## Genetic algorithm for experiment optimization

We employ an evolutionary algorithm to automatically optimize different stages of a cold atom experiment without human intervention. This approach closes the loop between computer based experimental control systems and automatic real time analysis and can be applied to a wide range of experimental situations. The genetic algorithm quickly and reliably converges to the most performing parameter set independent of the starting population. Especially in many-dimensional or connected parameter spaces, the automatic optimization outperforms a manual search.

Rohringer, W., R Bücker, S Manz, T Betz, Ch. Koller, M Göbel, A Perrin, Jörg Schmiedmayer, and T Schumm.

*Stochastic Optimization of a Cold Atom Experiment Using a Genetic Algorithm. *

*Applied Physics Letters* 93 (2008): 264101