Hall B So(ware Status. Veronique Ziegler

Transcription

1 Hall B So(ware Status Veronique Ziegler

2 Physics Applica;on Design within the ClaRA SOA Physics applica;on design/composi;on based on services Development of services within ClaRA à Wri;ng a service simply requires to extend JService class à Test service in standalone mode using standard tools

3 Physics Applica;on Design within the ClaRA SOA The execute method implemented by extending JService runs the execu;on of the service à Sets Output Configura;on & calls a method to process the event à processevent runs the event thru the service reconstruc;on Design Object Model Need for design to be maintainable & extendable

4 Example of Event Reconstruc6on Development EC Petri- net diagram showing example service composi;on KF KF PCAL R CT FT TOF EB PID W R/W: Reader/Writer CT: Central Tracking FT: Forward Tracking KF: Kalman Filter EC: Electromagne;c Calorimeter PCAL: PreShower Calorimeter TOF: Forward & Central Time- Of- Flight HTCC/LTCC: Threshold Cerenkov EB: Event Builder PID: Par;cle ID HTCC LTCC

5 Online Event Display & Histogramming capabili;es SIDIS events with 1 control proton track Runs in Stand Alone mode or as an Orchestrator connected to the ClaRA plavorm Use as a tool to study backgrounds and check the reconstruc;on Study effect of backgrounds Noise analysis

6 So(ware Development Planning Working with Detector Groups Provide structure and Object Model () Include detector group algorithms within framework Give the applica;on back to detector group for tes;ng Done for FT Cal, next CND FT- Cal University of Genova FTCal Software status: 1. implementation of cluster algorithm completed 2. Algorithm tested on GEMC simulated data 3. Results consistent with expected performance

7 List of Ac;ve ClaRA Services Project Status Language Descrip6on EC reconstruc;on PCAL reconstruc;on TOF reconstruc;on FTOF calibra;on SVT calibra;on TRAC (Track Reconstruc;on Applica;on for CLAS12) Template to bring users onboard for further calibration development Forward Tagger Reconstruc;on Completed, included in service chain, developed using tested and validated legacy code Needs further op;miza;on, considering unifying object- model with that of EC, included in service chain Completed, included in service chain, developed using similar object- model code structure to EC, needs added panel- to- panel linking algorithms and valida;on Preliminary test of algorithms. Further tes;ng and algorithm development, database design & GUI in progress Preliminary test of implementa;on, histogramming & fidng using Scavis package Reconstructs charged tracks in the SVT with placeholders for MM. Contains DC pafern recogni;on algorithms for hit- based tracking. Uses KF method for track fidng. Completed implementa;on of Calorimeter cluster finder algorithm C++ CLARA services that implements the EC reconstruc;on algorithms and map u;li;es interfaces to databases CLARA services that implements the PCAL reconstruc;on algorithms CLARA services that implements the TOF reconstruc;on algorithms for the FTOF and the CTOF and interfaces to the CLAS6 configura;on database for the FTOF Services developed for data conversion into monitoring histograms, event filtering and storing of data, histograms and constants Service developed based on single module calibra;on C++ code and extended to include mul;ple modules monitoring Contains packages for track reconstruc;on algorithms and services for tracking in the central and forward detector systems, respec;vely CLARA services that implements the FT Calorimeter reconstruc;on algorithms; working with detector groups, the Tracker and Hodoscope reconstruc;on code will be included in the same package as HTCal using TRAC abstract classes and interfaced. (Next CND)

8 List of Ac;ve ClaRA Services (cnd.) Project Status Language Descrip6on HTCC Reconstruc;on HTCC cluster reconstruc;on exists as a C++ service C++ Simple clustering algorithm for HTCC reconstruc;on Event Builder Just started. Object Model to be under review soon (early March). Design of output banks for EvIO to ROOT conversion. Connect the outputs of the chained reconstruc;on services to build the full event (complicated tasks which requires expert involvement and cleaver scheme to create output bank structures) Geometry Service DC, TOF, PCAL systems included. Require detector groups to provide geometry document based on template. C++ Service to provide simula;on and reconstruc;on clients with detector geometry ced (CLAS12 event display) Bas been opera;ng since It is used for online detector diagnos;cs and offline analysis support. Histogram Services (examples) Need to create a package with histogramming and n- tupling tools Sta;s;cal data histogramming for reconstruc;on output valida;on example for SVT à Needs to create a package extendable and useable to other detectors U;lity Services Under development & review Contains various u;lity services such as magne;c field, banks and event reader/writer services (under review), jar Handling (clasjlib project) Data Mining Advanced and stable CLAS12 data management system capable of archiving processed data and providing on- demand data processing for physics analysis. Provides loca;on independent resource pooling (data and/or applica;on services) & u;liza;on of IT resources of collabora;ng Universi;es.

