A stochastic algorithm for quantifying partial solutions of the Drake Equation

Speaker: Geoffrey Lentner, University of Louisville

Abstract: The prospect of detecting an Extraterrestrial Intelligence (ETI) is supreme and its implications for our collective human perspective goes without saying. There are many ways in which an estimate on the total number of ETIs in the Milky Way can be expressed, the most prominent construction being the Drake Equation. In a new approach, I turn this endeavor on it’s head and instead ask the question, given a solution N, where might me expect to find our nearest neighbor? As we compile more data with projects such as SDSS-III we will be able to model the spatial distribution of key parameters in our search for life and habitability in the Milky Way.

I will present a code I’ve developed for the purpose of numerically modeling galaxies via user defined statistics. Generally speaking, this software has the capability to generate any system of particles confined to a 3D volume. The user defines an arbitrary number of probability density functions (PDFs) in any of the three major coordinate systems. The additional step this program makes is to build an entire ensemble of these systems and perform a nearest neighbor analysis on each to construct functions that describe the expectation of finding a neighbor inside a certain volume given the location of inquiry. There is the potential here for impact with respect to the Fermi paradox and how preferable a location we live in to detect ETIs and/or find habitable worlds.