Weekly plans and update for week 7

Dear All, we hope you are all doing well. This is the weekly FYS4411/9411 update with plans for this week and links to various topics. 
Concerning the covid-19 situation, as of now (today, Wednesday Feb 17), we do not know if we can have in-person lectures and labs. Hopefully, with an improved situation this may change to the better.

Else, last week we attempted on giving you a link to the derivations of the Fokker-Planck equation and the Langevin equation used in importance sampling. For us, the most important aspect is however how this is implemented in our codes. 
We ended last week with a start on optimization methods. This is were we start this week and we will continue with this topic next week as well before we move on to resampling methods and finally parallelization. 
These will be the last ingredients we need in order to have a professional variational MC code.

The lecture material this week is at for example http://compphysics.github.io/ComputationalPhysics2/doc/pub/week6/html/week6.html.
We will discuss Gradient Descent methods, Steepest descent and Stochastic gradient descent
and possibly the Conjugate Gradient Descent method.

We will start with a top-down view, with a simple harmonic oscillator problem in one dimension as case.
Thereafter we continue with implementing the simplest possible steepest descent approach to our two-electron problem with an electrostatic (Coulomb) interaction. Our code includes also importance sampling. The simple Python code here illustrates the basic elements which need to be included in our own code.
Then we move on to the mathematical description of various gradient methods.

The lab is as usual right after the lecture, from 1615-19.

Best wishes to you all and stay healthy,
Morten and ?yvind