Material Budget Imaging

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Using the beam telescope and test beam infrastructure of DESY the material budget can be imaged: By integrating a material in the telescope, collecting data and reconstructing the scattering angle, the sample under test (SUT) can be 2D imaged in terms of position-dependent scattering angles. Furthermore, by using known material and one method radiation lengths - or the figure of merit thickness over radiation length (x/X0) - can be calibrated and used for unknown samples.

In November 2017 a first meeting happened with people working on these studies. The agenda and the contributions you find here: Participants of this first little workshop were: Jan-Hendrik Arling (DESY, ATLAS), Jan Dreyling-Eschweiler (DESY, ATLAS), Hendrik Jansen (DESY, CMS), Claus Kleinworth (DESY, CMS), Michaela Queitsch-Maitland (DESY, ATLAS), Benjamin Schwenker (University Goettingen, BelleII), Paul Schütze (DESY, CMS), Ulf Stolzenberg (University Goettingen, BelleII), Mengqing Wu (DESY, FLC).

First common goals of this "working collaboration" are:

  • Provide an easy usage to get material budget images
  • Compare and investigate different approaches and methods
  • Providing calibration data and framework for more precise tracking

If you are interested to contribute, please contact us.

Some examples:

Example from ATLAS ITK, M. Queitsch-Maitland
Example from 3D-Tomography and, P. Schütze

Caution: All below is under construction!

Step 1: Taking data

These is a brief summary out of experience.

  • Define your telescope geometry
    • coarsely adopt to thickness (range) of sample
    • geometry and beam energy stay fixed for all runs
    • alignment run: no sample
    • calibration run: known material and thickness
    • sample run
  • Measurement settings and time:
    • high energy and high rate, for example 4 GeV
    • collimator settings
    • ~5 tracks per plane
    • ~1-2 kHz trigger rate
    • for analysis >1000 tracks per image cell to achieve a proper resolution

Step 2: Track and scattering angle reconstruction


Kalman filter approach.


to be continued


GBL approach