Monte Carlo renormalization-group analysis of percolation.

We describe a Monte Carlo renormalization group approach to the calculation of critical behavior for percolation models. This approach can be utilized to determine the renormalized bond probabilities and the values of the critical exponents. We illustrate the method for two-dimensional bond percolation, but the method is also applicable to other percolation models and other dimensions.

Genetic algorithm optimization for focusing through turbid media in noisy environments.

We introduce genetic algorithms (GA) for wavefront control to focus light through highly scattering media. We theoretically and experimentally compare GAs to existing phase control algorithms and show that GAs are particularly advantageous in low signal-to-noise environments.