Data Analysis in the Frequency Domain for Astroparticle Physics

Module PH8129

This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.

Basic Information

PH8129 is a semester module in English language at Master’s level and graduate-studies level which is offered once.

This Module is included in the following catalogues within the study programs in physics.

Subject-Related Qualification Modules for Doctoral Candidates in Physics (lecture series)

If not stated otherwise for export to a non-physics program the student workload is given in the following table.

Total workload	Contact hours	Credits (ECTS)
30 h	16 h	1 CP

Responsible coordinator of the module PH8129 is the Dean of Studies at Physics Department.

Content, Learning Outcome and Preconditions

Content

The module will give an introduction to the analysis techniques in the frequency domain which finds application for cryogenic detectors, gravitational waves and other experiments that require digital signal processing. The block course will be organized in 4 lectures and 4 dedicated exercises. Lectures: 1) Recap: Fourier series, Fourier transform, Laplace transform (2h). 2) Shannon-Nyquist theorem, aliasing, Discrete Fourier Transform (2h). 3) Noise theory. Shot, Johnson, Flicker and generation-recombination noises. Estimation of the noise power spectral density (2h). 4) Finite (FIR) and infinite (IIR) impulse response filters. Matched (optimal) filter (2h). Exercises 5) Practice 1: Application of the Discrete Fourier Transform (2h) 6) Practice 2: Noise and signal generators (2h) 7) Practice 3: Estimation of the noise power spectral density from data (2h). 8) Practice 4: Application of the matched filter to data (2h).

Learning Outcome

After successful completion of the module the students are able to:

understand and apply the fundamental concepts of Fourier and Laplace transformations
apply basic data-analysis techniques to detector data
perform a basic noise study of data
develop and apply dedicated simple filters to data

Preconditions

No preconditions in addition to the requirements for the Master’s program in Physics. Basic programming skills.

Courses, Learning and Teaching Methods and Literature

Courses and Schedule

SS 2021

Type	SWS	Title	Lecturer(s)	Dates	Links
VO	0.5	Data Analysis in the Frequency Domain for Astroparticle Physics	Vignati, M.	Wed, 14:00–16:00, virtuell	eLearning
UE	0.5	Exercise to Data Analysis in the Frequency Domain for Astroparticle Physics	Strauß, R. Responsible/Coordination: Vignati, M.	dates in groups

Learning and Teaching Methods

This module consists of a 4 lectures and 4 exercises. The lecture will provide a solid theoretical background in frequency domain analysis techniques. In the tutorials, the concepts of the lectures will be practiced with concrete examples. In small groups of students, short programs (Matlab, phyton, Root, ...) will be developed.

Media

Presentation with blackboard (lecture online), beamer presentations

Literature

no info

Module Exam

Description of exams and course work

There will be an oral exam of 30 minutes duration. Therein the achievement of the competencies given in section learning outcome is tested exemplarily at least to the given cognition level using comprehension questions.

Participation in the exercise classes is strongly recommended since the exercises prepare for the problems of the exam and rehearse the specific competencies.

Exam Repetition

The exam may be repeated at the end of the semester.