This thesis describes the search for KL 2![pi]0[pi]0[mu]+[mu]-, which was conducted using data collected by the KTeV Experiment at Fermi National Accelerator Laboratory in Batavia, Illinois. Although this decay mode is possible within the Standard Model, it is limited to a very narrow band of phase space. The HyperCP Experiment has recently observed three [Sigma]+ 2!p[mu]+[mu]- events within a narrow dimuon mass range of 213.8 MeV/c2 to 214.8 MeV/c2. This suggests that the process could occur via a neutral intermediary particle, [Sigma]+ 2!pX0 2!p[mu]+[mu]-, with an X0 mass of 214.3 MeV/c2 ± 0.5 MeV/c2 . Since the X0 has a light mass and a low interaction probability, then it is most likely a new neutral boson that exists beyond the Standard Model. Recent theoretical predictions suggest that the decay mode KL 2![pi]0[pi]0[mu]+[mu]- can also occur via the aforementioned neutral boson: KL 2![pi]0[pi]0X02![pi]0[pi]0[mu]+[mu]-. Therefore, in addition to a Standard Model measurement, the search for KL 2![pi]0[pi]0[mu]+[mu]- is also carried out in an effort to address the viability of X0 in explaining the HyperCP phenomena. Measurement of the upper limits presented in this thesis were performed using blind analysis techniques. The upper limit of the decay KL 2![pi]0[pi]0[mu]+[mu]- has been measured in this thesis to be BR(KL 2![pi]0[pi]0[mu]+[mu]- )

Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.

An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.