From Laplace to supernova SN 1987a: Bayesian Inference In Astrophysics

The Bayesian approach to probability theory is presented as an alternative to the currently used long-run relative frequency approach, which does not offer clear, compelling criteria for the design of statistical methods. Bayesian probability theory offers unique and demonstrably optimal solutions to well-posed statistical problems, and is historically the original approach to statistics. The reasons for earlier rejection of Bayesian methods are discussed, and it is noted that the work of Cox, Jaynes, and others answers earlier objections, giving Bayesian inference a firm logical and mathematical foundation as the correct mathematical language for quantifying uncertainty. The Bayesian approaches to parameter estimation and model comparison are outlined and illustrated by application to a simple problem based on the gaussian distribution. As further illustrations of the Bayesian paradigm, Bayesian solutions to two interesting astrophysical problems are outlined: the measurement of weak signals in a strong background, and the analysis of the neutrinos detected from supernova SN 1987A. A brief bibliography of astrophysically interestin

Finding simplicity in complexity: general principles of biological and nonbiological organization

What differentiates the living from the nonliving? What is life? These are perennial questions that have occupied minds since the beginning of cultures. The search for a clear demarcation between animate and inanimate is a reflection of the human tendency to create borders, not only physical but also conceptual. It is obvious that what we call a living creature, either bacteria or organism, has distinct properties from those of the normally called nonliving. However, searching beyond dichotomies and from a global, more abstract, perspective on natural laws, a clear partition of matter into animate and inanimate becomes fuzzy. Based on concepts from a variety of fields of research, the emerging notion is that common principles of biological and nonbiological organization indicate that natural phenomena arise and evolve from a central theme captured by the process of information exchange. Thus, a relatively simple universal logic that rules the evolution of natural phenomena can be unveiled from the apparent complexity of the natural world