Algorithm for Discriminating the Signal from the Background to Search for Non-Naryonic Super-Symmetric Dark Matter

Abstract

Neutralino, a super symmetric particle linearly composed of super partners, has been estimated to be a candidate for a weakly interacting massive particle (WIMP). The WIMP has been considered a major part of non-baryonic dark matter located in galactic halo. Already, many experimental studies have searched for WIMPs in the last two decades. The same as other particle physics experiemnts, the direct detection methods searching for the WIMP provides many signals and backgrounds. We estimate our liquid or solid detectors to provide at least 10(-2)/kg/day and up tp 10(12) background signal a day with a direct detection method. To handle those data, we need to establish a data-finding algorithm based oil e-science. Our signal finding and data analysis algorithm will help to discriminate signals from background, to determine the signal amplitude, and to transfer the created huge date to other computing systems. We have developed a data-finding algorithm, the so-called computer aided significant signal detection (CASSD), that is based on the concept of a moving avrage (MA) and the more advanced concept auto regressive moving average (ARMA) and auto regressive indifference moving averag (ARiMA). We expect the concepts of the ARMA and the ARiMA to be used to detect significant data carefully.