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Register a new userPostulating Exoplanetary Habitability via a Novel Anomaly Detection Method
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Margarita Safonova Dr.
Publication date
2021
fields
Physics
and research's language is
English
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A profound shift in the study of cosmology came with the discovery of thousands of exoplanets and the possibility of the existence of billions of them in our Galaxy. The biggest goal in these searches is whether there are other life-harbouring planets. However, the question which of these detected planets are habitable, potentially-habitable, or maybe even inhabited, is still not answered. Some potentially habitable exoplanets have been hypothesized, but since Earth is the only known habitable planet, measures of habitability are necessarily determined with Earth as the reference. Several recent works introduced new habitability metrics based on optimization methods. Classification of potentially habitable exoplanets using supervised learning is another emerging area of study. However, both modeling and supervised learning approaches suffer from drawbacks. We propose an anomaly detection method, the Multi-Stage Memetic Algorithm (MSMA), to detect anomalies and extend it to an unsupervised clustering algorithm MSMVMCA to use it to detect potentially habitable exoplanets as anomalies. The algorithm is based on the postulate that Earth is an anomaly, with the possibility of existence of few other anomalies among thousands of data points. We describe an MSMA-based clustering approach with a novel distance function to detect habitable candidates as anomalies (including Earth). The results are cross-matched with the habitable exoplanet catalog (PHL-HEC) of the Planetary Habitability Laboratory (PHL) with both optimistic and conservative lists of potentially habitable exoplanets.
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It is currently unknown how common life is on exoplanets, or how long planets can remain viable for life. To date, we have a superficial notion of habitability, a necessary first step, but so far lacking an understanding of the detailed interaction between stars and planets over geological timescales, dynamical evolution of planetary systems, and atmospheric evolution on planets in other systems. A planet mass, net insolation, and atmospheric composition alone are insufficient to determine the probability that life on a planet could arise or be detected. The latter set of planetary considerations, among others, underpin the concept of the habitable zone (HZ), defined as the circumstellar region where standing bodies of liquid water could be supported on the surface of a rocky planet. However, stars within the same spectral class are often treated in the same way in HZ studies, without any regard for variations in activity among individual stars. Such formulations ignore differences in how nonthermal emission and magnetic energy of transient events in different stars affect the ability of an exoplanet to retain its atmosphere.In the last few years there has been a growing appreciation that the atmospheric chemistry, and even retention of an atmosphere in many cases, depends critically on the high-energy radiation and particle environments around these stars. Indeed, recent studies have shown stellar activity and the extreme space weather, such as that created by the frequent flares and coronal mass ejections (CMEs) from the active stars and young Sun, may have profoundly affected the chemistry and climate and thus habitability of the early Earth and terrestrial type exoplanets. The goal of this white paper is to identify and describe promising key research goals to aid the field of the exoplanetary habitability for the next 20 years.
In this Letter, we make use of sophisticated 3D numerical simulations to assess the extent of atmospheric ion and photochemical losses from Mars over time. We demonstrate that the atmospheric ion escape rates were significantly higher (by more than two orders of magnitude) in the past at $sim 4$ Ga compared to the present-day value owing to the stronger solar wind and higher ultraviolet fluxes from the young Sun. We found that the photochemical loss of atomic hot oxygen dominates over the total ion loss at the current epoch whilst the atmospheric ion loss is likely much more important at ancient times. We briefly discuss the ensuing implications of high atmospheric ion escape rates in the context of ancient Mars, and exoplanets with similar atmospheric compositions around young solar-type stars and M-dwarfs.
We present a novel technique for Cosmic Microwave Background (CMB) foreground subtraction based on the framework of blind source separation. Inspired by previous work incorporating local variation to Generalized Morphological Component Analysis (GMCA), we introduce Hierarchical GMCA (HGMCA), a Bayesian hierarchical graphical model for source separation. We test our method on $N_{rm side}=256$ simulated sky maps that include dust, synchrotron, free-free and anomalous microwave emission, and show that HGMCA reduces foreground contamination by $25%$ over GMCA in both the regions included and excluded by the Planck UT78 mask, decreases the error in the measurement of the CMB temperature power spectrum to the $0.02-0.03%$ level at $ell>200$ (and $<0.26%$ for all $ell$), and reduces correlation to all the foregrounds. We find equivalent or improved performance when compared to state-of-the-art Internal Linear Combination (ILC)-type algorithms on these simulations, suggesting that HGMCA may be a competitive alternative to foreground separation techniques previously applied to observed CMB data. Additionally, we show that our performance does not suffer when we perturb model parameters or alter the CMB realization, which suggests that our algorithm generalizes well beyond our simplified simulations. Our results open a new avenue for constructing CMB maps through Bayesian hierarchical analysis.
Habitability has been generally defined as the capability of an environment to support life. Ecologists have been using Habitat Suitability Models (HSMs) for more than four decades to study the habitability of Earth from local to global scales. Astrobiologists have been proposing different habitability models for some time, with little integration and consistency among them, being different in function to those used by ecologists. Habitability models are not only used to determine if environments are habitable or not, but they also are used to characterize what key factors are responsible for the gradual transition from low to high habitability states. Here we review and compare some of the different models used by ecologists and astrobiologists and suggest how they could be integrated into new habitability standards. Such standards will help to improve the comparison and characterization of potentially habitable environments, prioritize target selections, and study correlations between habitability and biosignatures. Habitability models are the foundation of planetary habitability science and the synergy between ecologists and astrobiologists is necessary to expand our understanding of the habitability of Earth, the Solar System, and extrasolar planets.
Observations of extrasolar planets were not projected to be a significant part of the Spitzer Space Telescopes mission when it was conceived and designed. Nevertheless, Spitzer was the first facility to detect thermal emission from a hot Jupiter, and the range of Spitzers exoplanetary investigations grew to encompass transiting planets, microlensing, brown dwarfs, and direct imaging searches and astrometry. Spitzer used phase curves to measure the longitudinal distribution of heat as well as time-dependent heating on hot Jupiters. Spitzers secondary eclipse observations strongly constrained the dayside thermal emission spectra and corresponding atmospheric compositions of hot Jupiters, and the timings of eclipses were used for studies of orbital dynamics. Spitzers sensitivity to carbon-based molecules such as methane and carbon monoxide was key to atmospheric composition studies of transiting exoplanets as well as imaging spectroscopy of brown dwarfs, and complemented Hubble spectroscopy at shorter wavelengths. Spitzers capability for long continuous observing sequences enabled searches for new transiting planets around cool stars, and helped to define the architectures of planetary systems like TRAPPIST-1. Spitzer measured masses for small planets at large orbital distances using microlensing parallax. Spitzer observations of brown dwarfs probed their temperatures, masses, and weather patterns. Imaging and astrometry from Spitzer was used to discover new planetary mass brown dwarfs and to measure distances and space densities of many others.
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