Application of MARS for modeling local nonlinear relationships in data on ultraviolet copper ion lasers

Abstract

Articles you may be interested inExtended temperature tuning of an ultraviolet diode laser for trapping and cooling single Yb + ions Rev. Sci. Instrum. 81, 053110 (2010); 10.1063/1.3386580Three-dimensional simulation of laser-produced plasma for extreme ultraviolet lithography applications Abstract. When analyzing experiment data, the main statistical procedure is finding relationships in the data and developing models to describe them. Modeling is a powerful means of estimation, simulation, and prediction of the experiment and an indispensable tool in practical engineering. This paper considers the use of the multivariate adaptive regression splines (MARS) method to describe local relationships in the experiment data for several types of metal vapor lasers. The investigated data has been collected from patented UV ion lasers developed at the Bulgarian Academy of Sciences in the last ten years. A short description of MARS is provided. Specific MARS models have been developed describing the efficiency of an ultraviolet ion copper bromide vapor laser dependent on the change of 9 main input physical laser characteristics. The models are of linear and nonlinear type. It has been established that the best statistical indices and model fit are those of nonlinear models which contain second order local terms. The models account for about 95% of the data. The models are used to analyze the local behavior of the efficiency of various devices from the types of lasers under investigation. Graphs illustrating the established relationships are provided. The ability to predict future experiments is demonstrated.