Norman Graf SiD Workshop, Eugene November 15, 2010 SiD Simulation Norman Graf SiD Workshop, Eugene November 15, 2010

Work Plan for 2012 1. Demonstrate proof of principle on critical components. 2. Define a feasible baseline design. 3. Complete basic mechanical integration of the baseline design… 4. Develop a realistic simulation model of the baseline design, including the identified faults and limitations. 5. Develop a push-pull mechanism, … 6. Develop a realistic concept of integration with the accelerator … 7. Simulate and analyze updated benchmark reactions with the realistic detector model. Include the impact of detector dead zones and updated background conditions. 8. Simulate and study some reactions at 1 TeV, including realistic higher energy backgrounds, demonstrating the detector performance. For 7 and 8, Specific physics channels will be investigated and defined by the Physics Common Task Group and supported by the Software Common Task Group. 9. Develop an improved cost estimate.

Beyond the LOI The detector model sid02 was a necessary compromise between the desire to include all the details of the engineering designs and the need to complete the large-scale physics benchmarking simulations in a timely fashion. Since then have developed a detector model which includes more realistic detectors. Benefits from engineering work done for the LOI. Allows much more realistic subdetector performance studies to be undertaken.

Calorimeter Model with Gaps gaps between calorimeter staves material can be specified parameters to compact modeled with one volume inside another layering in daughter volume

Non-Projective Stave HCal Model work in progress not ready for simulation yet need some additional infrastructure to support this geometry (boolean volumes, layering)

Pointing vs Non-pointing HCal Projective advantages: All modules are the same (+ smaller largest module) Pseudo-layer reconstruction (e.g. pandora) possible Consistent depth in phi Non-projective advantages: Inter-module cracks do not point to origin Current strategy is to pursue symmetric Hcal and only implement other model if needed. Current studies show minimal, if any, effect of cracks on PFA performance. Number of cracks reduced with octagonal layout.

0, 5 and 10mm steel skins in HCal Barrel Using single u jets of 50GeV, differences between HCal modules is not statistically significant. Further studies are ongoing. No strong motivation to pursue non-pointing stave geometry.

Improving RPC response simulations Characterize average multiplicity using current standalone simulation. Custom Geant4 program writes out individual hits from a shower in the RPC gas-gap. Processed using a FORTRAN program to calculate the charge spreading and populate the neighboring cells if the charge spreads beyond a cell boundary. Use DigiSim to incorporate this average cross-talk on a statistical basis and see whether the final results change. I If not, we can use this approach for physics analyses If there are significant differences, can the charge spreading be parameterized to provide a simple formula for the number of hit neighbors as a function of the distance between the MC energy deposition to the cell edge? This could then, with some work, be incorporated into the slic simulations. If not, and we need to account for a number of small depositions adding up to exceed some threshold, determine a fiducial region in the center of the cell for which no neighbors will be created. Modify slic to only write out the individual hit information in the border regions. Provide a C++ or java version of the FORTRAN code to incorporate into either slic or lcsim.

RPC simulation overview Had ‘Edep’ within D0 before? Geant4 find a ‘Edep’ in RPC Yes No charge! continue No Generate total charge according to C-spectrum Distribute on pads according to measured distribution No DHCal hits End of evt? Yes Apply threshold Fortran program (by Jose Repond) exists since a long time ago Re-written recently (L. Xia) in order to be included in SiD simulation Program speed is also significantly improved Lei Xia

Total charge generation Measured charge distribution for HV = 6.2 kV Before re-writing After re-writing Generated charge by randomly throwing points Using look-up table Slightly faster Lei Xia

Charge distribution on pads (I) Measured charge distribution as function of y in the pick-up plane D.Underwood et al. Before re-writing After re-writing Throw 10,000 points in x,y plane, calculate charge Q(r), sum up charge on 1 x 1 cm2 pads Using look-up table, much faster Better accuracy Distribute charge on 3x3 pads Ignore charge outside 3x3 This part of the new algorithm still need to be verified by old program Lei Xia

Charge distribution on pads (II) Total charge [pC] outside 3x3 pads: < 1% Charge distribution [pC] on 3x3 pads (6.3kV, Edep randomly generated on central pad) N(hit) distribution (thr = 0.6pC) Efficiency ~ 89% Multiplicity ~ 1.33 Lei Xia

Next step Verify whole algorithm with old program Very soon Verify using standalone Geant4 simulation Integrate into SiD simulation Should not be difficult, can be soon Lei Xia

Tracking Geometry LOI geometry consisted of cylinders and disks New geometry models each silicon sensor – rectangular detectors in barrel, trapezoidal detectors in endcaps, with module overlap in r,  and z, including dished endcaps.

Detector Optimization MIT group engaged in systematic study of HCal variants based on simplified SiD geometries using slic + SiD PFA (talk by R. Cowan). extending studies done for the LOI by Marcel Stanitzki using Mokka + MarlinReco (SiD-ish) primarily studying HCal depth and layout. Should we engage in a similar global exercise? Tracker layouts Detector aspect ratios Ecal design HCal absorber materials, layout, readout technologies.

Optimization Designs Defined a series of detectors designed to easily and efficiently optimize the HCal design (currently the critical path item). Simulate very deep HCal barrel and endcap 60 and 70 layers deep Analyze resolution as a function of the number of layers used in reconstruction. Generate variants to study absorber material, readout technology and dead material in cracks.

