Astera is a cosmological visualization tool currently being developed at the University of Southampton. Running on a modified version of Unreal Engine, this software renders large cosmological simulations in real time, allowing for interactive, first person control of the universe you have simulated. Although not currently ready for public release, we are excited to show you some of what we are working on.
We use hundreds of galaxy images extracted from the Sloan Digital Sky Survey to represent our galaxies. Any dataset can be used to describe their coordinates and characteristics, but our default dataset is based on the Bolshoi Simulation. These assets are combined using the cutting edge semi-analytic and semi-empirical techniques we use at the University of Southampton to build a mock universe; the result is a visually realistic galaxy catalogue for you to explore at your leisure.
Astera can render many millions of galaxies simultaneously. Fly though the cosmic web and witness the effects of the mysterious underlying distribution of dark matter firsthand. Experience the universe on the largest scales, in a structure that is composed of distinct galaxies.
Astera supports spiral galaxies, lenticular galaxies and the massive elliptical galaxies that reside in the centre of clusters. We have also introduced active galaxies, or AGN, which host a staggeringly bright accreting supermassive black hole. Each galaxy is represented by one of hundreds of hand-picked astronomical images from the Sloan Digital Sky Survey.
To better show off large-scale structure, Astera offers a colour-inverted structure mode, which allows the cosmic web to be seen with unprecedented clarity.
A short demonstrational video of Astera in action can be downloaded here. You will probably have trouble streaming the video (because lots of small moving objects is really bad for video streaming); for the best experience, download the full mp4 and play it locally.
Chris Marsden is a PhD student at the Astronomy group and centre for Next Generation Computer Modelling (NGCM) at Southampton. Chris obtained his undergraduate at the University of Nottingham, and after two years in industry joined the Department of Physics and Astronomy at Southampton in 2017. His PhD explores the co-evolution of supermassive black holes and their host galaxies, with a specific expertise in advanced computational modelling. Chris is currently focussing on the (extremely challenging) modelling of velocity dispersion (the random motions of the stars in an elliptical galaxy) to better understand its mysterious relationship with the galaxy's supermassive black hole. He is also working with Francesco on the creation of cutting-edge AGN mock galaxy catalogues, which are of paramount importance to future missions such as Euclid, Athena and LSST. Chris is the lead developer behind Astera, the project being initially conceved as a simple video showing the extragalactic universe, but rapidly evolving into an ambitions real time rendering using Unreal Engine. He has demonstrated Astera at various events around Southampton, including at a TEDx talk.
Francesco Shankar is Associate Professor in the Southampton Astronomy group. After obtaining his PhD at SISSA, he moved for a postdoc to the Ohio State University, to the Max Planck Institute for Astrophysics as an Alexander von Hulmboldt Fellow, and then to the Observatoire de Paris as a Marie Curie Fellow. He then joined the Department of Physics and Astronomy at Southampton in 2013. His research revolves around the theoretical modelling of galaxies, their central supermassive black holes, and their host dark matter haloes. He pioneered in the phenomenological modelling of galaxies and black holes based on a combination of abundance matching and continuity equation techniques. He has now started a group in extra-galactic astronomy aimed at specifically constraining the evolutionary channels of early-type, bulged galaxies and supermassive black holes via advanced semi-empirical models. The increasing quantity of future data in extra-galactic Astronomy will have to be paralleled by fast modelling. The extreme flexibility and accuracy make semi-empirical models ideal tools to create full test catalogues for fast predictions and comparisons to data.