sensitive detector segmentation n.
Skip this Video
Loading SlideShow in 5 Seconds..
Sensitive Detector Segmentation PowerPoint Presentation
Download Presentation
Sensitive Detector Segmentation

Loading in 2 Seconds...

play fullscreen
1 / 11

Sensitive Detector Segmentation - PowerPoint PPT Presentation

  • Uploaded on

Sensitive Detector Segmentation. Norman Graf (SLAC) LC-ECFA Meeting, DESY May 28 , 2013. Problem Statement. LC Detectors being considered for the ILC and CLIC are highly segmented, resulting in hundreds of millions to billions of readout channels.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

Sensitive Detector Segmentation

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
sensitive detector segmentation

Sensitive Detector Segmentation

Norman Graf (SLAC)


May 28, 2013

problem statement
Problem Statement
  • LC Detectors being considered for the ILC and CLIC are highly segmented, resulting in hundreds of millions to billions of readout channels.
  • Implementing each readout channel as a separate volume in Geant4 is impractical.
  • Define Sensitive Detectors as larger volumes and use “virtual segmentation” to define readouts, e.g.
    • Tracking sensitive detector is silicon wafer, virtual segmentation returns pixels or strips.
    • TPC sensitive detector is full endplate, virtual segmentation returns pads
    • Calorimeter sensitive detector is scintillator sheet, or gas volume, virtual segmentation returns cells.
  • Given local position, return cell ID
  • Given cell ID, return local position
  • Given cell ID, return list of neighboring cell IDs
  • Return cell size (allows energy density clustering)
  • Need to have a separate package containing segmentation classes on which both the simulation and reconstruction packages depend.
  • Do not want to couple the reconstruction to Geant4.
  • Also don't want to have two separate implementations of segmentors.










cartesian grid
Cartesian Grid
  • For each grid
    • x
    • deltaX
    • y
    • deltaY
  • Allows for effective gaps in between pads
r phi readout e g beamcal
R-Phi Readout, e.g. BeamCal
  • For each annulus:
    • rmin
    • rmax
    • nCells
    • phi0
    • deltaPhi
  • Allows for effective gaps in both radius and phi
  • Allows for staggered cells
  • Define hexagon “radius”
  • Can define effective gaps between cells using two “radii”
attaching segmentation class to volume
Attaching Segmentation Class to Volume
  • Need the ability to specify location of origin and orientation of segmentation coordinates with respect to sensitive geometric volume.
  • In calorimeters, how to handle Geant4 steps which straddle cell borders or cross “gaps”
  • How to handle edges of segmentation classes
    • irregular cell sizes and shapes
    • missing neighbors
  • Semi-Digitization
    • How to handle position-sensitive digitization such as charge-sharing across boundaries (e.g. RPC) or efficiency of light collection in scintillator readout.
software architecture
Software Architecture
  • Segmentation classes should be closely related to Geant4 primitive volumes for efficiency in defining, implementing and utilizing them.
  • Do not want reconstruction to depend on Geant4
  • Standalone package upon which both simulation and reconstruction classes depend.
  • Runtime binding via plugin mechanism might lead to problems of provenance.
  • Prefer compile-time binding of classes, run-time definitions for parameters.