Skip to main content

Research Repository

Advanced Search

Impact of observational selection functions on simulated age and metallicity distributions

Atkin, Daniel


Daniel Atkin


Brad K. Gibson

C. Gareth (Christopher Gareth) Few


I use a novel approach to close the gap between observations and simulations of stellar abundance and ages by comparing observational data from Gaia-ESO 4th release (GES-iDR4) with that of a Milky Way-like galaxy simulation. The simulation is brought into the observational plane by applying selection functions and observational uncertainties to simulation data. I extend this comparison by performing a second observational transformation on the same simulated galaxy using the selection criteria and uncertainties of the RAVE survey. The methodology used here employs a kernel density estimation to apply observational error and weighting to the distribution functions. I find that the simulated [Mg/Fe](from here [] denotes a solar normalised metallicity) distribution is more strongly affected by the application of the Gaia-ESO observational uncertainty than [Fe/H]. The Gaia-ESO selection functions cause both [Fe/H] and [Mg/Fe] to become more metal-rich, which is mainly due to the J-magnitude cut. While the transformed [Mg/Fe] distribution is a better fit to the GES-iDR4 data than the unaltered simulation, the simulated [Fe/H] distribution does not improve. The age distribution of the simulation evolves into a much younger distribution than the observation and unaltered simulation as the selection functions, particularly the magnitude limits, removes old stars. In the age-metallicity plane the 2D kernel density estimate achieves a much better fit to the observations than the unaltered simulation especially for [Fe/H]. The simulated [Fe/H] becomes significantly more metal-rich when RAVE selection criteria are employed compared to the Gaia-ESO selection limits. The [Mg/Fe] distribution is less affected due to lower uncertainty from the RAVE survey and becomes slightly less [Mg/Fe]-rich than the unaltered simulation. Although the transformed simulations are not perfect fits to the observations in every case, the purpose of the study is not to test the accuracy of the simulation but to examine how the selection functions and uncertainties change the simulations and why. This work is an advancement on previous studies since the replacement of the initial spatial cut with a more observationally relevant magnitude cut allows bright distant stars to be included in the distribution. Furthermore, the use of a kernel density estimate to implement observational uncertainty on stars in order to create a continuous distribution is more statistically accurate than a stochastic scattering and can be undertaken with a smaller number of simulated star particles.


Atkin, D. (2019). Impact of observational selection functions on simulated age and metallicity distributions. (Thesis). University of Hull. Retrieved from

Thesis Type Thesis
Deposit Date Feb 21, 2020
Publicly Available Date Feb 23, 2023
Keywords Physics
Public URL
Additional Information Department of Physics and Mathematics, The University of Hull
Award Date Mar 1, 2019


Thesis (2.2 Mb)

Copyright Statement
© 2019 Atkin, Daniel. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.

You might also like

Downloadable Citations