Analysis of DHCAL Events José Repond Argonne National Laboratory Frascati, February 6 - 10, 2012

The DHCAL Project RPC – based imaging calorimeter DHCAL = First large scale calorimeter prototype with Embedded front-end electronics Digital (= 1 – bit) readout Pad readout of RPCs (RPCs usually read out with strips) Extremely fine segmentation with 1 x 1 cm2 pads DHCAL = World record channel count for calorimetry Argonne National Laboratory Boston University Fermi National Accelerator Laboratory IHEP Beijing Illinois Institute of Technology University of Iowa McGill University Northwestern University University of Texas at Arlington DHCAL Collaboration Heads Engineers/Technicians 22 Students/Postdocs 9 Physicists 10 Total 41 …and integral part of

Calorimeters/configurations DHCAL 38 layers, each 1 x 1 m2 1.2 X0 Fe (+ Cu) absorber plates 350,000 readout channels Tail Catcher 14 layers, each 1 x 1 m2 8 1.7 X0 Fe (+Cu) + 6 5.9 X0 Fe (+Cu) absorber plates 129,000 readout channels Silicon – Tungsten Electromagnetic Calorimeter 30 layers, each 18 x 18 cm2 Variable thickness Tungsten absorber 10,000 readout channels Minimal Absorber Structure 50 layers, each 1 x 1 m2 0.27 X0 Fe (+Cu) absorber plates 461,000 readout channels

Tests in the Fermilab Test Beam Fermilab Test Beam Facility 120 GeV primary proton beam 1 – 60 GeV/c secondary beam (pions, positrons, muons…) Broadband muon beam 3.5 second long spills every minute Muon data taking +32 GeV/c secondary and 3 m Fe absorber DAQ rates 500 – 2000/spill DAQ triggered by a pair of 1 x 1 m2 Scintillator paddles Secondary beam data taking DAQ rates 50 – 500/spill DAQ triggered by a pair of 19 x 19 cm2 Scintillator paddles 1 x 1 m2 Scintillator Paddle A 1 x 1 m2 Scintillator Paddle B DHCAL Tail Catcher Trigger DHCAL Tail Catcher Trigger Cerenkov 19 x 19 cm2 Scintillator A 19 x 19 cm2 Scintillator B

World record in calorimetry The DHCAL in the Fermilab Test Beam Date DHCAL layers Tail catcher layers Total RPC layers Configuration Readout channels Number of Muon events Secondary events October 2010 38 DHCAL 350,208 1.4M 2.9M January 2011 13 51 DHCAL + TAIL CATCHER 470,016 1.6M 5.2M April 2011 14 52 + CALICE Si-W ECAL 488,952 2.5M 7.3M June 479,232 3.3M 6.0M November 50 Minimal Absorber 460,800 0.6M 4.5M TOTAL 9.4M 25.8M 488,952 readout channels World record in calorimetry

Energy reconstruction in the DHCAL Data Consists of hit patterns of pads with signal above 1 threshold and their time-stamps with 100 ns resolution Incident particle energy reconstruction To first order E ∝ N N = ∑layer Ni … total number of hits Correction for contribution from noise E ∝ N - Nnoise Nnoise … accidental hits Correction for variation in chamber inefficiency E ∝ ∑layer Ni ·(ε0 /εi) – Nnoise ε0 … average DHCAL efficiency εi … efficiency of layer i Correction for variation in pad multiplicity E ∝ ∑layer Ni ·(ε0 /εi) ·(μ0 /μi) – Nnoise μ0 … average pad multiplicity ` μi … average pad multiplicity of layer i Second order corrections Compensate for e/h ≠ 1 Saturation (more than 1 particle/pad) …

General DHCAL Analysis Strategy Noise measurement - Determine noise rate (correlated and not-correlated) - Identify (and possibly mask) noisy channels - Provide random trigger events for overlay with MC events (if necessary) Measurements with muons - Geometrically align layers in x and y - Determine efficiency and multiplicity in ‘clean’ areas - Simulate response with GEANT4 + RPCSIM (requires tuning 3-6 parameters) - Determine efficiency and multiplicity over the whole 1 x 1 m2 - Compare to simulation of tuned MC - Perform additional measurements, such as scan over pads, etc… Measurement with positrons - Determine response - Compare to MC and tune 4th (dcut) parameter of RPCSIM - Perform additional studies, e.g. software compensation… Measurement with pions - Compare to MC (no more tuning) with different hadronic shower models - Perform additional studies, e.g. software compensation, leakage correction… This talk This talk + Poster

Some cute muon events Note: Consecutive events (not selected) Look for random noise hits

DHCAL rotated by 100 Increased MIP detection efficiency Average pad multiplicity → As seen with cosmic rays

Estimation of contributions from noise Data collection (in general) Trigger-less (all hits) mode for noise, cosmics Triggered (record hits in 7 time bins of 100 ns each) for noise, cosmics, testbeam → Only hits in 2 time bins used for physics analysis Noise measurement These results from trigger-less mode In quantitative agreement with measurements with random trigger Results Noise rate measured to be 0.1 – 1.0 Hz/cm2 Rate strongly dependent on the temperature of the stack (FE-electronics embedded into stack and generates heat) Tail catcher in 4/2011 run DHCAL in 4/2011 run DHCAL in 10/2010 run Noise rate [Hz/cm2] 0.1 0.5 1.0 Nnoise/event in DHCAL + Tail Catcher (2 time bins) 0.009 0.05 0.09 Nnoise/event in DHCAL + Tail Catcher (7 time bins) 0.033 0.165 0.33 1 hit corresponds to ~ 60 MeV! Contribution from noise negligible for most analysis

