Mitglied der Helmholtz-Gemeinschaft Data Acquisition at a particle physics experiments Sergey Mikirtytchiants, IKP FZJ GGSWBS'12, Batumi Aug

Slide 2 Outline. How to study interaction of an elementary particles? Particle identification and detectors. Digitizing of detector signals. Data acquisition system. Trigger. Example: Strange particle production in p-p collision. Summary.

Slide 3 How to study interaction of an elementary particles? incident target interaction ejectiles ? Kinematics (conservation law) Reconstruct ejectiles, unobservable directly (missing mass) Example: Strange particle production in proton-proton collision  total ~  b

Slide 4 What is needed to carry out such study? Accelerator Target Setup to detect and identify ejectiles Incident particle beam Particle: p; Energy: 2 GeV; Intencity: n b = /s Particle: p; Dencity (thikness): n t = /cm 2 Luminosity: L = n t n b f b = x x 10 6 = cm -2 s -1 Event rate: R =  total  L = cm -2 x cm -2 s -1 = 10 3 s -1

Slide 5 Particle identification. Energy losses in matter Cherenkov radiation Bending of trajectory in magnetic field B Time of flight Means the type of the particle (mass) and its momentum (P) Charged particles  E/  x [ MeV/cm ]  (velocity) R=P/eBR=P/eB → P=f(x,y) tof = (t 1 -t 0 )/L [ ns/m ]

Slide 6 Detectors. Temporal resolution TOF Spatial resolution Tracking Energy resolution E,  E Dead time MW Chambers Prop. Drift Scintillators Organic Inorganic Silicon Strip Pixel 2 ns 0.1 ns 10 ns 1 ns mm DG 10  m1  m MeV0.1Me V 0.2  s 0.1  s 10 ns 1  s 10  s 100  s DG - Detector Geometry

Slide 7 Digitizing (1). TDC — Time Digital Converters ADC — Analog Digital Converters Resolution -  [ns  /  bin] Range (full scale) – n-bits Nonlinearity -  = f(bin) Conversion time ~  s Resolution -  [AV / bin] Range (full scale) – n-bits Nonlinearity -  = f(bin) Conversion time ~  s Amplitude A Flash ADC ajaj 0 m T clk 0 < j < m Charge Q  t t0 t0 start t0 t0 stop t1 t1 t stop_m tn tn tj tj Multihit TDC: m times m times

Slide 8 Digitizing (2). Registers Scalers Coordinate detector (MWPC) Each input signal increments the counter content by ONE Data = Data + 1 Double pulse resolution ~ ns Max. speed ~ MHz Capacity – bits 0/ Latch Data MSB n 0 LSB2 1

Slide 9 Data acquisition. Common hardware structure DATA stucture Detectors Front end electronics Digitizers InterfaceComputer CAMAC VME LVDS Bus PCI Bus ….. ADC TDC REG SCL …. PreAmp Amplifier Discriminator …. D1...Dn HV, LV Gas, Cooling …. Trigger Level 1 ….. DATA storage. Header (Run number, comment) {Event number; Time stamp; Source ID (ADC_1); {Data_ADC_1}; Source ID (TDC_1); {Data_TDC_1}; … End of event}; // event size {Next Event}; Amount of DATA = x Accepted Trigger rate upto 100 MB/s !!! → Zero data suppression → Selective Trigger

Slide 10 Data acquisition. Common hardware structure Dead time: After each accepted event DAQ is insensitive during a period  (DT) Detectors Front end electronics Digitizers InterfaceComputer ….. …. t 0, gate …. Trigger ….. DATA storage. D1...Dn DT n inp n acc n inp Full Dead time: Full Live time: For a unit of time: Efficienty  of Data taking: n acc Average DT: = 100  s  /s /s /s /s0.01 Efficiency  increasing by → Clusters ( less DT ) → Selective Trigger (less n inp ) DT BUSY n acc

