Assessing Planetary Complexity and Potential Agnostic Biosignatures using Epsilon Machines

We present a new approach to exoplanet characterization using tech-niques from complexity science, with potential applications to biosig-nature detection. This agnostic method makes use of the temporalvariability of light reected or emitted from a planet. We use a tech-nique known as epsilon machine reconstruction to compute the statisticalcomplexity, a measure of the minimal model size for time series data.We demonstrate that statistical complexity is an e ective measure ofthe complexity of planetary features. Increasing levels of qualitativeplanetary complexity correlate with increases in statistical complexityand Shannon entropy, demonstrating that our approach can identifyplanets with the richest dynamics. We also compare Earth time serieswith Jupiter data, and nd that for the three wavelengths consid-ered, Earth's average complexity and entropy rate are approximately 50% and 43% higher than Jupiter's, respectively. The majority ofschemes for the detection of extraterrestrial life rely upon biochemicalsignatures and planetary context. However, it is increasingly recog-nized that extraterrestrial life could be very di erent to life on Earth.Under the hypothesis that there is a correlation between the pres-ence of a biosphere and observable planetary complexity, our techniqueo ers an agnostic and quantitative method for the measurement thereof.