Proposal

The abundance of intelligent civilisations in the Galaxy is a

longstanding question related to the expected probability of success for SETI programs.  Traditional approaches to quantify this problem use either frequentist inferences or numerical simulations. The key challenges in both cases are the proper treatment of the time variable and the large uncertainties on the intervening factors. Here we present a three-parametric statistical model of the network of causally connected locations in a simplified Galaxy, with the restriction of a maximum distance range for any signal. We implement Monte Carlo simulations of this model to explore the parameter space and analyse the probabilities of causal contacts for random locations in the Galaxy.

We find

that, given the enormous distances involved, causal contacts between civilisations would be very rare. The odds to make a contact in a few years of monitoring are low for most models, except for those of a galaxy densely populated with ancient civilisations. The probability of causal contacts increases with the lifetime of civilisations more significantly than with the number of active civilisations. We show that the maximum probability of making a contact occurs when a civilization discovers the required communication technology.

Methods and working hypothesis

Simulations are suitable tools to analyze systems that evolve with time and involve randomness.

An advantage of simulations compared to theoretical approaches, is that the former usually require less assumptions and simplifications, and can be applied to systems where a theoretical model can not be found.

In particular, many complex stochastic processes that can be described by the evolution of the state of a system, can be efficiently modeled with the discrete–event (hereafter, DE) simulation approach.

A system described with the DE paradigm is characterized by a set of actors and events, where actors interact causally through a series of events on a timeline and process these events in chronological order

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Space-time diagrams showing the causal contact connections.

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All possible cases for the generation of events.