9 Event Reconstruction Completion Goals Quarterly)Progress) Develpmt. done 14% 18% Event'Builder' Forward'Tagger'ReconstrucAon' 62% PID$Detector'ReconstrucAon'' (EC/PCAL) Neutral'ParAcle'ReconstrucAon' 57% 49% Charged'ParAcle'Tracking'(TRAC)' CLAS12 Commissioning Feb 2016 CD4B Sept 2017 Apr$12' Jul$12' Oct$12' Jan$13' Apr$13' Jul$13' Oct$13' Jan$14' Apr$14' Jul$14' Oct$14' Jan$15' Apr$15' Jul$15' Oct$15' Dec$15' 9

10 Overall Clas12 Offline Software Completion Goals Quarterly)Progress) Develpmt. done... Monitoring'Services' Histogramming'Services' Data'Analysis'Package' CalibraCon'Constants'DB'Tables' Geometry'Service' Database'Tables'&'Services' VisualizaCon'(ced$12)' Full'simulaCon'digiCzaCon' Detector'simulaCon' SimulaCon' CalibraCon' Vertexing'' Event'Builder' Forward'Tagger'ReconstrucCon' PID$Detector'ReconstrucCon'' Neutral'ParCcle'ReconstrucCon' Charged'ParCcle'Tracking'(TRAC)' Event'ReconstrucCon' Apr$12' Jul$12' Oct$12' Jan$13' Apr$13' Jul$13' Oct$13' Jan$14' Apr$14' Jul$14' Oct$14' Jan$15' Apr$15' Jul$15' Oct$15' Dec$15' CLAS12 Commissioning Feb 2016 CD4B Sept 2017

11 So(ware Development Tasks Timeline March April Summer End of Year Review of exis;ng Object Model TRAC EB PCAL Development of template for detector groups to provide geometry and calibra;on (DB) info. : : Development of Virtual Machine for development and to run clara locally Data processing bench- marking Development of some common tools & libraries EvIO handling (standardiza;on of bank- reading & wri;ng), histogramming, Math u;li;es

12 BACK- UP SLIDES

13 GEMC EC PCAL FTOF LTCC DC HTCC Central Detector BST, BMT, FMT, CTOF, CND

14 Sensitivity/Digitization Detector Sensi6vity Digi6za6on Time Window BST 3 or 4 regions, 2 layers/reg, 3 modules/lay, 256 variable angle strips /lay. Charge Sharing, Electronic Noise. 3 bit ADC, region/layer/strip # 130 ns BMT/FMT 3 or 4 regions, 2 layers/reg, 3 6les/lay, 1000 strips /6les. Charge Sharing, Lorentz Angle. 12 bit ADC, region/layer/6le/strip # 130 ns CTOF 58 scin6llators, (photo- sensor quantum efficiency, a:enua;on length, effec;ve velocity*) Paddle #, (ADC, TDC*) 4 ns CND 3 or 4 layers, 48 scin6llators each, photo- sensor quantum efficiency, awenua6on length, effec6ve velocity, Birks Effect, paddle resolu6on Region, Paddle #, ADC, TDC 4 ns HTCC 12 sectors, 4 layers. Wavelength- dependent PMT quantum efficiency and gas, mirrors refrac6on indexes. PMT#, ADC, TDC 100 ns DC 3 regions 2 Superlayers/reg 6 layers/sl. DOCA, dri] velocity, cell resolu6on. Sector, Region, SL, L, wire #, (ADC, TDC*) LTCC 36 ellip6cal, 36 hyperbolical mirrors, WC*, PMT. (Wavelength- dependent PMT quantum efficiency and gas, mirrors refrac;on indexes*). Number of photoelectrons and 6ming. Sector, PMT# L/R, (ADC, TDC*) 250, 500 ns 100 ns FTOF PCAL EC RICH 3 panels, 5, 56, 120 paddles. (photo- sensor quantum efficiency, a:enua;on length, effec;ve velocity*) 15 layers, u,v,w views, 24 scin6llators/view, awenua6on length, effec6ve velocity, PMT gain, number of photons/charge 39 layers, u, v, w views, 36 scin6llators/view, awenua6on length, effec6ve velocity, PMT gain, number of photons/charge Wavelength- dependent PMT quantum efficiency and gas, mirrors refrac6on indexes. Mul6- channel PMT Sector, Panel, PMT#, ADC, TDC Sector, stack, view, strip, ADC, TDC Sector, stack, view, strip, ADC, TDC Mul6- channel PMT#, ADC, TDC FT Light Yield for PbWO4, APD Quantum Efficiency, gain, noise. PMT#, ADC, TDC 132 ns 4 ns 200 ns 200 ns 4 ns

15 Monitoring & Calibra6on Monitoring a) Event Displays i. Displays output of reconstruc;on as events are being processed (control room displays for detector monitoring) b) Histogramming services i. Occupancy plots (SVT cosmics data analysis) ii. Detector noise analysis, etc c) Service & Applica;on Monitoring i. Error handling ii. Incident monitoring Calibra;on a) Calibra;on Development i. TOF & EC Systems under development (using ROOT input) ii. SVT under development () iii. DC: planning stage- legacy algorithms and ROOT input