Scintillator (analog) sidloi_opt variants RPC (digital) sidloi_opt sidloi_opt_5mmskin sidloi_opt_octagonal sidloi_opt_w Scintillator (analog) sidloi_opt_scint sidloi_opt_scint_5mmskin sidloi_opt_scint_octagonal sidloi_opt_w_scint

Optimization Tools Code has been written to automate standard procedures needed for new detectors: Sampling Fraction determination MIP most-probable-value determination EM shower sampling fractions for Ecal, Hcal, Barrel, Endcap Had shower sampling fractions for Ecal, Hcal, Barrel, Endcap EM shower covariance matrices for particle ID Standard energy and position resolution plot generation.

Optimization Data Sets Single , , K0L, at fixed angles and energies for sampling fraction determination. Single particles (as above, plus e,  ,K ,p,…) at variable angles and energies to study clustering and tracking efficiency and resolution. Simple resonances (0,,) to study efficiency and resolution of two-particle states. Single quarks at fixed energies to study jet energy resolution (u,d,s). Single Z0 at fixed energies to study dijet mass resolution.

Diagnostic Plots /E vs 1/E Cluster Energy MC Energy vs Cluster E Residuals vs E /E vs E

Single Photon Response (Barrel) single photons of discrete energies 1,2,5,10,20,50 &100 GeV theta=90 degrees phi=0 degrees misses overlapping portion of barrel staves in EM calorimeter

Single Photon Linearity (Barrel) slope: 0.9852 intercept: 0.0201

Single Photon Residuals (Barrel) Full range ~2% But systematic trend obvious.

Single Photon Resolution (Barrel)

Single Photon Resolution (Barrel) slope: 0.167 intercept: 0.005

Single K0L Response (Barrel) single K0L of discrete energies 1,2,5,10,20,50 &100 GeV theta=90 degrees phi=0 degrees misses projective cracks of barrel modules in Had calorimeter

Single K0L Linearity (Barrel) slope: 1.020 intercept: -0.573

Single K0L Residuals (Barrel)

Single K0L Resolution (Barrel)

Single K0L Resolution (Barrel) slope: 0.4714 intercept: 0.0175

SiD Optimizations ECal resolution could be improved with thicker Si ECal thickness (cost) could be reduced ECal/Hcal separation is somewhat artificial Excellent high energy , e+/- response with analog HCal Octagonal Barrel geometry reduces number of phi “cracks” reduces amount of overlap in EM staves Is Tracker layout Optimal? Pixel Tracker option very attractive …

Silicon Detector Definition Expect that the detector design will change going forward. Need to implement some form of Change Control Board to ensure that the modifications motivated by physics studies or engineering constraints are formally communicated to the subdetector, simulation and reconstruction groups.

lcsim Reconstruction Tracking reconstruction now features planar silicon wafers, full hit digitization, clustering to form hits (with hit-size dependent uncertainties) and ab initio track-finding (talk by R. Partridge). Calorimeter code has been modified to support polygonal modules and PFA adapted to the new geometries(talk by R. Cassell). PFA code is being improved (talks by U. Mallik & R. Zaidan). Reconstruction is run-time configurable. Allows new users to begin running reconstruction without having to code Drivers, etc.

Clustering across modules Efficiency of cross module clustering. geometry Particle ID efficiency as a function of phi. shower shape Energy resolution as a sampling fractions Thin absorber Thick absorber +/- 1% 100 GeV photons Phi Energy

0,  / 0 Tests charged / neutral clustering in locally dense environment. Resonance mass is performance metric.

Jets Single quarks (u,d,s) at fixed energies and angles. Tests energy resolution in controlled environment.

Z0qq Single boson decaying to light quarks at fixed energies and angles. Tests invariant mass resolution as function of boson energy.

slicPandora Developed to support the CLIC SiD’ studies using analog scntillator readout Not a replacement for SiD PFA using digital RPC readout Full chain of analysis demonstrated generation of geometry description generation of track-states & calorimeter hit input including all relevant sampling fractions PFO creation and analysis overall energy scale to be determined See talks by J. McCormick (infrastructure) and P. Speckmeyer (use at CLIC).

Track Finding No significant changes to LOI track finding algorithm. Some structural/implementation changes to improve tracking performance, especially with large numbers of hits. A couple of known issues are being worked on: Forward efficiency is worse than LOI – fast checking of hit pairs, misplaced digitized hits. Events have been found where tracking takes a very long time. overlapping modules in barrel regions  4 hits / layer. Hits in multiple wafers in same layer can create ghost tracks. (see above) See talk by R. Partridge for details.

Tracking: Future Work Further optimization of the detector layout Number and position of layers Strip and pixel size and layout All pixel tracker option Additional studies of calorimeter assisted tracking Assist in kink finding and identification Identification of long-lived resonance decays &  conversions Systematic studies of the impact of: hit inefficiencies / dead channels, non-uniform magnetic field, beam backgrounds, …

Computing Resources LOI made extensive use of both the LCG and OSG grids. LCG: DESY, RAL Tier 1, in2p3, … OSG running opportunistically on the CMS grid @ FNAL In general, no problems with the concept software SiD software (slic & org.lcsim) just worked (also ran MarlinReco on LCG where it was installed). This process can no longer rely on individuals, it has to be institutionalized, automated and coordinated with ILD & CLIC within the ILC VO. See next talk by J. McCormick on Dirac. Not clear what, if any, resources remain available at SLAC.

Summary Simulation infrastructure essentially done. Reconstruction code being adapted for more complex geometries, (PFA & tracking). Workflow being streamlined & automated. Detector optimization studies being conducted before major event production. First set of detectors defined, and large set of diagnostic events available for analysis. Would like to see some physics benchmarks used CLIC CDR is “pilot” job. see talk by P. Speckmeyer)