Data Evaluation in High Energy Physics Experiments

In English are only some chapters, other is on Czech

Set of fully working examples is in disposition

Full text of chapter 11

Tasks of analysis in lecture focus

Tasks of beam tests in lecture focus

Tasks of DST data formats in lecture focus

Course Objective

After taking this course, students should be able to evaluate quality of acquired data and understand the typical data evaluation methodology as well as to carry out many steps single-handed.

Course Layout

Statistics in evaluation of data acquired in modern detectors, its implementation methods, e.g. detector properties assessment, particle tracks and their intersections (vertices) reconstruction, fitting, measurement error evaluation and evaluation tools - program framework ROOT.

Course Contens

  1. Introduction to basic statistics
  2. C++ and ROOT quick introduction
  3. DAQ methods and electronics for DAQ
  4. Sources and properties of acquised data
  5. Errors in measuremnets and neural networks
  6. Example of detector efficiency calculation
  7. From electronics signal to space point, track and vertex
  8. Analogue detectors and spectras
  9. Alignment od detectors
  10. Automation of analysis and fitting functions
  11. Fitting of track and errors of this
  12. Big experiments and their organization, world distributed computer network GRID and Athena framework
  13. List of examples and other sources for study (14 fully working examples on real data, 38 sources, 156 pages)