The learning objectives of the course are the following:

• Provide theoretical and practical knowledge of experimental techniques concerning the interaction ofradiation with matter, particle detectors, signal processing, electronics as well as statistical methods forsimulation and data analysis.
• Make the students able to perform measurements using appropriate instrumentation.
• Provide basic knowledge on laboratory instrumentation.
• Make the students able to design simple experimental setups.
• Make the students able to perform simple estimations and produce graphs to analyse experimental data.
• Provide basic knowledge on simulation techniques and Monte Carlo method.
• Introduce students to the ROOT data analysis framework.
• Improve students' skills (writing and speaking), to describe the topic, the methods, the results,the analysis procedure and the interpretation of the experiments output.

With reference to "Dublin descriptors", this Course contributes to provide the following skills:

 Knowledge and understanding:

• Ability in induction and deduction methods.
• Ability to schematize a real problem, defining the physical quantities (scalars and vectors) thatare essential for obtaining results.
• Capability to setup and define a problem by using quantitative relations (algebraic, differential integral)between physical variables and to solve it by means of analytical or numerical algorithms.
• Capability to design simple experimental setups or to use scientific instrumentation to perform thermo-mechanics and electromagnetic measurements.
• Capability to carry out statistical analyses of results.
• Capability to perform analysis sessions of experimental data from modern physics experiments.
• Capability to perform numerical simulations.

Capability to apply the knowledge in order to:

• Describe physical phenomena by a correct and quantitative application of scientific methodologies.
• Capability to develop theoretical models.
• Evaluate the performance of experiments in nuclear physics and carry out the analysis of experimentaldata.
• Perform numerical calculations and simulation procedures.

Autonomy of judgment:

• Reasoning skills.
• Capability to find the most appropriate methods for a critical evaluation and interpretation of experimentaldata.
• Capability to understand the prediction of a model or theory.
• Capability to evaluate the accuracy and importance of existing measurements
• Capability to evaluate the goodness and limits in the comparison between experimental dataand theoretical predictions.

Communication skills:

• Abilities in computer programming.
• Capability to appropriately communicate scientific topics and problems, discussing the motivations andmain results.
• Capability to describe in a written report a scientific topic or problem, discussing the motivations and mainresults.

The course includes lessons and exercises during hall lectures, laboratory demonstrations andexperiments in the lab by the students.During hall lectures the teacher presents the theoretical course contents needed for understandingexperiments in the lab, together with a description of the experiments procedure and of theinstrumentation used. Particular attention is given to the data analysis techniques and to therepresentation of the experimental results obtained during lab activities.

During the course the students carry out exercises on the use of laboratory instrumentation and areintroduced to the use of the data analysis framework ROOT.

In the lab students carry out the experiments described during hall lectures.

6 CFU (each corresponding to 7 hours) are dedicated to hall lectures, for a total of 42 hours, theremaining 3 CFU (each corresponding to 15 hours) are dedicated to lab activities and exercises, for atotal of 45 hours. The course (9 CFU) therefore includes a total of 87 hours of didactic activities.

Should the circumstances require online or blended teaching, appropriate modifications to what ishereby stated may be introduced, in order to achieve the main objectives of the course.

It is necessary to have basic knowledge about general Physics, modern Physics, mathematicalanalysis, the error theory in an experimental measurement and data analysis techniques. For thisreason, as required by the Didactic Regulations, it is mandoratory to have passed the followingexams: Mathematical Analysis I, General Physics I and II, Laboratory of Physics I and II;

It is also useful to have basic knowledge of condensated matter Physics and nuclear Physics.

Attendance at the courses is usually compulsory (see the Didactic regulations of the Master of Science inPhysics).Should the circumstances require online or blended teaching, appropriate modifications to what is herebystated may be introduced, in order to achieve the main objectives of the course.

Part I

1. Techniques and laboratory instrumentation

Sensors for the measurement of physical quantities - Analog and digital sensors - Data acquisition fromsensors - Digital multimetere- Analog and digital oscilloscopes - Vacuum techniques - Elements for vacummproduction and measurement - Measurement of radiations from Infrared to ultraviolet - Optical fibers -Spectrophotometers - Radioactive sources

2. Radiation Detectors

Interaction of charged particle with matter - Bethe-Block relation - Range - Straggling - Energy loss of electronsand positrons - Photon interaction - Photoelectric effect - Compton Effect - Pair production - Electromagneticshowers - Particle detectors - Measure of energy, momentum, position, mass and charge of particles - Generalproperties of a detector: sensitivity, resolution, efficiency, dead time - Gas detectors - Ionization chambers -Geiger counters - Solid state detectors - Strip, drift and pixel detectors - Radiation damage - Scintillationdetectors - Light yield - Photomultipliers - Light guides and WLS fibers - APD and SiPM.

