Simulation & Algorithms Update Development of Simulation Tools Calorimetry E-Flow Algorithms

1. Rob McIntosh Vishnu Zutshi Arthur Maciel • Simulation & Algorithms Update • Development of Simulation Tools • Calorimetry E-Flow Algorithms Since Calor-2002 A. Maciel, (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

2. Simulation Tools Effort • The (SLAC) LCD-JAS Package: • Integrated; Detector Model(s) + • Event Simulation + Reconstruction • + Data Analysis • GISMO based simulation • Detector models have projective • geometries • Reconstruction/Analysis package • currently hardcoded for projective • geometry • The NIU Project: • Adopt a GEANT4 based simulation • The proposed NIU detector(DHCal) • has non-projective geometry • Adopt the LCD-JAS set of tools • The SLAC/NIU project: general plan is to converge towards a common • set of integrated detector models and simulation tools • (I) Implement a GEANT4 detector description with an output format compatible w/LCD-JAS • (II) Generalize LCD-JAS for the reconstruction & analysis of non-projective geometry models A. Maciel, for Robert McIntosh (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

3. The current plan is; ( , Rob McIntosh) • Start with a G4 description of the LCD detector • (Input geometry in XML format exists) • Decouple the simulation engine from ROOT • Interface it (output persistency) with LCD-JAS lcd-root Once we have the above model working; • Adopt a description language for a more general detector • GDML (CERN), Data Base + Drivers (E-Poly, Fr.) • Replace the detector model with the NIU prototype • Interface it with the general geometry upgraded LCD-JAS A. Maciel, for Robert McIntosh (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

4. A Clustering Strategy for Highly Segmented Calorimeters by Vishnu Zutshi • Two main stages; • Independent layer by layer (transverse) clustering • -- 1) Search for local maxima • -- 2) Neighborhood inspection around maxima • Longitudinal connection of layer clusters • -- 1) Inspect layer-to-layer correlations • -- 2) Implement a tracking filter to connect layers Calorimetry Tracking 1st tests applied to the LCD-”SD”(Mar2001) EM calorimeter • Stage-1 parameters and current (tentative) values; • -- thresholds; (i) 15 MeV for a local MAX • (ii) 0.5 MeV for cell accretion • -- neigh.search; hit 2cells (minimal connectedness inθbin , φbin) • -- no shared cells (for now, at least) + – single particles may generate multiple clusters in a single layer... A. Maciel, for Vishnu Zutshi (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

5. 20GeVπ0 Clusters from all layers superimposed A. Maciel, for Vishnu Zutshi (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

6. 5 GeV Electron Clusters from all layers superimposed x y view x z view y z view θ φ view Stage II – “Tracking”: expected to eliminate the out-lying spray A. Maciel, for Vishnu Zutshi (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

7. Cluster Distances from Extrapolated Track 5 GeV Electrons, B=0 5 GeV Electrons, B=5T A. Maciel, for Vishnu Zutshi (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

8. A Study on E-Flow by A. Maciel • Developing a tool for single particle clustering resolution • Neighborhood hit density gradients are proposed as a means for • -- identifying cluster boundaries • -- implementing a cluster split/merge strategy • Relies on the inspection of “calorimeter domains” – collections of • connected cells ganged as projective towers. Currently coded in • “box form”  ( n x m x l ) cells as segmented in (theta,phi,layer). • Currently being tested in the EM Calorimeter of the SLAC-LCD • Mar2001 “SD” detector model. Final aim is to apply to hadronic • calorimetry in digital mode. • E-Flow “domain methods” were 1st proposed in the ECFA-DESY • LC workshop at Saint Malo, April 12-15, 2002. See • http://www-dapnia.cea.fr/ecfadesy-stmalo/Sessions/Arthur_StMalo.pdf (ppt or ps) A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

9. Motivation • E-Flow, neutral particles; absence of tracking seeds to suggest cluster structure • High segmentation (small cells) allow a differential approach to cluster resolution • The collective cell approach cancels out the (small cell) sampling fluctuations • Equally applicable to both analog and digital readouts Method y-axis; dE/dV (arbitrary units) x-axis; #cells from cluster axis neighborhood hit density gradients Using radial dE/dV γ2 γ1 γ1 γ2 γ1 γ2 γ1 dr = 2cells A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

10. EM Shower Characteristics in the “SD” Detector Model • Profiles are averaged over samples of 5000 monochromatic single photons (10GeV) • All plots are longitudinal profiles, where the x-axis labels the layer number • Layer mean square radius definition; energy-weighted transverse shower radius (in each layer) A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

11. SD – 10GeV single γ’s in Em-Cal (5k evts.) shower-max GeV n.of cells hit-max energy-weighted transverse shower radius (in #of cells) A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

12. EM Pre-Clustering with Neighborhood Gradients Gmax • Shower profiles suggest pre-clustering • box of 4x4 cells. • Locate (4 x 4 x all) domain with highest • energy (or #hits). • Inspect neighborhood w/ grads; i.e. find • (Rmin, Gmin) and (Rmax,Gmax). • If Gmax > k*Gmin, then a secondary cluster • is declared found (currently using k = 2 ). • Rmin & Rmax determine a search area for • “next-hottest” (4 x 4 x all) domain. • Cross check that γ2 cluster also “sees” γ1 • Use both sets of R&G(min,max) to re-size clusters. Gmin Rmin Rmax search area for γ2 γ1 Rmin+1 Rmax + size A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

13. π0( 10GeV )γ γ5K single-π0 events γγdistance, generated (cm) 1= layers 0 -- 9 2= layers 10--19 neighborhood 2 is tested if neighborhood 1 fails 1 cell = 0.5 cm γγdistance, reconstructed (#of cells) 5000 events superimposed (#of cells) A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

14. Generated (upper) .vs. “Reconstructed” (lower) GeV inefficiency A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

15. Pre-Cluster (Projective Box) Energy Resolution ~0.2/E1/2 A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

16. Algorithm Performance • Running on 10GeV single π0’s • Define inefficiency (a missing γ2) as; • (i) neigh.grads do not find γ2 , i.e. • Gmax/Gmin > TOL not satisfied • .OR. • (ii) γ1 and γ2 are reported as ~merged • π0e+e–γ (1.2%) removed from sample • Running on 10GeV single e–’s • and single γ’s • Define rejection (a rightly missing γ2) as; • (i) neigh.grads do not find “γ2 ”,i.e. • Gmax/Gmin > TOL not satisfied • note: primary e-ID comes from tracking π0’s singles • Notes; • No parameter tuning studies as yet • Studied samples do not have added noise • A noise parameter, coded as a pedestal, • if(Gmin < NOISE) Gmin = NOISE; • has also not yet been studied A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002

17. Summary • Two complementary E-Flow strategies: preliminary results encouraging • -- Both need completion, and performance (parameter) tuning • -- Currently applied to 1-particle “events” in the EM calorimeter • -- Study the hadronic sector, in digital and analog readout modes • -- Apply to physics events, get performance numbers (Eff,Rej,Res) • -- Investigate the impact on physics reach • Simulation; a concerted effort to integrate various existing tools and detector • models, through appropriate interfaces, common formats and I/O persistence • Develop a simulation of the specific N.I.U. Digital Hadronic Calorimeter project short term mid term long term A. Maciel (NIU), Santa Cruz Linear Collider Retreat, June 27-29, 2002