
Course unit
EXPERIMENTS IN PHYSICS 1 (PART A)
SCP4067974, A.A. 2019/20
Information concerning the students who enrolled in A.Y. 2019/20
Integrated course for this unit
ECTS: details
Type 
ScientificDisciplinary 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 
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, multitasking process, administration of the memory and of the I/O. The most important operating systems, Network fundamentals, protocols. The internet and TCP/IP, WorldWide 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 floatingpoints 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 binarysearch 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; Bubblesort, 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 nonlinear function. Nonlinear equations, determination of the zero, iterative methods, uncertainties and convergence, theorem of Bolzano and bisection method, method of NewtonRhapson, method of the secant, highorder interpolation, inverse interpolation, method of Brent.
8) Integer numbers and montecarlo 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, pseudorandom numbers; MonteCarlo 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, bynarysearch 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 nonlinear equations. Introduction, function as parameters, bisection method, NewtonRhapson method, applications.
8) MonteCarlo method. The function where, the hitormiss 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 elearning 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.

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, ...)

