Real-Time Bayesian Analysis of Ground Motion Envelopes for Earthquake Early Warning

Current earthquake early warning systems usually make magnitude and location predictions and send out a warning to the users based on those predictions. We describe an algorithm that assesses the validity of the predictions in real-time. Our algorithm monitors the envelopes of horizontal and vertical acceleration, velocity, and displacement. We compare the observed envelopes with the ones predicted by Cua & Heaton's envelope ground motion prediction equations (Cua 2005). We define a "test function" as the logarithm of the ratio between observed and predicted envelopes at every second in real-time. Once the envelopes deviate beyond an acceptable threshold, we declare a misfit. Kurtosis and skewness of a time evolving test function are used to rapidly identify a misfit. Real-time kurtosis and skewness calculations are also inputs to both probabilistic (Logistic Regression and Bayesian Logistic Regression) and nonprobabilistic (Least Squares and Linear Discriminant Analysis) models that ultimately decide if there is an unacceptable level of misfit. This algorithm is designed to work at a wide range of amplitude scales. When tested with synthetic and actual seismic signals from past events, it works for both small and large events.

Natural cone formation for fast ignition of laser fusion

We propose to utilize the leading pulse of a petawatt class laser to create a conic plasma channel in the dense plasmas. This plasma channel could serve as a natural cone to guide the main pulse to the cone tip, as behaves similarly to the physical Au cone. We estimate that the leading pulse of a petawatt laser could create a natural cone with cone tip only about 100 mu m away from the edge of compressed core plasma. The natural cone formation should be compatible for a good uniform compression and efficient fast heating of the imploded fuel.