Electron Density Determination of Laser Induced Plasma from Polymethyl Methacrylate Using Phaseshift Detection Technique

Irradiation of a Polymethyl methacrylate target using a pulsed Nd-YAG laser causes plasma formation in the vicinity of the target. The refractive index gradient due to the presence of the plasma is probed using phase-shift detection technique. The phase-shift technique is a simple but sensitive technique for the determination of laser ablation threshold of solids. The number density of laser generated plasma above the ablation threshold from Polymethyl methacrylate is calculated as a function of laser fluence. The number density varies from 2×1016 cm-3 to 2×1017 cm-3 in the fluence interval 2.8-13 J · cm-2.

An Optical limiter based on Ferrofluids

We report an optical limiter based on ferrofluids which has a very high shelf life and remarkable thermal stability, which are important requirements for sustainable use with intense lasers. The colloidal suspensions contain nanosized particles of approximately 80 Å diameter, with a number density of the order of 1022 /m3. The nonlinear optical transmission of the samples is studied using nanosecond and femtosecond laser pulses. Excited state absorption phenomena contribute to enhanced limiting in the nanosecond excitation regime. An advantageous feature of ferrofluids in terms of device applications is that their optical properties are controllable by an external magnetic field.

ARMA modeling of time series based on rational approximation of spectral density function

This study is concerned with Autoregressive Moving Average (ARMA) models of time series. ARMA models form a subclass of the class of general linear models which represents stationary time series, a phenomenon encountered most often in practice by engineers, scientists and economists. It is always desirable to employ models which use parameters parsimoniously. Parsimony will be achieved by ARMA models because it has only finite number of parameters. Even though the discussion is primarily concerned with stationary time series, later we will take up the case of homogeneous non stationary time series which can be transformed to stationary time series. Time series models, obtained with the help of the present and past data is used for forecasting future values. Physical science as well as social science take benefits of forecasting models. The role of forecasting cuts across all fields of management-—finance, marketing, production, business economics, as also in signal process, communication engineering, chemical processes, electronics etc. This high applicability of time series is the motivation to this study.