Abstract
The complexity and accuracy of current and future "precision cosmology" observational campaigns has made it essential to develop an efficient technique for directly combining simulation and observational data sets to determine cosmological and model parameters, a procedure we term "calibration." Once a satisfactory calibration of the underlying cosmological model is achieved, independent predictions for new observations become possible. For this procedure to be effective, robust characterization of the uncertainty in the calibration process is highly desirable. In this Letter we describe a statistical methodology that can achieve both of these goals. An application example based around dark matter structure formation simulations and a synthetic mass power spectrum data set is used to demonstrate the approach.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
