.
Jet-Met November G. Bernardi LPNHE - Paris Zero-Suppression & Missing E T Compare Data Quality with: - May data = Pre-Shutdown Data, 154k-155k,
Study of neutrino oscillations with ANTARES J. Brunner.
Study of neutrino oscillations with ANTARES J. Brunner.
Calo preparation for 2015 Goals: -Trigger stability -Good calibration for HLT2 processing -Improved calibration ( timing, e/gamma response) for all calo.
1 Single top in e+jets channel Outline : - Data and MC samples - Overview of the analysis - Loose and topological cuts - MC efficiencies and expected number.
Update : Ratio of Three over Two Jet Cross Sections P.Kokkas, I.Papadopoulos, C.Fountas, I.Evangelou, N.Manthos University of Ioannina, Greece Senior Editor.
Met and Normalization Sarah Eno. I wanted to see if we can learn anything about the MET normalization issue using a toy monte carlo. first, we need a.
CALOR April Algorithms for the DØ Calorimeter Sophie Trincaz-Duvoid LPNHE – PARIS VI for the DØ collaboration  Calorimeter short description.
Missing Et Before and After Shutdown Yuri Gershtein.
Mark Dorman UCL/RAL MINOS Collaboration Meeting Fermilab, Oct. 05 Data/MC Comparisons and Estimating the ND Flux with QE Events ● Update on QE event selection.
DIJET (and inclusive-jet) CROSS SECTIONS IN DIS AT HERA T. Schörner-Sadenius (for the ZEUS collaboration) Hamburg University DIS 06, April 2006 Tsukuba,
Diphoton + MET Analysis Update Bruce Schumm UC Santa Cruz / SCIPP 03 July 2013 Editorial Board Meeting.
Jet/MET Trigger On-Call Report Ricardo Gonçalo – LIP Jet Trigger Meeting – 31/3/2015.
22 January 2009 David1 Look at dead material and fake MET in Jx samples mc08 10 TeV simulations, release J0 to J6 are tag s479_r586, ‘ideal geometry’
1 M2-M5 Efficiency and Timing checks on 7TeV beam data Alessia, Roberta R.Santacesaria, April 23 rd, Muon Operation
Effect of Recyling Events on MET results use a toy Monte Carlo to try to understand the effect that the recycling of min bias “pileup” events has on the.
Calorimeter Meeting 22 October 02 Stephanie Beauceron LPNHE - Paris 1 Attempts on: Response dependence on temperature Stephanie Beauceron LPNHE - Paris.
1 Measurement of the Mass of the Top Quark in Dilepton Channels at DØ Jeff Temple University of Arizona for the DØ collaboration DPF 2006.
Muons at CalDet Introduction Track Finder Package ADC Corrections Drift Points Path Length Attenuation Strip-to-Strip Calibration Scintillator Response.
Update on Diffractive Dijets Hardeep Bansil University of Birmingham 12/07/2013.
G. Eigen, Paris, Introduction The SiPM response is non-linear and depends on operating voltage (V-V bd ) and temperature  SiPMs need monitoring.
LAV efficiency studies with photons T. Spadaro* *Frascati National Laboratory of INFN.
December, Calibration of electromagnetic calorimeter of Hall A DVCS experiment Eric FUCHEY Ph.D Laboratoire de Physique Corpusculaire.
1 Bunch length measurement with the luminous region Z distribution : evolution since 03/04 B. VIAUD, C. O’Grady B. VIAUD, C. O’Grady Origin of the discrepancies.
Ian Ross Rose-Hulman Institute of Technology Mentor: Dr. Richard Teuscher University of Toronto ATLAS Group Cosmic Ray Cataloging.
CALORIMETER CELL MONITORING TOOL Viacheslav Shary.
1 Update offline zero suppression on missing E T Aim : Implementation of a true 2.5 cut Offline Studies of resolutions of Missing E T on zero bias events.
SUSY DILEPTON TRIGGER MONITORING
Emmanuel Monnier, Elodie Tiouchichine, Elisabeth Petit LAr Week
Missing ET resolution Aim:
Some introduction Cosmics events can produce energetic jets and missing energy. They need to be discriminated from collision events with true MET and jets.
Effect of t42 algorithm on jets
Searches for double partons
Jean-Roch Vlimant LPNHE november 6, 2002
First look at data/MC comparison for period 8 reference runs
Detector Configuration for Simulation (i)
Database Implementation Issues
The Perils of Missing pT Corrections
J/Y Simulations for Trigger
Stability of Calibration Data
Database Implementation Issues
Presentation transcript:

Jet-Met November G. Bernardi LPNHE - Paris Run Selection for p11 data -August-October = Post-Mixing Data, -Runs to , p11.11, p11.12, p Studies of the data are presented, Store by Store, Run by Run File by File (i.e. root file by root file) Data, from mid-August to end of October

