- Docente: Silvia Arcelli
- Credits: 6
- SSD: FIS/01
- Language: English
- Moduli: Silvia Arcelli (Modulo 1) Pietro Antonioli (Modulo 2) Davide Falchieri (Modulo 3)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2) Traditional lectures (Modulo 3)
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Physics (cod. 9245)
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from Nov 18, 2024 to Dec 17, 2024
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from Sep 16, 2024 to Nov 12, 2024
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from Oct 15, 2024 to Oct 22, 2024
Learning outcomes
At the end of the course the student will have a basic knowledge of modern electronic data collection systems and advanced knowledge in the field of modern computer systems for experimental data processing and Monte Carlo simulation. In particular, the student will be able to: sketch the selection criteria related to the "online" data flow and to the "offline" processing, including event reconstruction, detector calibration and data analysis.
Course contents
Unit I :
General introduction to data acquisition concept, elements of theory of sensors and Analog to Digital Converters (ADC/TDC). Trigger concept, dead-time and trigger concept evolution in large scale experiments. Data bus concept and case study of VME and IPBUS. The module includes two lab exercise practicing coding taking data on VME and IPBUS based cards.
Unit II:
Introduction to the reconstruction and analysis of physics events. Global and local methods of pattern recognition- Track Finding e Track Fitting- determination of the track parameters – Kalman Filter. Algorythms for Particle Identification (Bayesian PID).
General concepts on the calibration and alignment of the detectors, with examples of the techniques used in the LHC experiments.
Unit III:
Serial bus protocols.
Concept and implementation examples of serial protocols: RS232, USB, I2C and SPI. Serial buses on high speed optical links. 8B/10B encoding/decoding.
Serializers and de-serailizers. Bit error rate. Practical applications of Xilinx FPGAs.
Readings/Bibliography
slides and reviews on the topics presented during lectures
Teaching methods
Lectures and laboratory sessions
Assessment methods
Oral examination on the topics presented during the course.
Teaching tools
Slides and extra material that will be available on Virtuale. Laboratory sessions on Data Aquisition and Techniques of track reconstraction (coding of a kalman filter using ROOT)
Office hours
See the website of Silvia Arcelli
See the website of Pietro Antonioli
See the website of Davide Falchieri
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.