First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
ASTRONOMY
Course unit
EXPERIMENTS IN PHYSICS 1 (PART A)
SCP4067974, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course First cycle degree in
ASTRONOMY
SC1160, Degree course structure A.Y. 2008/09, A.Y. 2019/20
N0
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination EXPERIMENTS IN PHYSICS 1 (PART A)
Website of the academic structure http://astronomia.scienze.unipd.it/2019/laurea
Department of reference Department of Physics and Astronomy
Mandatory attendance
Language of instruction Italian
Branch PADOVA

Lecturers
Teacher in charge ANTONINO MILONE FIS/05
Other lecturers IVANO BERTINI FIS/05

Integrated course for this unit
Course unit code Course unit name Teacher in charge
SCP4067973 EXPERIMENTS IN PHYSICS 1 GIULIA RODIGHIERO

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses FIS/01 Experimental Physics 6.0

Course unit organization
Period Annual
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Group didactic activities 0.0 8 0.0 No turn
Laboratory 3.0 32 43.0 No turn
Lecture 3.0 24 51.0 No turn

Calendar
Start of activities 30/09/2019
End of activities 20/06/2020
Show course schedule 2019/20 Reg.2008 course timetable

Syllabus

Common characteristics of the Integrated Course unit

Prerequisites: Fundamentals of mathematics and physics.
Target skills and knowledge: The student will know the fundamentals of numerical programming and statistics and acquire the skills to critically analize physical measurements, being provided with computing softwares to also formally associate an uncertainty to each measurement.
Examination methods: Oral exam about the topics discussed during lectures and the laboratory reports.
Assessment criteria: Evaluation of the laboratory reports. Knowledge of the topics of the program and capability of making connections among them. Ability to use theoretical framework discussed during the lectures to understand and perform the laboratory experiments. Ability in writing and discussing the topics of the program in a proper and scienfitic way.

Specific characteristics of the Module

Course unit contents: Theoretical lectures:
1) Computer's architecture. Historical introduction, main components, cycle fetch/decode/execute. CPU basic, machine's main memories, hard disk, hierarchy of the memories, methods to maximize the CPU performances.
2) Operating systems and networking. The history of Operating Systems.
The concept of a process, multi-tasking process, administration of the memory and of the I/O. The most important operating systems, Network fundamentals, protocols. The internet and TCP/IP, World-Wide Web.
3) Representation of the information. Representing binary numbers, integer numbers with and without sign. Two's complement, hexadecimals system, representing real numbers in the IEEE754 format. Common issues associated to the floating-points representation. Representation of text and images.
4) Algorithms and programming languages. The definition of an algorithm, algorithm representation, programming languages, selection structures, iterative structures, Boolean expressions and variables, units and modules
5) Data, recursive structures and the binary-search algorithm. data classification; a way of introducing recursion, recursion and algorithms; recursive structures, recursive control, removing the recursion, binary search algorithm.
6) Sorting algorithms and analysis of the algorithms. Introduction to the sorting; Bubble-sort, selection sort, insertion sort, quick sort algorithms. Analysis of the algorithm, efficiency, worst/best/middle case, asymptotic pattern, identification of the maximum/minimum. Application to the selection and quick sort algorithm.
7) Determination of the zero of non-linear function. Non-linear equations, determination of the zero, iterative methods, uncertainties and convergence, theorem of Bolzano and bisection method, method of Newton-Rhapson, method of the secant, high-order interpolation, inverse interpolation, method of Brent.
8) Integer numbers and monte-carlo methods. basics of random events, probability, discrete random variables, expectation value, variance, continuous random variables, uniform distribution, Gaussian distribution, Poisson distribution, distribution function, generation of random numbers, pseudo-random numbers; Monte-Carlo method, integration hit or miss, sample mean integration; simulations.

Computer laboratory:
1) Introduction to Linux. Basic Linux commands.
2) Introduction to Python. IDLE shell, variables, characters, lists.
3) Programming in Python. Instructions if, while and for; function, range, how to write a program, definition of function, module, namespaces, matplotlib, plot of a function, return arguments, tuple, optional parameters.
4) Sorting algorithms. Insertion sort, bynary-search algorithm, Quick sort algorithm.
5) Numerical computation. Numpy, 1D array, genaration of random numbers, histogram plots.
6) Analysis of observational data. Mean, standard deviation, how to read the data from a text file, plot of the data, symbols and colors, how to set the limits on the abscissa and ordinate axes, weighted mean
7) Determination of the zero in non-linear equations. Introduction, function as parameters, bisection method, Newton-Rhapson method, applications.
8) Monte-Carlo method. The function where, the hit-or-miss method for the determination of the area of an irregular figure; simulation
Planned learning activities and teaching methods: Lectures of theory and exercises in the computer laboratory. Lectures are given in Italian.
Additional notes about suggested reading: Lecture notes available through the website of the course on the e-learning platform of the Department of Physics and Astronomy "G. Galilei" (https://elearning.unipd.it/dfa/).
Suggested textbook.
Textbooks (and optional supplementary readings)
  • Brookshear, J. Glenn; Brylow, Dennis; Smith, David T., Informatica una panoramica generale. Milano: Pearson, 2012. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)