Slide 11 Data acquisition. Cluster structure Advantages: a) Flexibility; b) High performance … Detectors Front end electronics DigitizersInterface Computer ….. …. ….. DATA storage. D1 n acc cluster_1 Trigger n inp DT DAQ BUSY n acc …. t 0, gate …. Dn cluster_n cluster synchro cluster event builder

Slide 12 Trigger. Level 1: very fast, but pure rejection Level 2: stronger rejection, but slower ; needs data buffering Higher trigger levels: more selective and slower Aim: digitize and store data only in case of the certain conditions. Goal: reduce data losses and amount of stored data by ignoring of undesirable background events. Hardware logic based on Timing (restricted time window for TOF)  E,E (cut  by setting of high threshold Spatial selection by coincidence of certain SC's Dedicated digital signal processing based on special algoriythm (rough track reconstruction) Software based, can be applied ofline.

Slide 13 Example. Strange particle production in p-p collision near to threshold T p 1.8 – 2.2 GeV  total Searching for pair: (K + p), (K +  + ) Триггер: K + Aim of experiment:

Slide 14 COoler SYnchrotron COSY. p, d (un)polarized momentum GeV/c intencity upto /s Cooling electron: ~0.3 GeV/c stochastic: >1.5 GeV/c

Slide 15 Spectrometer ANKE. STT Target 1 m ND (SC, MWPC) H 2,D 2 cluster jet FD (SC, MWPC, MWDC) PD (SC, MWPC) K +,   p, d p, d

Slide 16 Frontend electronics of Scintillator Detectors. Y= 0 Front end electronics Sc PMT_up PMT_dn HV_up PS HV_dn Fan Out CFD Mean timer Fan Out CFD PdSo14_Tup → TDC, Scaler PdSo14_MT → TDC, Scaler, Trigger PdSo14_Tdn → TDC, Scaler PdSo14_Tdn → QDC PdSo14_Tup → QDC Y= L L=1m  =7 ns/m  t = 2L  = 14 ns

Slide 17 Raw spectra. Source: TDC's TOF spectra between So13 and Sa Source: QDC's Energy loss spectra So13 and Sa criterion efficiency of registration K + BG Valid Sa

Slide 18 Time of flight (TOF). TOF spectrum of So13 (& Sa1...23) criterion efficiency of registration K + BG TOF onl TOF ofl online offline Energy loss spectrum of So13

Slide 19 'Delayed Veto'. criterion efficiency of registration K + BG Del_Ve onl ~0.2 ~ 5x10 -3 Del_Ve ofl 0.2 < offline online Delayed Veto spectrum of Tel13 &  t-So & del_1 & del_2 & del_n Valid Sa TOF trigger unit So  t-Ve del_Ve Trigger Ve

Slide 20 Vertical angle. criterion efficiency of registration K + BG Vertical angle Vertical angles after K + -cuts in SC of Tel.13

Slide 21 Summary of Criteria criterion efficiency of registration K + BG Valid Sa TOF Del_Ve ~0.2 ~ 5x10 -3 TOF Del_Ve 0.2 < Vertical angle All 0.2 < 3.5x10 -6 Trigger rate suppresion 10 — 30 times 50 — 200 times Right Criteria allows to study rare processes !

Slide 22 Result: total cross section PLB 652, (2007) T p =2.16 GeV

Slide 23 Summary. Data Acquisition : Small dead time Cluster stucture Flexibility Trigger: Compromise of a criteria Cut Background Do not cut effect Online Data Handling: To control trigger criteria setting and thus be sure in quality of taken data For effictiveness data taking it is needed:

Slide 24 Questions. Detectors: 1. Which types of detectors can be used for tracking? 2. Which detectors have fast time response? Digitizers: 1. Types and main characteristics of a digitizers? Data Acquisition : 1. What is important for effictiveness data taking? 2. Ways how to increase the efficiency of data taking? Trigger: 1. What is aim of trigger? 2. Which criteria could be used on the first level of trigger?