Jet-Met November G. Bernardi LPNHE - Paris We start after the fix of Calo bunch mixing. Run , and go up to October 25th: Run  39 stores During this period: 395 Lumi runs / 64 Millions evt Studied Files (root-tuples) about 1-few Lumi-block each (2500 evts each).  33.9 Million Events / 203 Reconstructed runs Corresponding to a delivered LUMI: 17.7 pb -1 recorded 13.2 pb -1 Live fraction 76.0% The rest is not reconstructed with p11. Info presented on 214 runs: 33.3 Mevts / 12.3 pb -1 p11.11/12 Data, mid-August to end October

Jet-Met November G. Bernardi LPNHE - Paris Overview: MET, Hot cells, SET MET: 1 entry per file. August to October. Hot cells sometimes correlated to high MET 39 stores, visible in mean scalar E T also in RMS

Jet-Met November G. Bernardi LPNHE - Paris Overview: MET-x, MET-y Rms(MET-x) : 1 entry per file. Relatively stable : huge variations +/- 5 GeV Same story for MET-y

Jet-Met November G. Bernardi LPNHE - Paris Overview: MET-x, MET-y How to select runs? No clear separation on RMS (MET-x) or y Anisotropy of the calo response due to warm zones creates strong x-y offsets. Offset can be removed “by hand” (cf W x-sec kado/zitoun), but how to keep the event consistent??? Same story for MET-y

Jet-Met November G. Bernardi LPNHE - Paris A closer look : MET, Hot cells 4 stores in October (1828, 30, 32, 34) Hot cells: 1.5/event Compared to 4 stores at end of August (1686, 87, 89, 91)

Jet-Met November G. Bernardi LPNHE - Paris A closer look : MET-x 4 stores in October (1828, 30, 32, 34) Compared to 4 stores at end of August (1686, 87, 89, 91)

Jet-Met November G. Bernardi LPNHE - Paris A closer look : Scalar E T 4 stores in October (1828, 30, 32, 34) We see the changes of prescales, not the direct influence of lumi decrease 4 stores at end of August (1686, 87, 89, 91)

Jet-Met November G. Bernardi LPNHE - Paris A closer look : MET-x 4 stores in October (1828, 30, 32, 34) Not only the shapes are different, but the rms is also larger when there is a shaky behaviour. (also true in Met-y) 4 stores at end of August (1686, 87, 89, 91)

Jet-Met November G. Bernardi LPNHE - Paris Good Run definition Only Runs with >= 1000 events are considered. (203 runs to start with) Define MET-xy = sqrt [ (MET-x) 2 +(MET-y) 2 ] GOOD RUN: 1) require MET-xy < 3 GeV in at least 75% of the events of the run, and all events must have MET-xy < 5 GeV 2) Require mean scalar E T between 90 and 150 GeV We keep 123 good runs ( 60% of the total statistics, about 8.5 pb -1 ) Possibility to reject on a file by file base, since each file is lumi- block consistent  only 20% rejected. Same story for MET-y

Jet-Met November G. Bernardi LPNHE - Paris Good Runs: MET, Hot cells, SET MET: 1 entry per file. August to October. Hot cells sometimes correlated to high MET 39 stores, more regular, still visible in mean scalar E T also in RMS

Jet-Met November G. Bernardi LPNHE - Paris Good Runs: MET, Hot cells, SET MET: 1 entry per run: 123 runs selected August to October. Regularity improves with time.

Jet-Met November G. Bernardi LPNHE - Paris Good runs: MET-x, MET-y 1 entry per file. Rms(MET-x) : Relatively stable : variations have been reduced Same story for MET-y

Jet-Met November G. Bernardi LPNHE - Paris Good runs: MET-x, MET-y 1 entry per run Rms(MET-x) : Relatively stable : systematically shifted by about +1-2 GeV closer to 0. Sometimes correlation between large offset and large RMS

Jet-Met November G. Bernardi LPNHE - Paris Good runs : MET-x, MET-y 1 entry per file (9127 files for the 123 good runs) bumps are removed by the run selection criteria. Shift in x worse than in y. RMS also larger in x than in y.

Jet-Met November G. Bernardi LPNHE - Paris Good runs : MET, SET Dispersion in MET and SET diminished. Same story for rms.

Jet-Met November G. Bernardi LPNHE - Paris Conclusions “Warm zones” create problems to the missing E T, rendering the run selection delicate. Problem is amplified with the “soft” 2.5 sigma cut (let alone the famous 1.5 sigma…), so situation will naturally become easier with the “hard 2.5” of p13. To save Lumi, it is possible to provide in addition to the current Run selection, a file by file selection (one file = one lumi block in stable conditions). Currently we have 8.5 pb -1 of data which can be used w/o further correction. The additional 4 pb -1 have a MET offset too large to be used w/o a “recentering” function.