In the coming era of LSST, PanSTARRS, WFIRST, Euclid, ALMA, ELTs, JWST, and other facilities, we want to know: What science can we learn by injecting more astrophysics into mock catalogs, and how can we use mock data to maximize the science output of real data?
This workshop will cover a variety of astronomy topics bound together by their need to mock the universe: strong and weak lensing, stellar streams and Milky Way dynamics, galaxy and star formation, large scale structure, and dust. How do you simulate data? What techniques do you use to check whether you get out what you put in? What do you hope to learn by comparing mock catalogs to real data? How can we best use observations to improve synthetic ones? Are there parts of our fake universes that we should share with the community? How?
As computing resources grow and simulations resolve entire observable universes, it may become possible to simulate every pixel observed in next-generation surveys, many times over. Is this a worthy goal? Where should our simulations and surveys meet in order to learn the most about how our universe works? What are the computing, mathematical, and scientific problems we must overcome to achieve these goals?
We invite contributed talks and posters along the entire continuum of observations to theory, especially those that exploit combinations of fake and real data to constrain astrophysical models, measure cosmological parameters, and determine our cosmic history.
We stress that this workshop is as much for “observers” to discuss how they use mock data, and how real data inform what mock observations should include but don’t, as it is for “theorists” to discuss how they mock the universe.