readme: update

- Mention slides.pdf

- Mention new programs and changes in ex-1

- Update for removal of lectures.pdf

README.md

@@ -5,10 +5,12 @@
 
 This repository is structured as follows:
 
-- `lectures`: a summary of the lectures of the course
+- `lectures`: notes and slides of the course lectures
 
 - `notes`: an explanation of the solutions of the exercises
 
+- `slides`: a slideshow about some further researches
+
 * `ex-n`: programs written for each exercise
 
 
@@ -28,17 +30,13 @@ only exception of the `#pragma once` clause) and require the following
 libraries to build:
 
 - [GMP] (≥ 6.2)
-
 - [GSL] (≥ 2.6)
-
 * [pkg-config] (≥ 0.29, build-time only)
 
 To generate plots, Python (version 3) with
 
 - [numpy] (≥ 1.18)
-
 - [matplotlib] (≥ 2.2)
-
 - [scipy] (≥ 1.4, optional)
 
 is required to generate plots.
@@ -79,8 +77,9 @@ different samples by changing the seed via the environment variable
 
 ### Exercise 1
 
-`ex-1/bin/main` generate random numbers following the Landau distribution and
-run a series of test to check if they really belong to such a distribution.  
+`ex-1/bin/main` generate random numbers following either the Landau or Moyal
+distributions (controlled by the argument `-m`) and run a series of statistical
+test to check if the points where samples from a Landau.  
 The size of the sample can be controlled with the argument `-n N`.  
 The program outputs the result of a Kolmogorov-Smirnov test and t-tests
 comparing the sample mode, FWHM and median, in this order.
@@ -93,6 +92,11 @@ fig. 4) of the kernel density estimation used to compute a non-parametric FWHM
 from a sample of random points. To run this program you must additionally
 install [scipy].
 
+(optional) `ex-1/plots/slides.py` makes two plots. The first (shown
+in fig. 3, exercises.pdf) is an illustration of the Landau distribution
+FWHM and the second (shown in slides.pdf) is a comparison of the Landau
+and Moyal distributions.
+
 
 ### Exercise 2