High speed liquid crystal over silicon display based on the flexoelectro-optic effect.

One of the key technologies to evolve in the displays market in recent years is liquid crystal over silicon (LCOS) microdisplays. Traditional LCOS devices and applications such as rear projection televisions, have been based on intensity modulation electro-optical effects, however, recent developments have shown that multi-level phase modulation from these devices is extremely sought after for applications such as holographic projectors, optical correlators and adaptive optics. Here, we propose alternative device geometry based on the flexoelectric-optic effect in a chiral nematic liquid crystal. This device is capable of delivering a multilevel phase shift at response times less than 100 microsec which has been verified by phase shift interferometry using an LCOS test device. The flexoelectric on silicon device, due to its remarkable characteristics, enables the next generation of holographic devices to be realized.

Bayesian model selection for time series using Markov chain Monte Carlo

We present a stochastic simulation technique for subset selection in time series models, based on the use of indicator variables with the Gibbs sampler within a hierarchical Bayesian framework. As an example, the method is applied to the selection of subset linear AR models, in which only significant lags are included. Joint sampling of the indicators and parameters is found to speed convergence. We discuss the possibility of model mixing where the model is not well determined by the data, and the extension of the approach to include non-linear model terms.