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The selected event files are reweighted with the scripts [[attachment:CreateDataForSignalAndBackground.C|CreateDataForSignalAndBackground.C]] and [[attachment:CreateDataForSignalAndBackgroundEqualSign.C|CreateDataForSignalAndBackgroundEqualSign.C]]. Both scripts have
to be compiled for RooT by calling e.g. {{{.L CreateDataForSignalAndBackground.C++}}} on the root command line.
They use the {{{Fortran}}} library {{{libnunugamma_DiffXSec.so}}} coded by O.Kittel. The library has to be compiled in advance from
the file [[attachment:nunugamma_DiffXSec.f|nunugamma_DiffXSec.f]]

Christoph Bartels

Email: <christoph.bartels@desy.de>

This page is not finished yet, and heavy editing has to be done!!

Documentation of my PhD analyses

A full documentation of the results can be read in my thesis The full source code of both analyses can be found on DESY dCache at:


Model independent WIMP search

Analysis Walkthrough

The WIMP search is designed as model independent as possible. This entails two important decisions:

  • Use a model independent ( ;) ) signal description. The "model" used can be found in the paper of Birkedal "et al."

  • The signal contribution to the data is not explicitly generated and simulated, but obtained by a reweighting of events after the selection. This is possible because the dominant background process is indecernible from the signal on an event-by-event basis.

Data Samples

The data samples used were produced by the ILD community for the detector optimisation effort in 2008. The fully reconstructed data files can be found in the International Linear Collider Simulations Database.

Post-reconstruction data processing

Two corrections have been performed on the simulated data samples. Both corrections are linked to the photons being uncharged. While for charged particles tracking information is used in the clustering stage to match particle momentum and energy depositions, without this information, the clustering is purely topological. This results in split em Clusters from single incident photons, each subcluster being identified as an individual photon candidate, and energy lost in the insensitive material of the cracks in the calorimeters.

Photon splitting

The photon splitting is recovered by an iterative merging of photon candidates with a cone based method. The cone opening angle has been optimised with respect to purity and efficiency. The optimisation algorithm can be found in FindMergeAngle.C.

The so found opening angle is then used to merge photon candidates by use of the function MergeRecoPhotons() in the root script PreprocessData.C

Energy calibration

After the merging procedure, the photon energies are recalibrated as function of their polar angle. The calibration function is determined with the script CalibrationFunctions.C and subsequently applied to the photon merged data samples with CalibrateData.C

Event Selection

The routine Selection.C performs the event selection. The following criteria are applied:

For the signal definition at least one photon with

  • 10 GeV < E < 220 GeV and

  • -0.98 < cos( Theta ) < 0.98


  • Maximal visible energy excluding the most energetic photon E_vis < 20.0 GeV

  • Maximal track p_T < 3.0 GeV

  • Rejection of high energy electrons tagged in the forward calorimetry.

Signal Generation

The selected event files are reweighted with the scripts CreateDataForSignalAndBackground.C and CreateDataForSignalAndBackgroundEqualSign.C. Both scripts have to be compiled for RooT by calling e.g. .L CreateDataForSignalAndBackground.C++ on the root command line. They use the Fortran library libnunugamma_DiffXSec.so coded by O.Kittel. The library has to be compiled in advance from the file nunugamma_DiffXSec.f

Theoretical Signal and Background predictions


Helicity structure and signal cross section

Mass determination and partial wave

Cherenkov Detector Prototype

Simulation and simulated data


WIMPs searches on ILC (last edited 2015-02-20 18:27:35 by AnnikaVauth)