Michael G. Gowanlock

A Model of Habitability Within the Milky Way Galaxy

We present a model of the galactic habitable zone (GHZ), described in terms of the spatial and temporal dimensions of the Galaxy that may favor the development of complex life. The Milky Way galaxy was modeled using a computational approach by populating stars and their planetary systems on an individual basis by employing Monte Carlo methods. We began with well-established properties of the disk of the Milky Way, such as the stellar number density distribution, the initial mass function, the star formation history, and the metallicity gradient as a function of radial position and time. We varied some of these properties and created four models to test the sensitivity of our assumptions. To assess habitability on the galactic scale, we modeled supernova rates, planet formation, and the time required for complex life to evolve. Our study has improved on other literature on the GHZ by populating stars on an individual basis and modeling Type II supernova (SNII) and Type Ia supernova (SNIa) sterilizations by selecting their progenitors from within this preexisting stellar population. Furthermore, we considered habitability on tidally locked and non-tidally locked planets separately and studied habitability as a function of height above and below the galactic midplane. In the model that most accurately reproduces the properties of the Galaxy, the results indicate that an individual SNIa is ∼5.6× more lethal than an individual SNII on average. In addition, we predict that ∼1.2% of all stars host a planet that may have been capable of supporting complex life at some point in the history of the Galaxy. Of those stars with a habitable planet, ∼75% of planets are predicted to be in a tidally locked configuration with their host star. The majority of these planets that may support complex life are found toward the inner Galaxy, distributed within, and significantly above and below, the galactic midplane.

Assessing researcher interdisciplinarity: a case study of the University of Hawaii NASA Astrobiology Institute

In this study, we combine bibliometric techniques with a machine learning algorithm, the sequential information bottleneck, to assess the interdisciplinarity of research produced by the University of Hawaii NASA Astrobiology Institute (UHNAI). In particular, we cluster abstract data to evaluate Thomson Reuters Web of Knowledge subject categories as descriptive labels for astrobiology documents, assess individual researcher interdisciplinarity, and determine where collaboration opportunities might occur. We find that the majority of the UHNAI team is engaged in interdisciplinary research, and suggest that our method could be applied to additional NASA Astrobiology Institute teams in particular, or other interdisciplinary research teams more broadly, to identify and facilitate collaboration opportunities.

Extending Galactic Habitable Zone Modeling to Include the Emergence of Intelligent Life

Previous studies of the galactic habitable zone have been concerned with identifying those regions of the Galaxy that may favor the emergence of complex life. A planet is deemed habitable if it meets a set of assumed criteria for supporting the emergence of such complex life. In this work, we extend the assessment of habitability to consider the potential for life to further evolve to the point of intelligence--termed the propensity for the emergence of intelligent life, φI. We assume φI is strongly influenced by the time durations available for evolutionary processes to proceed undisturbed by the sterilizing effects of nearby supernovae. The times between supernova events provide windows of opportunity for the evolution of intelligence. We developed a model that allows us to analyze these window times to generate a metric for φI, and we examine here the spatial and temporal variation of this metric. Even under the assumption that long time durations are required between sterilizations to allow for the emergence of intelligence, our model suggests that the inner Galaxy provides the greatest number of opportunities for intelligence to arise. This is due to the substantially higher number density of habitable planets in this region, which outweighs the effects of a higher supernova rate in the region. Our model also shows that φI is increasing with time. Intelligent life emerged at approximately the present time at Earths galactocentric radius, but a similar level of evolutionary opportunity was available in the inner Galaxy more than 2 Gyr ago. Our findings suggest that the inner Galaxy should logically be a prime target region for searches for extraterrestrial intelligence and that any civilizations that may have emerged there are potentially much older than our own.

Computer-Aided Discovery: Toward Scientific Insight Generation with Machine Support

The process of scientific discovery is traditionally assumed to be entirely executed by humans. This article highlights how increasing data volumes and human cognitive limits are challenging this traditional assumption. Relevant examples are found in observational astronomy and geoscience, disciplines that are undergoing transformation due to growing networks of space-based and ground-based sensors. The authors outline how intelligent systems for computer-aided discovery can routinely complement and integrate human scientists in the insight generation loop in scalable ways for next-generation science. The pragmatics of model-based computer-aided discovery systems go beyond feature detection in empirical data to answer fundamental questions, such as how empirical detections fit into hypothesized models and model variants to ease the scientists work of placing large ensembles of detections into a theoretical context. The authors demonstrate successful applications of this paradigm in several areas, including ionospheric studies, volcanics, astronomy, and planetary landing site identification for spacecraft and robotic missions.

Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

Applications in many domains search moving object trajectory databases. The distance threshold search finds all trajectories within a given distance of a query trajectory. We develop three GPU distance threshold search implementations that use indexing techniques significantly different from those used in CPU implementations. We determine experimentally under which conditions each approach performs well using one real-world astrophysics dataset and two synthetic datasets. Overall, we find that the GPU is an attractive technology for a broad range of relevant trajectory database scenarios.

ASTROBIOLOGICAL EFFECTS OF GAMMA-RAY BURSTS IN THE MILKY WAY GALAXY

A planet having protective ozone within the collimated beam of a Gamma Ray Burst (GRB) may suffer ozone depletion, potentially causing a mass extinction event to existing life on a planets surface and oceans. We model the dangers of long GRBs to planets in the Milky Way and utilize a static statistical model of the Galaxy that matches major observable properties, such as the inside-out star formation history, metallicity evolution, and 3-dimensional stellar number density distribution. The GRB formation rate is a function of both the star formation history and metallicity; however, the extent to which chemical evolution reduces the GRB rate over time in the Milky Way is still an open question. Therefore, we compare the damaging effects of GRBs to biospheres in the Milky Way using two models. One model generates GRBs as a function of the inside-out star formation history. The other model follows the star formation history, but generates GRB progenitors as a function of metallicity, thereby favoring metal-poor host regions of the Galaxy over time. If the GRB rate only follows the star formation history, the majority of the GRBs occur in the inner Galaxy. However, if GRB progenitors are constrained to low metallicity environments, then GRBs only form in the metal-poor outskirts at recent epochs. Interestingly, over the past 1 Gyr, the surface density of stars (and their corresponding planets) that survive a GRB is still greatest in the inner galaxy in both models. The present day danger of long GRBs to life at the solar radius (

Distance threshold similarity searches on spatiotemporal trajectories using GPGPU

R_\odot=8

Clustering Throughput Optimization on the GPU

kpc) is low. We find that at least

Superresolution full-polarimetric imaging for radio interferometry with sparse modeling

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Exploiting Variant-Based Parallelism for Data Mining of Space Weather Phenomena

65% of stars survive a GRB over the past 1 Gyr. Furthermore, when the GRB rate was expected to have been enhanced at higher redshifts, such as