Introduction to Signal Processing in Experimental Physics

Course content

Progress in natural science and technology is based on carefully conducted experiments: ranging from particle accelerators, gravitational waves observatories, genome sequencing, to autonomous vehicles. 

To enable you to contribute to this progress this course introduces the basics of signal acquisition and processing using modern analog and digital electronic circuitry. 

 

The course is organised in lecture tutorials, laboratory exercises and an experimental project.

Learning outcome

Skills:

  • Understand and set-up simple passive electronic circuits 

  • Design simple active circuits for signal conditioning

  • Describe (linear) systems with transfer functions

  • Discuss the limitations and noise of sensors and circuits

  • Select and use suitable ADCs for data acquisition tasks

  • Construct truth tables for Boolean functions

  • Implement simple logic operations in FPGA hardware

  • Understand and discuss different data representation 

Competences:

This course gives the student a solid background in signal processing, practical experience with modern data acquisition and experiment control methods. It provides students with a good basis for laboratory work in MSc or PhD projects and experimental work in all natural sciences dealing with data acquisition.

Knowledge:

  • Passive and active electronic components

  • Transfer functions of linear systems, filters

  • Operational amplifier circuits

  • Signal conditioning and feedback

  • Noise in electronic circuits

  • Sampling and analog to digital conversion

  • Data types and representations/encoding

  • Boolean algebra

  • Introduction to Field Programmable Gate Arrays (FPGAs)

Lecture tutorial, laboratory exercises, experimental project.
Short hands-on exercises will be part of the lecture tutorials for a deeper understanding of the presented concepts.
In the first weeks of the course, lab exercises will be offered to the students. They will work in groups and get acquainted with the lab instrumentation. The goal is to apply the topics learned during the lecture tutorials.
In the last weeks of the course the group of students will work on an experimental project

See Absalon for a list of course literature

Lecture notes, book chapters, research articles.

Basic knowledge of physics (in particular electromagnetism) and mathematics equivalent to the first two years of BSc education is required. Strong interest in experimental work is recommended.

ECTS
7,5 ECTS
Type of assessment
Oral examination, 30 minutes
Written assignment, during course
Type of assessment details
30 minutes, no preparation time
Oral exam: 80% of the final grade
Written project report (max 5 pages): 20% of the final grade.
The parts of the exam do not need to be passed separately, only the total exam.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Re-exam

The same as for the ordinary exam.

The student can choose to re-use the written report from the ordinary exam or hand in a new report no later than 3 weeks before the oral re-exam.

Criteria for exam assessment

See Intended learning outcome.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 22
  • Preparation
  • 135,5
  • Practical exercises
  • 12
  • Laboratory
  • 36
  • Exam
  • 0,5
  • English
  • 206,0

Kursusinformation

Language
English
Course number
NFYK23003U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Duration

1 block

Placement
Block 3
Schedulegroup
B
Capacity
24
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Studyboard
Study Board of Physics, Chemistry and Nanoscience
Contracting department
  • The Niels Bohr Institute
Contracting faculty
  • Faculty of Science
Course Coordinators
  • Jörg Helge Müller   (6-70786f6f68754371656c316e7831676e)
  • Alessandra Camplani   (10-68356a687477736875704775697035727c356b72)
  • Jean-Baptiste Sylvain Béguin   (7-6e66696b796d724472666d326f7932686f)
Teacher

Alessandra Camplani
Jean-Baptiste Sylvain Béguin

Saved on the 16-02-2024

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