Codes

• Image recovery

• Reconstructing unital quantum processes from average gate fidelities

• Ranking of sport leagues

• Python script to merge bibtex files

Image recovery: A compressed sensing demonstration

Images are approximately sparse after a discrete cosine transform (DCT) or wavelet transform (WT). This can be used in order to reconstruct images from few pixels (20% and much fewer with some tricks).

As a demonstration I have written this program which is directly applicable to photos (black white).

Quantum process tomography

Reconstructing unital quantum processes from average gate fidelities

Simulating open system dynamics

... later

Ranking of sport leagues

Here I provide a Python code (jupyter notebook) to rank the teams of the German Bundesliga.

I was persuaded to join a betting game on the German Bundesliga. The problem is, that my knowledge about soccer is very limited and that I am also not willing to look into all its details.

If one want to estimate the winner of a soccer league game, then one can obtain a first guess from the current point tables. However, if team A has played against stronger teams than team B, then their points might suggest a non-optimal guess.

Useful links:

• Data base

• Vitibet (professional forecast)

Merging bibtex files

When writing papers in collaboration one often generates a number of bibtex files, where many of them have a large overlap. Then you would like to merge them into one file and resolve the problem of multiple entries in a simple but meaningful way.

This python program provides a way to do exactly that: it merges the bibfiles from one folder into one file and in case of multiple entries it takes the one that comes from the most recent bibtex file.