This course covers the complete syllabus for Python programming for 5th semester students enrolled in BSc(Honours) Physics at Calcutta University. We will cover
1. Study of Random Numbers and Time series:
Introduction to the numpy.random() module
- Histogram (by matplotlib.pyplot.hist) and autocorrelation function of a given time series.
- Generating exponential variates from uniform variate using transformation
- Gaussian variate from uniform variate using central limit theorem.
- Study of histogram and moments of random sequences of different probability density using numpy.random.
2. Applications of Random Numbers
- Coin tossing. Fit with binomial distribution.
- Nuclear Decay: Simulation assuming a constant decay probability per unit time. • Random Walk:
- In 1D and in 2D (Square grid)
- Plot of r.m.s. value of end to end distance as a function of time step
- fitting and finding of exponent
- Monte Carlo Integration
3. Scaling and plots, exponents and parameters:
Laws and distributions from Statistical Mechanics
Some Problems:
- Maxwell-Boltzmann distribution • Bose-Einstein distribution
- Fermi-Dirac distribution
- Plot of specific Heat of Solids
- Dulong-Petit law
- Einstein distribution function
-
25 % In Progress
-
8.33 % In Progress
-
0 % In Progress
-
16.67 % In Progress
-
0 % In Progress
-
33.33 % In Progress
-
0 % In Progress