In the field of Astrobiology, a quantitative approach has not been made to predict the number of extraterrestrial intelligent civilizations that may have existed on a habitable exoplanet as well their corresponding properties, such as intelligence, lifespan, and recovery time. Prior research indicates that numerous planetary systems within the Milky Way Galaxy are of over six billion years in age, implying many exoplanets, if sustainable to life, may have had several cycles of civilizations emergence and self-destruction, suggesting the ruins of advanced civilizations should be commonplace within the galaxy. We investigate this problem by utilizing statistical algorithmic simulations to predict and estimate the number of civilizations (both future and extinct) that may arise within an exoplanetary continuum, further generating the accompanying characteristics of said civilizations. Within the model, factors such as self-induced extinction/destruction, natural civilization decay, planetary disasters, and civilization rediscovery have been incorporated to examine the pathways a civilization can encounter. Our results corroborate the notion that on many of the older exoplanets in our galaxy, civilizations may have existed, however most have ultimately died out within a short period, further limiting the search for current extraterrestrial intelligence, but strengthening the approach of interstellar archeology.

Here we explore the detection limits of a seismic event originating from Europa’s silicate interior. Such an event could be used to constrain the tectonic regime, rheology, and internal dynamics of Europa’s deep interior. We use PlanetProfile to generate interior structure models of Europa with ice shell ranging from 5-50 km in thickness. We then use the models as inputs for AxiSEM and InstaSeis to generate a database of seismograms. Realistic noise is added using the approach of Panning et al. 2018. We show that a deep event (depth 155km) would produce seismic signals 1/10- 1/75 the amplitude of shallow (depth 3km) events. Thinner ice shells allow for more ground motion, and thus, a seismometer could detect a smaller magnitude event than if the ice shell was thick. A Mw 3.5 could overcome background noise, but a Mw 4.5 or greater is necessary to be detectable by even the most sensitive seismic instrumentation. A Mw 5.0 or greater is likely needed to be seen by a seismometer on Europa’s surface. Constraining deep seismicity would allow for better constraints on the deep internal structure and dynamics of Europa.

Chaotropicity (order-destroying) describes the entropic disordering of lipid bilayers and other biomacromolecules which is caused by substances dissolved in water. Solvents in water are defined as kosmotropic (order-making) if they contribute to the stability and structure of water-water interactions. These interactions between brine solutions (water and salt) and ancestral proteins (AncC ribonuclease) induce varying changes in the protein’s structure. Understanding how these brine solutions and early protein structures interact provides insight into the origins of life and zones of habitability across the solar system. Here, we used a molecular dynamics simulator to assess the reaction of an ancient protein (ribonuclease sequence) when exposed to .15M and 1.5M concentrations of MgCl2 and NaCl. The ancient ribonuclease structure responded uniquely to .15M NaCl and both concentrations of MgCl2. Both the nature of the cation and concentration of the salt promote different responses and effects in the secondary structures of the AncC protein. According to the Hoffmeister Series scale, sodium is more kosmotropic and magnesium is more chaotropic. These two different salts with two different chao-kosmo properties create two different responses within the protein structure in that particular brine. This observation speaks highly to the significance of chao-kosmo influences on molecular level outcomes.

The search for life in the universe can inspire students and members of the public alike. Three projects are described which provide an immersive experience with astrobiology. The first is teaching astrobiology to non-science majors in the virtual world Second Life. Second Life can support authentic learning and foster cross-cultural competencies. In the next iteration of the course, students will create simulations of exoplanet landscapes and architectures of exoplanetary systems. The second project is a virtual reality exhibit for education and outreach. It has models of major facilities in astronomy and space science in a virtual space. Users wear Oculus Quest headsets and use game controllers to navigate. Next additions to the VR space will be examples of exoplanet science and fully animated exoplanet systems. The third project is a new version of a multimedia performance piece called StellarScape, combining original electronic music, dance and simulations of star birth. A live dancer interacts with simulations via sensors. The next version is PlanetScape, where back-projected video is a series of realistically rendered exoplanet surfaces. The dancer undertakes a “hero’s journey,” experiencing the altered gravity and physical conditions of alien planets as they try to find their way home.

We utilize the Planet Model Code [1] to model the probability of survival of Earth-like life on habitable worlds (to 3 billion years post-abiogenesis). The Planet Model Code [1] was originally created by Tyrrell [2] to investigate the chances of intelligent life. This necessitates stability in a rather narrow temperature range. Here we expand the focus to the survival of any life, including extremophiles, with greater tolerance for variations in temperature. Specifically, we investigate the relationship between the long-term survival probability of life and larger temperature variations. Keywords: Exoplanet; Habitable; Prokaryote; Matlab; Planet Model Code References: 1. T. Tyrrell, Planets model code, (Oct. 2020) https://doi.org/10.5281/zenodo.4081451. 2. T. Tyrrell, “Chance played a role in determining whether earth stayed habitable”, Commu- nications Earth & Environment 1, 1–10 (2020).

