Eric Sembrat's Test Bonanza

Take a break from studying and come listen to Prof. Yoshida describe the history of the universe over 13 billion years since the Big Bang. He will use the visual results from recent state-of-the-art computer simulations that aid our understanding on how astronomical objects such as stars, galaxies, and black holes form in an expanding universe. He will explore prospects for future high-performance computing using exascale computers.

Galaxy clusters are the most massive virialized objects in the universe, and have the potential to be highly accurate probes of cosmological parameters. A fundamental challenge for cluster cosmology is to estimate the masses of these objects using observational proxies such as X-ray luminosity and temperature, which are complicated by the merger history of clusters and the microphysical properties of the intracluster medium. These effects, while frustrating to cosmologists, provide a rich laboratory for exploring the plasma physical processes that are occurring in these massive objects. In this talk I will present recent efforts to understand the effects that several plasma processes - including conduction and AGN feedback - have on the observable properties of galaxy clusters.

Exoplanet surveys have revealed an amazing diversity of planets orbiting other stars in the last two decades. Studying the atmospheres of representative exoplanets is the key next step in leveraging these detections to further transform our understanding of planet formation and planetary physics. Additionally, atmospheric studies are critical for determining if any of the small habitable zone exoplanets that are now being detected are truly habitable, and even inhabited. In this talk I will describe recent results from exoplanet atmosphere observations with an emphasis on results from major programs using the Hubble Space Telescope. Although atmospheric studies of potentially habitable planets are currently out of reach, I will discuss how future facilities may open up this possibility in the near future.

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Microbial ecosystems in the top decimeters of sediment play an important role in determining the chemistry of the atmosphere and help support multicellular life. The metabolic rates of these microbes are strongly limited by the time it takes nutrients to diffuse from the surface. Here we combine experiments, mathematical models, and field work to understand how two microbes, the bacteria Thiovulum majus and the eukaryote Uronemella, respond collectively to overcome diffusion limitation. These microbes have independently evolved the ability attach to surfaces by means of a mucus tether. Once tethered, cells use their flagella or cilia to pump nutrient-rich water. Microbes also attach to members of their own species to form a centimeter-scale community called a ``veil''. In a veil, cells generate a macroscopic flow that mixes its environment 40 times more efficiently than do individuals. We show how this collective behavior arises from the individual behavior of cells. In the second part of the talk, we describe a new form of collective dynamics displayed by T. majus. Untethered bacteria self organize on a surface into rotating two-dimensional crystals of quickly spinning cells. These crystals show a number of rich phenomena including the formation of fixed points, limit cycles, and surface melting. Proceeding from a force balance on each cell, we show how this visually-striking behavior arises from the flow of water being created by each cell. These results provide mathematically tractable examples of how the large-scale behavior of microbial communities in the environment arises from the response of individual cells to nutrient limitation.

The collective motion of a large group of individuals has two different scales. Individuals move and interact on a local scale, while the motion of the group as a whole occurs on a global scale. All the movement of the group on the global scale is produced by the many movements of its members, and so a good model for the global behaviour should arise from local models for the individuals. We investigate the link between the two scales, and create formulae for producing a global model for any particular lattice-based local model using mean-field approximations.

We introduce an inverse design approach based on minimal theoretical modeling, direct numerical simulations and artificial intelligence techniques for the investigation of biolocomotion in fluids. Its application to the characterization of inertial aquatic phenomena and to the identification of optimal swimming gaits and morphologies is presented.

 TBD