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1 Benchmarking the SiD Tim Barklow SLAC Sep 27, 2005.

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Presentation on theme: "1 Benchmarking the SiD Tim Barklow SLAC Sep 27, 2005."— Presentation transcript:

1 1 Benchmarking the SiD Tim Barklow SLAC Sep 27, 2005

2 2 There is an effort underway at SLAC to do physics benchmarking of the SiD. Activities include: – Evaluation and parameterization of the output of event reconstruction software applied to the fully simulated (Geant4) SiD detector – Selection of physics benchmark reactions – Physics analysis of reconstructed objects

3 3 Why Do Physics Benchmarking? Optimize individual detector designs – where is optimal physics/$ as function of component radius and length, B-field, etc.? Help evalulate performance of different detector concepts – we’re not at this point yet, but eventually we will have to do this. Further strengthen physics case for the ILC – despite 15+ years of research, not all processes have been studied – an in-depth look at a previously studied physics measurement can cut both ways: more realistic simulation of detector and background may worsen resolution, but inclusion of overlooked signal reactions and decay modes can lead to an improvement.

4 4 SiD Detector outline Whole Detector ~ 12m X 12m X 12m

5 5 SiD Detector outline A high performance detector for the LC Uncompromised performance BUT Constrained & Rational cost This is simulated SiD 00

6 6 Detector Design Issues to be Addressed by Physics Benchmarking (I) Physical dimensions & B-field Tracker (aka Momenter) performance – momentum resolution how much is enough? how much multiple scattering is acceptable? – tracking efficiency* as function of polar angle, track density, track origin – forward region behavior Calorimeter performance – granularity, E jet resolution*, MIP tracking * Combined VTX+TRK+CAL performance

7 7 Distance in cm Fraction 1.5 x the pad size Fraction of the photon(s) energy per event, closer to a charged track than some distance BR 2 does not by itself set performance. Pixel size (and Moliere radius) are also very important.

8 8 EMCAL Si/W pixel size: prototypes are 16 mm 2 readout chip: designed for 12 mm 2 How small can we go?? 2-4 mm 2 ? Need a physics argument for smaller pixels.  ->  +  o

9 9

10 10 Detector Design Issues to be Addressed by Physics Benchmarking (II) Vtx detector – inner radius, number of layers – mechanical design, sensor technology Alignment and Calibration – Is Z-pole running required? – Alternatives such as ? Background – true and false track finding efficiency – timing-based background veto

11 11 150 bunch crossings (5% of train) 98 events 920 GeV detected energy 125 detected charged tracks 1 bunch crossing Yellow = muons Red = electrons Green = charged hadrons Black = Neutral Hadrons Blue = photons with E > 100 MeV Illustration of bunch timing tag

12 12 WWS (World Wide Study of Physics and Detectors for the ILC) Formed Committee to Develop Physics Benchmark List:

13 13 Physics Benchmark Processes

14 14 Physics Benchmark Processes Reduced Benchmark List : SiD plans initially to study all of these reactions plus *addresses issue of ultimate EM calorimeter granularity

15 15 SiD Benchmarking Tools MC Data sets (stdhep files) of all SM processes at Ecm=500 GeV assuming nominal ILC machine parameters –About 50 fb -1 with e- pol=+/- 90% available at (-90% e- pol) (+90% e- pol) –1 ab -1 on SLAC mass storage with all initial e+,e- polarization states Many Monte Carlos (Pythia, Whizard) for producing additional stdhep files Fast MC which takes stdhep files as input and outputs the same kind of reconstructed particle LCIO objects that full event reconstruction software produces (LCIO bindings exist for C++, JAVA, FORTRAN ).

16 16 Fast MC Detector Simulation (I) In the context of SiD benchmarking the Fast Monte Carlo should be considered a Fast Physics Object Monte Carlo. It emulates the bottom line performance of the event reconstruction software in producing the electron, muon, charged hadron, photon and neutral hadron physics objects. Status of Fast MC used by SiD: –Tracker simulation uses parameterized covariance matrices based on tracker geometry and material –Electron and muon id given by min energy + overall efficiency –Photon and neutral hadron energies & angles smeared using single particle EM & hadronic energy & angle resolutions. Photons and neutral hadrons also have min energy and overall efficiency within detector volume.

17 17 Fast MC Detector Simulation (II) Fast MC with nominal single particle calorimeter response gives 17%/sqrt(E) jet energy resolution. This can be tuned to any value by varying the single particle EM & hadronic calorimeter energy resolutions and by replacing charged particle tracker momentum with calorimeter energy a certain fraction of the time. Will improve the parameterization of calorimeter response as we learn more from the particle flow algorithm studies.

18 18 Full Reconstruction/Analysis Overview Java based reconstruction and analysis package –Runs standalone or inside Java Analysis Studio (JAS) –Fast MC  Smeared tracks and calorimeter clusters –Full Event Reconstruction detector readout digitization (CCD pixels & Si  -strips) ab initio track finding and fitting for ~arbitrary geometries multiple calorimeter clustering algorithms Individual Particle reconstruction (cluster-track association) –Analysis Tools (including WIRED event display) –Physics Tools (Vertex Finding, Jet Finding, Flavor Tagging) –Beam Background Overlays at detector hit level

19 19 Full Reconstruction/Analysis Java Analysis Studio (JAS) provides a framework for event visualization (with WIRED) and reconstruction.

20 20 Software CD We have developed a CD containing simulation and reconstruction software as well as documentation and tutorials. In addition, a small amount of data is available on this CD. Full Detector simulation is available through slic (GUI available for Windows). Reconstruction/analysis via org.lcsim & JAS.

21 21 Examples of Tracker (Momenter) Performance Benchmarking

22 22 Recoil Mass (GeV)

23 23 Recoil technique provides best Higgs mass measurement if there is signficant branching ratio for decays with invisible particles

24 24 E beam (GeV) Beam Energy Profiles Before CollisionAfter CollisionLumi Weighted E beam (GeV) Center of Mass Energy Error Requirements Top mass: 200 ppm (  M t =35 Mev) Higgs mass: 200 ppm (  M H =60 MeV for 120 GeV Higgs) Giga-Z program: 50 ppm

25 25 angles only  E Z  vs b  E Z  vs a  E  vs a  E  vs b Measure Ecm with Detector using

26 26 Examples of Calorimeter Performance Benchmarking

27 27 M bb (GeV)

28 28

29 29 Summary Physics benchmarking is an important part of the ILC detector design process. SiD Benchmarking project would be an excellent entry point into ILC physics and detector studies Please contact any of the SLAC SiD people if you are interested. My email is

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