Tracking Clustering of hits Loop over layers 1 cluster 2 clusters Performed in each layer individually Use closest neighbor clustering (one common side) Determine unweighted average of all hits in a given cluster (xcluster ,ycluster) Loop over layers for layer i request that all other layers have Njcluster ≤ 1 request that number of hits in tracking clusters Njhit ≤ 4 request at least 10/38(52) layers with tracking clusters fit straight line to (xcluster,z) and (ycluster,z) of all tracking clusters j calculate χ2 of track request that χ2/Ntrack < 1.0 inter/extrapolate track to layer i search for matching clusters in layer i within record number of hits in matching cluster

Geometrical alignment For each readout board i plot residual in x/y Rix = xi cluster- xitrack Riy = yicluster - yitrack Average residuals per front-end board in x in y

After SW alignment of each readout board Note expanded y-scale RMS 1104 → 62 μm RMS 265 → 21 μm 1 entry/readout board

Simulation Strategy Comparison Parameters GEANT4 Experimental set-up Beam (E,particle,x,y,x’,y’) Measured signal Q distribution Points (E depositions in gas gap: x,y,z) GEANT4 RPC response simulation Hits Parameters Distance cut dcut (within which only 1 avalanche) Charge adjustment Q0 (if needed) Exponential slopes a1, a2 (of signal spread in pad plane) Ratio R (between 2 exponentials) Threshold T (of discriminator) Hits Comparison DATA With muons – tune a1, a2, R, T, (dcut), and Q0 With positrons – tune dcut Pions – no additional tuning

x = Mod(xtrack + 0.5,1.) for 0.25 < y < 0.75 y = Mod(ytrack – 0.03,1.) for 0.25 < x < 0.75 Scan across one 1 x 1 cm2 pad Note These features not implemented explicitly into simulation Simulation distributes charge onto plane of pads…

Efficiencies, multiplicities Select ‘clean’ regions away from - Dead ASICs (cut out 8 x 8 cm2 + a rim of 1 cm) - Edges in x (2 rims of 0.5 cm) - Edges in y (6 rims of 0.5 cm) - Fishing lines (12 rectangles of ±1 cm) - Layer 27 (with exceptionally high multiplicity) Measured average response Note: Simulation of RPC response tuned to this data Tail towards higher multiplicity reproduced with 2nd exponential

Response over the entire plane Implemented dead areas of data in MC (= corresponding hits deleted) Note x/y-axis in [cm] not [pad number] x-distribution Well reproduced y-distribution Inter-RPC gaps well reproduced Fishing lines well reproduced Edges well reproduced

Calibration constants, etc… Calibration factors = mean of multiplicity distribution/(average over detector) = ε·μ/ ε0·μ0

Analysis of Primary and Secondary Beam Data 50 GeV pion showers Muon traversing stack No isolated hits photons, neutrons Isolated hits from

Unidentified μ's, punch through Results - October 2010 Data CALICE Preliminary Gaussian fits over the full response curve Unidentified μ's, punch through

Pion Response N=aE As expected, linear up to > 25 GeV CALICE Preliminary (response not calibrated) N=aE Standard pion selection + No hits in last two layers (longitudinal containment 16 (off), 32 GeV/c (calibration off) data points are not included in the fit. As expected, linear up to > 25 GeV

Energy Resolution for Pions (response not yet calibrated) CALICE Preliminary (response not yet calibrated) B. Bilki et.al. JINST 4 P10008, 2009 MC predictions for a large-size DHCAL based on results from small scale prototype. 32 GeV data point is not included in the fit. Standard pion selection + No hits in last two layers (longitudinal containment) Measurements confirm prediction

(response not yet calibrated) B. Bilki et.al. JINST 4 P04006, 2009 Positron Response CALICE Preliminary (response not yet calibrated) N=a+bEm Non-linearity Due to saturation (more than 1 hit/pad) Can be improved with software compensation Not detrimental: this is a hadron calorimeter! Data (points) and MC (red line) from small prototype test and the MC predictions for a large-size DHCAL (green, dashed line). Measurements confirm prediction

Compensation? Due to saturation (=more than one hit/pad) for em showers → Can be overcome with software compensation, fractal analyses… As usual in calorimeters with Iron absorbers Careful choice of segmentation (1 x 1 cm2 pads) → Compensation

Events taken with Minimal Absorber Stack 50 layers Cassette contain 2 mm Cu and 2 mm Fe 0.27 X0/layer → 13.4 X0 total 0.038 λI/layer → 1.9 λI total Beam 1,2,3,4,6,8,10 GeV/c secondaries 8 GeV e+ 16 GeV/c π+ 8 GeV/c π+

Concept of a Digital Hadron Calorimeter (almost) validated Conclusions The DHCAL provides new insight into showers Preliminary results have been presented using muons Geometrical alignment Response across pad Performance parameters in ‘clean’ regions Performance parameters over the entire plane Performance as function of time Comparison with track segment method Results compared to GEANT4 + RPCSIM simulation RPCSIM tuned to reproduce performance in ‘clean’ regions Overall reasonable agreement with data observed Preliminary results have been presented using the secondary beam Response to pions and positrons consistent with expectations Concept of a Digital Hadron Calorimeter (almost) validated

Backup Slides

RPCSIM Parameters Distance dcut Charge Q0 Slope a1 Slope a2 Ratio R Distance under which there can be only one avalanche (one point of a pair of points randomly discarded if closer than dcut) Charge Q0 Shift applied to charge distribution to accommodate possible differences in the operating point of RPCs Slope a1 Slope of exponential decrease of charge induced in the readout plane Slope a2 Slope of 2nd exponential, needed to describe tail towards larger number of hits Ratio R Relative contribution of the 2 exponentials Threshold T Threshold applied to the charge on a given pad to register a hit Only used in 2 exponential parameterization