1 Hot/dead map 22 Jul 2011 Hiroyuki Sako JAEA 1. Run-by-run bad chip map 2. Hot/dead pixel map.

Slides:



Advertisements
Similar presentations
STAR Pixel Detector Phase-1 testing. 22 Testing interrupted LBNL-IPHC 06/ LG Lena Weronika Szelezniak born on May 30, 2009 at 10:04 am weighing.
Advertisements

13/02/20071 Event selection methods & First look at new PCB test Manqi Ruan Support & Discussing: Roman Advisor: Z. ZHANG (LAL) & Y. GAO (Tsinghua))
QUAD MODULE TESTING 18 th January 2013 Kate Doonan University of Glasgow.
October 31, 2008METDQM Study1 Summary from MET DQM Plot Scanning.
Cpe 252: Computer Organization1 Lo’ai Tawalbeh Lecture #2 Standard combinational modules: decoders, encoders and Multiplexers 1/3/2005.
1 Data Analysis Framework for DHC Tower Update - 07/28/2003 Kurt Francis - Northern Illinois University.
TB & Simulation results Jose E. Garcia & M. Vos. Introduction SCT Week – March 03 Jose E. Garcia TB & Simulation results Simulation results Inner detector.
Edge Detection Today’s readings Cipolla and Gee –supplemental: Forsyth, chapter 9Forsyth Watt, From Sandlot ScienceSandlot Science.
Status Report For Threshold Scans. Shaper/Sampler Drop Trims As promised new and improved trimming techniques have been developed. As suggested, we will.
ERP. What is ERP?  ERP stands for: Enterprise Resource Planning systems  This is what it does: attempts to integrate all data and processes of an organization.
SPiDeR  SPIDER DECAL SPIDER Digital calorimetry TPAC –Deep Pwell DECAL Future beam tests Wishlist J.J. Velthuis for the.
Chapter 4 Introduction to MySQL. MySQL “the world’s most popular open-source database application” “commonly used with PHP”
MAMMA data analysis Marco Villa – CERN 3 rd May 2011.
Thomas Jefferson National Accelerator Facility Page 1 EC / PCAL ENERGY CALIBRATION Cole Smith UVA PCAL EC Outline Why 2 calorimeters? Requirements Using.
1 xCAL monitoring Yu. Guz, IHEP, Protvino I.Machikhiliyan, ITEP, Moscow.
Commissioning and Operation of the CMS Tracker analogue optical link system at TIF with CMSSW: R.Bainbridge, A.Dos Santos Assis Jesus, K.A.Gill, V. Radicci.
Background Subtraction and Likelihood Method of Analysis: First Attempt Jose Benitez 6/26/2006.
Noise study 6/May/’13 Kazuki Motohashi - Tokyo Tech.
MICE Analysis Code Makeover Chris Rogers 14th September 2004.
RPC DQM status Cimmino, M. Maggi, P. Noli, D. Lomidze, P. Paolucci, G. Roselli, C. Carillo.
21 Sep 2009Paul Dauncey1 Status of Imperial tasks Paul Dauncey.
Jyly 8, 2009, 3rd open meeting of Belle II collaboration, KEK1 Charles University Prague Zdeněk Doležal for the DEPFET beam test group 3rd Open Meeting.
Pixel DQM Status R.Casagrande, P.Merkel, J.Zablocki (Purdue University) D.Duggan, D.Hidas, K.Rose (Rutgers University) L.Wehrli (ETH Zuerich) A.York (University.
Missing Et Before and After Shutdown Yuri Gershtein.
1 DT Local Reconstruction on CRAFT data Plots for approval CMS- Run meeting, 26/6/09 U.Gasparini, INFN & Univ.Padova on behalf of DT community [ n.b.:
1 Oct 2009Paul Dauncey1 Status of 2D efficiency study Paul Dauncey.
, Dan Peterson Apparent inconsistencies and other issues in the xBSM measurements of IBS Scans We have studied the pinhole and CodedAperture.
Muons at CalDet Introduction Track Finder Package ADC Corrections Drift Points Path Length Attenuation Strip-to-Strip Calibration Scintillator Response.
N. Saoulidou, Fermilab1 Study of the QIE Response & Calibration (Current Injection CalDet & Development of diagnostic tools for NearDet N.Saoulidou,
Development of a pad interpolation algorithm using charge-sharing.
Manqi Ruan Discussing & Support: Roman, Francois, Vincent, Supervisor: Z. ZHANG (LAL) & Y. GAO (Tsinghua)) DQ Check for CERN Test.
DT calibration software: tentative release schedule S.Bolognesi & S.Maselli & G.Mila Alignement&Calibration Meeting, 25 January 2008, CERN.
GLAST LAT Project LAT Instrument Analysis Meeting– Aug 29, 2005 Hiro Tajima, TKR Updates at SLAC 1 GLAST Large Area Telescope: TKR Updates at SLAC Hiro.
Pi0 Reconstruction with High p t Photons John Chin-Hao Chen.
General online meeting SLAC Nov 4, 1999 G.Crosetti, M.Lo Vetere, E.Robutti IFR online calibrations status and plans.
Chapter 2 Variables and Constants. Objectives Explain the different integer variable types used in C++. Declare, name, and initialize variables. Use character.
Monitoring Energy Gains Using the Double and Single Arm Compton Processes Yelena Prok PrimEx Collaboration Meeting March 18, 2006.
Stability Hidemitsu Asano. pixel unstable point seg#
Takashi HACHIYA, RIKEN software meeting
Offline meeting Azimuthally sensitive Hanbury-Brown-Twiss (HBT) Interferometry Lukasz Graczykowski Warsaw University of Technology Johanna.
RIKEN VTX Software Meeting
The Standard Analysis chain
Pixel Status Mar 12nd 2012 Maki KUROSAWA RBRC.
Analysis Test Beam Pixel TPC
Software Update Takashi HACHIYA.
Remaining Online SW Tasks
Online Calibration Online calibration: validation: L3fCalCalibTool –
How to turn on MICE Step IV
INTRODUCTION c is a general purpose language which is very closely associated with UNIX for which it was developed in Bell Laboratories. Most of the programs.
Radiation Laboratory Meeting
Maki KUROSAWA VTX Group 2014 Feb 20
2vtx tagged dijets mass resolution study
Digital Image Processing using MATLAB
Telecommunications Engineering Topic 2: Modulation and FDMA
Pixels.
Current status of run14 VTX alignment
CMS Pixel Data Quality Monitoring
Weekly Report Maya SHIMOMURA Run dependent check for VTX alignment
EMCal Run4 Recalibration Check Looking at K mass centroid and width
Hot/dead map Compared run by run difference Basic features Strategy
->K+K- Production at 62.4GeV Au+Au Collisions
Run4 Fiducial Match between Real and MC
Energy Calibration with Compton Data
RIKEN VTX software Meeting
Schedule after Shutdown
3E7_05151 wafer 11 IV curve Noise ~122e Source scans bad and
Current Status of the VTX analysis
The Image The pixels in the image The mask The resulting image 255 X
Variables and Constants
Presentation transcript:

