Millepede-II  V04-03-10
Overview

Introduction

In certain least squares fit problems with a very large number of parameters the set of parameters can be divided into two classes, global and local parameters. Local parameters are those parameters which are present only in subsets of the data. Detector alignment and calibration based on track fits is one of the problems, where the interest is only in optimal values of the global parameters, the alignment parameters. The method, called Millepede, to solve the linear least squares problem with a simultaneous fit of all global and local parameters, irrespectively of the number of local parameters, is described in the draft manual.

The Millepede method and the initial implementation has been developed by V. Blobel from he University of Hamburg. Meanwhile the code is maintained at DESY by the statistics tools group of the analysis center of the Helmholtz Terascale alliance (www.terascale.de).

The Millepede II software is provided by DESY under the terms of the LGPLv2 license.

Installation

To install Millepede (on a linux system):

  1. Download the software package from the DESY svn server to target directory, e.g.:
     svn checkout http://svnsrv.desy.de/public/MillepedeII/tags/V04-03-10 target
    
  2. Create Pede executable (in target directory):
     make pede
    
  3. Optionally check the installation by running the simple test case:

     ./pede -t
    

    This will create (and use) the necessary text and binary files.

News

Tools

The subdirectory tools contains some useful scripts:

Details

Detailed information is available at:

Millepede II - Draft Manual

Major changes

List of options and commands

List of exit codes

Contact

For information exchange the Millepede mailing list anace.nosp@m.ntre.nosp@m.-mill.nosp@m.eped.nosp@m.e2@de.nosp@m.sy.d.nosp@m.e should be used.

References

  1. A New Method for the High-Precision Alignment of Track Detectors, Volker Blobel and Claus Kleinwort, Proceedings of the Conference on Adcanced Statistical Techniques in Particle Physics, Durham, 18 - 22 March 2002, Report DESY 02-077 (June 2002) and hep-ex/0208021
  2. Alignment Algorithms, V. Blobel, Proceedings of the LHC Detector Alignment Workshop, September 4 - 6 2006, CERN
  3. Software alignment for Tracking Detectors, V. Blobel, NIM A, 566 (2006), pp. 5-13, doi:10.1016/j.nima.2006.05.157
  4. A new fast track-fit algorithm based on broken lines, V. Blobel, NIM A, 566 (2006), pp. 14-17, doi:10.1016/j.nima.2006.05.156
  5. Millepede 2009, V. Blobel, Contribution to the 3rd LHC Detector Alignment Workshop, June 15 - 16 2009, CERN
  6. General Broken Lines as advanced track fitting method, C. Kleinwort, NIM A, 673 (2012), pp. 107-110, doi:10.1016/j.nima.2012.01.024
  7. Volker Blobel und Erich Lohrmann, Statistische und numerische Methoden der Datenanalyse, Teubner Studienbücher, B.G. Teubner, Stuttgart, 1998. Online-Ausgabe.
  8. Systems Optimization Laboratory, Stanford University;
    C. C. Paige and M. A. Saunders (1975), Solution of sparse indefinite systems of linear equations, SIAM J. Numer. Anal. 12(4), pp. 617-629.
  9. Systems Optimization Laboratory, Stanford University;
    Sou-Cheng Choi, Christopher Paige, and Michael Saunders, MINRES-QLP: A Krylov subspace method for indefinite or singular symmetric systems, SIAM Journal of Scientific Computing 33:4, 1810-1836, 2011, doi:10.1137/100787921