Documentation of primitive terrestrial life signatures and the methods used to characterize them will be relevant to identify signatures of biological origin at the surface of Mars. In this respect, fossils of chemolithotrophic microorganisms found in ancient volcanic rocks on Earth are used as analogues for the kinds of microorganisms that could be found on Mars. Indeed, chemolithotrophs are the ancient forms of life thought to inhabit the first habitats on Earth and potentially on Mars when the two planets had similar conditions in their early history, i.e. an atmosphere, geological activity and enough liquid water in specific habitable localities for a prolonged period of time.

Natural-like technosignatures candidates may represent a detection problem for both artificial systems and humans. We tested traditional computer vision models with natural formations with special characteristics, Ahuna Mons region in Ceres in this particular case. We looked if these artificial models may represent a trustful aid to human detection and identification of potential technosignatures in planetary surfaces. Ahuna Mons is a 4km particular geologic feature on the surface of Ceres of possibly cryovolcanic origin. The special characteristics of Ahuna Mons are also interesting in regard of its surrounding area, especially for the big crater besides. This crater possesses similarities with Ahuna Mons including diameter, age, morphology, etc. Under the cognitive psychology perspective and using current computer vision models we analyzed these two features on Ceres for comparison and pattern recognition similarities. Several algorithms were employed avoiding human cognitive bias. 3D analysis from images of both features characteristics are discussed. Results showed positive results for these algorithms about similarities of both features. Discussion is provided about implications of this pilot computer vision techniques experiment for Ahuna Mons and the potential cognitive bias problem of both human and Artificial Intelligence models and the risks for the search of technosignatures.

Enceladus is one of the moons of Saturn that has caught the attention of scientists due to the potential for harboring life. It has a stratified internal structure, below its ice shell has been detected an ocean layer which material is expelled through the jets from the plumes located in the south pole. The ice layer could limit the exchange of material between the ocean and the atmosphere. We present a model of the thermal atmospheric evolution with the presence of clouds, in order to understand, what would happen in the ice crust if the atmosphere has a small greenhouse effect. That change in the atmosphere was present during the Snowball period on Earth, where some molecules from the primitive ocean were liberated into the atmosphere. Those molecules probably are present in the ocean on Enceladus. We also present a comparative geochemical analysis of the molecules present in the ocean of Enceladus and the ones which were present in the ocean of Earth during the Snowball period in order to predict if Enceladus is in a primitive evolutionary stage and if these molecules could interact with the atmosphere if the ice crust has a destabilization.

The DNA molecules are stable but easily fragmented by ionization radiation, which challenges DNA integrity in searching for evidence for extraterrestrial life on icy satellites. The objective was to estimate the highest value of the attenuation effect of freezing temperature on the efficacy of gamma-radiation in fragmenting dsDNA. A bacterial 16S rRNA gene inserted in a vector as a lyophilized crude cell lysate was irradiated (60Co) under the liquid nitrogen conditions (-195.8oC). The outcome was tested in a specific PCR, generating the MAIN (~600bp) as well as EXTRA “mis-primed” small-sized (~70bp) amplicons. At the ambient temperature, the main PCR product entirely disappeared upon the doze 7.5kGy while at -195.8oC, it withstood ~750kGy (~100 times difference). Vise-verse, the EXTRA short amplicon reached the maximum outcome at the dose ~400kGy and continued to persist until the tested dose 840kGy. By extrapolation, the given product could be generated upon irradiating target DNA at a dose of more than 1mGy. Such a find opens a chance (and time window of more than 25 years) to pick up freshly flushed out sub-ice-ocean microbes/DNA and get frozen as inclusions in water matrices on the Jovian Europa to verify the extraterrestrial life.

Every river and its bed has a flourishing life thriving environment. Search of life in these region will help us to find out if really life existed in Mars. Commonly life could be of any form based on the surrounding environment. Artificial Intelligence could help us to find what kind of organisms could have existed based on the minerals found in the Jezero Crater site. In this research we deep learning with the list of elements found at site and conclude to what kind of creature sediments to search for. This could make our search easier to look for sediments. The basic idea of this research to bring out what to search for based on the environment in and around the Jezero Crater.

The core argument is that there may be a right to some of the knowledge that astrobiology can supply about the origins of life, and specifically about our human origins. Such a right might be appealed to in international agreements and declarations by bodies such as the UN.

In the near-future, new space telescopes like JWST, LUVOIR, and HabEx will begin attempting to explore the properties of atmospheres of potentially habitable planets. This will require a significant amount of time and resources for even a single planet, which makes it essential to prioritize observations by those most-likely to have detectable life. Here we present a statistical method to estimate the probabilities that specific exoplanets have been continuously in the habitable zone of their host stars for more than 2 billion years, the approximate time it took life on Earth to significantly increase the oxygen content of the atmosphere. We introduce the use of statistics of an ensemble of 3D planetary general circulation models to estimate these probabilities, replacing prior 1D model estimates.