3. Elements of Electronics

Pulse signals from detectors - Analog and digital signals - Propagation of signals - Coaxial cables - SIgnalGenerators- Power supply - Electronics for Nuclear Physics - The NIM standard - Linear electronics:preamplifier, amplifier, shapers - Basic knowledge of logic electronics: OR, AND, NOT circuits - Analog-to-digital converters (ADC and QDC) - Discriminators - Coincidence circuits - Counters - Trigger systems - Dataacquisition - Digital pulse processing

4. Data analysis and simulation techniques

Knowledge of elementary statistics - Central values and dispersion indexes - Experimental distributions -Gauss and Poisson distributions - Experimental errors - SIgnificance test - Data analysis techniques in nuclearphysics experiments - Spectra analysis - Background subtraction - Non linear fits . Multiparametric analysis -The ROOT software - SImulation of physical processed - Monte Carlo methods the GEANT package fordetector simulation 

Part II: Laboratory experiments

Exercises on the use of Arduino Board

Exercises on the use of laboratory instrumentation (electronics,..)

Exercises on the use of the ROOT software

Laboratory experiments (listed below, randomly assigned to students for the prepartion of a writtenreport to be discussed during the oral exam)

1) Measurements carried out by means of Arduino board

2) Photoelectric effect and the measurement of the Planck constant

3) Study of discrete and continuous light spectra with a digital spectrophotometer

4) Detection of electrons with a Geiger counter and study of the absorption coefficient

5) Study of the light absorption at different frequencies

6) Gamma spectrometry and absorption coefficient with scintillators

7) Alpha spectrometry and study of energy loss with silicon detectors

8) Measurement of the energy spectrum of a beta source

9) Michelson interferometer

10) SiPM characterization

For the items concerning the interaction of particle and radiation with matter, particle detectors and electronicssee one of the following textbooks:

1. William R. Leo, Techniques for Nuclear and Particle Physics Experiments, Springer-Verlag

2. Glenn F. Knoll, Radiation Detection and Measurement, John Wiley and Sons

3. Claude Leroy and Pier-Giorgio Rancoita, Principles of Radiation Interaction in Matter and Detection, WorldScientific

4. C.Grupen, B.Schwartz, Particle Detectors, Cambridge

For items concerning statistics and data analysis techniques:

5. J.R.Taylor, Introduzione all’analisi degli errori, Zanichelli

For Arduino:

6. B.W. Evans, Arduino Programming Notebook, Creative Commons

During the course the students will be invited to carry out some exercises and to summarize the obtained results in short reports that have to be sent to the teacher by email before the end of the lessons. In order to beabmitted to the exam, it is necessary to have sent the aforementioned short reports and to have attended thelaboratory shifts and the lessons. Exceptions can be agreed in case of workers. To guarantee equalopportunities and in compliance with the laws in force, interested students can ask for a personal interview inorder to plan any compensatory and / or dispensatory measures, based on the didactic objectives and specificneeds. It is also possible to contact the referent teacher CInAP (Center for Active and Participated Integration -Services for Disabilities and / or SLD) of our Department, Prof. Catia Petta.At the end of the course, the experiments carried out during laboratory shifts will be randomly assigned to eachstudent, which has to analyze the data and write a report (15-20 pages) that must be sent 1 week before theoral exam. The students will be questioned about all the reports they produced and about the other contents ofthe course.

The final evaluation will take into account the following aspects:

knowledge of the contents

clarity and language skills

relevance of the answers to the asked questions

ability to make correct links with other topics in the program

ability to report examples

ability to solve simple exercises and make estimates

The verification of learning will be done remotely if the circumstances would require online or blended teaching.

As required by the Didactic Regulations, it is mandoratory to have passed the following exams: MathematicalAnalysis I, General Physics I and II, Laboratory of Physics I and II.

The following list of questions is not exhaustive but includes just some examples.

Charged particles interaction with matter and energy loss - Gamma interaction with matter - Working principleof a gas detector - Scintillation detectors - Properties of a scintillator - Energy resolution of a detector - Timeresolution of a detector - Estimation of the geometrical acceptance of a detector - Calibration of a detector -Analog to digital converter - Discriminators - Coincidence circuit and spurious coincidences rate - Examples ofMonte Carlo simulations.