1 Hot/dead map 22 Jul 2011 Hiroyuki Sako JAEA 1. Run-by-run bad chip map 2. Hot/dead pixel map

2 1. Run-by-run dead/hot chip selection Purpose To identify bad (dead or hot) chips for each run Selected “best” data set –200 GeV Au data after last repair –Run –~60 % of the total 200 GeV Au

3 Procedure For each chip, plot rate / chip for each run If the rate distribution has a clean single peak, fit by Gaussian to determine the rate range to select good runs (+-5  )

4 Rate/chip Example (B0) M0 M1 M2 M3 M4 Red=fit Blue=data C0 C7 C1 C2C3 C4C5C6

5 Range 1 Module 28, Chip 0 Range 0 Cut0 Cut1 –If the distribution has multiple peaks, check run dependence If there is a discrete change, separate run ranges –Fit the peak in each range separately to define the cuts –Run ranges are different for each chip »Mostly the ranges are common within a module (half-ladder) »Separating map for each chip is necessary in DB A pixel map for each chip in each run range Run boundary Rate Run number

6 Rate/chip example (B1) M29 M28 M27 Double peaks M26 M25 C0 C7 C1 C2C3 C4C5C6

7 Other examples

8 Some sick chips Continuous variations Scattered (unstable) distributions Those chips are masked forever

9 Summary of chips Sick(7) Dead(99) Multiple peaks(45)

10 Fit results Rate mean Rate sigma Barrel 0 Barrel 1 Module*8+chip

11 Check for the run-by-run cuts Dead chip (107/480) Hot chip (4/480)

12 2. Hot/dead pixel map A map in a long run range for each chip Dead and hot pixel criteria All chips in B0All chips in B1 Module 0 (B0) Module 20 (B1) Hot Nor mal Nor mal Dead

13 Pixel map examples Module0 Chip0 (B0) Module20 Chip0 (B1) Hot/Dead MapHit distribution Normal pixel Dead pixel

14 Hot/dead map example (2) Module 18 Chip 1 (B0) Run Run

15 Schematic view of hot/dead maps in DB Pixel-by-pixel map for each chip in a long run range –Run ranges different for each chip Chip 0 Chip 1 Chip 2 Chip 3 … Chip 479 Run number Pixel map 1A Pixel map1B Pixel map 0A Rate Cut criteria Pixel map 2A Pixel map 2B Pixel map 2C Chip-by-chip map for each run Rate cuts are determined in each run range

16 Status With 200 GeV data after last repair Determined rate cuts for all chips Chip maps (text) were made for all the runs Created pixel maps (text) for each chip for each run range To do Implementing offline codes for chip maps and pixel maps (to be done soon!) –offline/database/pdbcal/base –Offline/database/pdbcal/pg Interface –Offline/packages/svx/SvxPixelHotDeadMap

17 Chip map for each run (plan) One entry for each run Store only bad chips –short module –short chip –short status (dead=-1,normal=0,hot=1)

18 Pixel map in DB (plan) One data set for each chip for each run range bankId = module*8+ROC Start timestamp = start time of the first run End timestamp = end time of the last run Store only dead/hot pixels –unsigned char module –unsigned char ROC –unsigned char column –unsigned char row –signed char status (dead=-1,normal=0,hot=1) Note In packages/svx/SvxPixelHotDeadMap, a complete pixel map is made for a given run with a chip map and pixel maps No pixel map necessary for always dead or sick chips If there is a difference in hot/dead pixels in segments of runs (typically 10 such pixels per run) –Take OR of hot/dead pixels

19 Module Smoothly varying rates M10

20 M30 M31 M32 M33 M34 Scattered distributions

21

22

23 Hot/dead map example(3) Module 29 Chip 4 (B1) Run Run