W-DHCAL Analysis Overview

José RepondArgonne National Laboratory

Data Quality I

- Dead ASICs/FEBs/RPCs

Check noise runs Make table of dead regions as function of run-ranges This information needs to be implemented into the MC simulation

- Hot regions

Mostly hits close to ground connectors Regions need to be excluded (also in MC simulation)

- Square events and ASICs

Need simple tool to identify and

Reject events or Reject corresponding hits (Burak Bilki already has an algorithm)

Data Quality II

- Select time window

Only accept hits with ΔTS = -18, -19 (values might be different for muon runs!) Cut removes tail (6%) → minor effect on resolution (at most 3%) What to do about simulation?

- Eliminate double hits

Hits with identical x,y,z but different TS need to be eliminated ← important!

Time →

Energy reconstruction in the DHCALData

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) …

Clustering of Hits

Nearest neighbor clustering

Require 1 common side between hits Performed in each layer individually (no cross-correlation between layers) Determine un-weighted average of all hits in a given cluster (xcluster ,ycluster)

Other clustering algorithms

Conceivable, but not explored (is it necessary?)

1 cluster 2 clusters

TracksLoop 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 clustersfit straight line to (xcluster,z) and (ycluster,z) of all tracking clusters j calculate χ2 of track

request that χ2/Ntrack < 1.0inter/extrapolate track to layer isearch for matching clusters in layer i within

record number of hits in matching cluster

ij

jtrack

jcluster

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jcluster

track

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cmyyxxR itrack

icluster

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Track Segments

Define tracking layers for each layer i

e.g. 2 previous plus 2 following layers

Find track segment

Loop over all clusters in first tracking layer Look for a cluster within a small angle in the second tracking layer Calculate straight line through both clusters and extrapolate to 3rd and 4th tracking layer Look for a cluster close to the extrapolated positions in 3rd and 4th tracking layers Fit a straight line through the 4 tracking clusters

request that χ2/Ntrack < somethinginter/extrapolate track to layer isearch for matching clusters in layer i within

record number of hits in matching cluster

cmyyxxR itrack

icluster

itrack

icluster 5.2)()( 22

Noise Studies- Guang Yang (IIT) working on steel data

Aim: publish paper this year

- Identify dead regions

See above

- Measure noise rate

As function of x,y,z Produce average over detector (don’t include hot hits, as discussed above) Analyze noise runs and correlate to T and p

- Analyze time bins -20 and -21 (cross check)

0.02% of hits Correlate to noise runs taken close in (real) time Correlate this noise rate to the average number of hits/event in a given run

- Create noise files

To overlay with MC events (for systematic studies)

Muon analysis- Analyze muon runs

Trigger counters 30 x 30 cm2

Trigger counters moved to 9 individual positions ~5 Mevents Check timing-bin cuts

- Analyze electron/pion data

Trigger counters 10 x 10 cm2

Decent muon peak in almost all runs

- Use both tracks and track segments

- Align layers in x and y

- Measure

Efficiency, average pad multiplicity Versus x,y,z and t Study muon response as function of muon momentum

- Cross correlate

Muon peaks with noise rate in electron/pion data and with T/p

Simulation Strategy

GEANT4

Experimental set-upBeam (E,particle,x,y,x’,y’)

Points (E depositions in gas gap: x,y,z) RPC response simulation

Measured signal Q distribution

Hits

DATA Hits Comparison

ParametersExponential slope a1 , a2

Ratio between exponentials RThreshold T

Distance cut dcut

Charge adjustment Q0

With muons – tune a, T, (dcut), and Q0

With positrons – tune dcut

Pions – no additional tuning

RPCSIM ParametersDistance dcut

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

After tuning in ‘clean regions’…

1 exponential function 2 exponential function Different definition of ‘clean’ regions

RPC_sim_4 RPC_sim_3

Response over entire plane I

Response at edge of chamber reproduced by attenuating charge

Adequate

Interesting

Response over entire plane II

Higher multiplicity in top chamber

→ Temperature? → Gas poisoning ? → Increased p in bottom RPC (NO)

Tuning of Simulation

CERN data

Different operating conditions than a Fermilab → Tuning exercise needs to be repeated Due to Erik’s tent → very stable T conditions (not so at Fermilab)

Begin with

Defining ‘average’ operating condition in muon runs Tune simulation (5 parameters) in ‘clean’ regions Tune simulation at edges

- Burak Bilki working on this with Steel data

- Factorization in time and location

Assume that response in x,y,z correlated in time: R(x,y,z,t) = R(x,y,z) x R(t)

- Correct individual runs for changes as function of time

1 constant as function of time Constant determined from: bins (-20,-21), noise runs, muon peak ← to be studied

- Factorization transversely and longitudinally

Assume R(x,y,z) = R(x,y within 1 RPC) x R(RPC index) R(RPC index) = (ε0/εi )(μ0/μ i) …1 constant per RPC No correction for x,y non-uniformity of individual RPCs

- Correct for spill time

Determine correction from change in the position of the response peak(s) Also, study correction using response to muon tracks as function of spill time and x/y

- Estimate systematic uncertainties

Turn on/off corrections

Calibration

Electron dataData samples at following energy settings

1,2,3,4,5,6,7,8,12,20,30,40,(60) GeV

[Can we collect higher energies in August?

Requires Wolfgang’s asymmetric analyzing magnet setting (to correct for SR)]

Simulation

GEANT4 has no significant uncertainties (compared to the precision of our data) Response sensitive to dcut – parameter (last parameter to be tuned)

Measure

Response (linearity, resolution) Measure shower shapes Study software compensation

Longitudinal calibration

Being studied by Jacob Smith for Steel Technique applied by ATLAS Improve resolution?

Pion dataData samples at following energy settings

2,3,4,5,6,7,8,9,10,15,20,30,40,50,60,80,100,120,150,180 GeV

Will collect higher energies in August

180 – 300 GeV (preferentially negative)

Simulation

GEANT4 has significant uncertainties with the simulation of hadronic showers RPC_sim has no more parameters to tune (absolute prediction)

Measure

Interaction layer (preliminary algorithm exists) Response (linearity, resolution) Measure shower shapes Study software compensation

Longitudinal calibration

Being studied by Jacob Smith for Steel Improve resolution?

Plan for future data taking

August 2012

7 days at SPS Higher energies 180 – 300 GeV pions (negative) High energy (50,60,70) electrons (if possible)

November 2012

7 days at SPS High statistics points at 20, 180 GeV (negative) High-rate operating conditions at 180 GeV (negative) → Reduced HV together with high gain amplification Tile-cal technical prototype (requires dedicated 0-2 days)