Understanding Bayesian stellar distance and stellar parameter estimation

Abstract: The consensus in the field is that we have a pretty good understanding of the physics behind star formation and evolution. So far, the models that have been created characterize the different collections of stars in our Milky Way galaxy with decent accuracy, and they have allowed for humanity to obtain insights into how our universe evolved. However, the author believes that our current techniques and theory that go into such models might be biased or slightly flawed. A simulated model of the Milky Way is used to generate virtual stars whose properties are known. These stars are then analysed using the current most up-to-date techniques, and the obtained values for the various stellar properties are compared with the already known values. Non-trivial evidence is obtained that we are indeed systematically over-/underestimating the values of these parameters by almost 1 standard deviation in most cases. Some possible ideas about why this might be the case are explored within this document.