Introduction

Typical high-energy particle physics experiments today employ large-scale silicon tracking detectors. The mounting precision with which the modules are mounted inside the tracking device is typically worse than their intrinsic measurement resoution. In order not to loose information, the module position needs to be measured from data with higher precision than the intrinsic resolution. This is called "alignment". However, the recipe is not constrained to silicon detector alignment and can be applied to other tracking devices easily.

Different methods are available for detector alignment. The method presented here is based on the Kalman Filter and was first published in Reference [1]. This software is an experiment-independent implementation of this algorithm which can be used under the terms of the GPL and has been published in Reference [2]. Additionally it contains a complete simulation of tracks in a silicon tracking device and track reconstruction. Also tools for data-driven validation and validation with respect to the input to simulation are available.

Contents

This project contains a simulation package, the Kalman alignment algorithm and a validation package. With the simulation package, one can simulate tracks in a misaligned detector. The Kalman alignment algorithm can be used to correct for the misalignment, i.e. compute the alignment constants. The data-driven validation package can be used to see the track χ²-improvement after alignment.

Installation instructions

Start by checking out the code from the subversion repository:

svn co http://svn.hepforge.org/kalmanalignment/tags/release-1.0

Sample output

The topmost picture on the right shows a misaligned detector and many tracks traversing the detector. This is a screenshot from the simulation package.

The picture below shows the alignment result for the most sensitive rotation angle of the detector (gamma) after alignment. For each detector (72 detectors in total), the value of the alignment parameter and its error are indicated.

The picture at the bottom is a screenshot from the validation package, showing the normalized track χ²-distribution before and after alignment. In this case, a moderate misalignment was applied. After alignment, the track χ²-distribution is almost ideal (mean is close to unity).

A heavily misaligned detector with lots of tracks going through the modules (screenshot from the simulation package).

Determined alignment parameters for the most sensitive rotation angle for each detector.

Normalized χ²-distribution before and after alignment.