1
00:00:02,690 --> 00:00:09,590
Welcome to the first homework session of Statistical Mechanics: Algorithms and Computations.

2
00:00:09,590 --> 00:00:16,590
During the lecture, we have seen two powerful methods to compute π using Monte Carlo algorithms

3
00:00:17,120 --> 00:00:20,480
the homework consists of three parts,

4
00:00:20,840 --> 00:00:23,600
and you can find them on the Coursera website.

5
00:00:23,940 --> 00:00:30,970
In part 1, you will evaluate errors associated to direct sampling like in the children's game

6
00:00:30,970 --> 00:00:32,990
at the Monte Carlo beach.

7
00:00:35,640 --> 00:00:42,090
In part 2, you will see that the performance of the Markov chain algorithm

8
00:00:42,090 --> 00:00:44,800
played by adults in the heliport

9
00:00:44,800 --> 00:00:47,880
depends on how far you can throw the pebble.

10
00:00:48,090 --> 00:00:52,610
You will find that the best performance is approximately reached

11
00:00:52,610 --> 00:00:56,540
using the very famous 1/2 thumb rule.

12
00:00:58,200 --> 00:01:02,380
In part 3, you will study an advanced automatic method

13
00:01:02,380 --> 00:01:05,210
to evaluate errors in a smart way

14
00:01:05,430 --> 00:01:09,730
in Markov Chain algorithm, it's named the bunching method.