Simulating the X-ray emission of hot gas in groups and clusters
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Date
31/03/2022Author
Robson, Dylan
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Abstract
As some of the largest gravitationally bound objects in the Universe, galaxy groups
and clusters provide a unique laboratory for testing models of cosmology and galaxy
evolution. While many of the basic properties of halos are determined by the
dissipationless dark matter component, the baryonic components that govern the
appearance of the visible matter such as the galaxies and the virialised hot gas, are
less well understood. As such the co-evolution of galaxies, gas, and black holes within
groups and clusters can help us examine galaxy evolution. By leveraging the benefits
of simulations we can closely investigate this evolution and the effects of feedback.
SIMBA is a cosmological hydrodynamical simulation run using the GIZMO code, that
utilises a novel approach to black hole growth and feedback. Deviations of the X-ray scaling relations within SIMBA from self-similarity give us insight into how the
implemented feedback affects halo evolution. It is then possible to determine more
specifically where feedback is altering halos through their X-ray profiles. Through
this work into the global X-ray properties of halos within SIMBA I have established
a baseline from which to start investigating the evolution of individual halos. Tracing
halos back through time allows us to pinpoint the moments, and events, which lead to
significant changes both in global X-ray properties, and the finer details of the X-ray
profiles. While the initial work was done using X-rays generated through PYGAD,
further work was achieved through the combination of pyXSIM, SOXS telescope
simulator, and XSPEC, to generate mock observations and allow for the more direct
comparison of simulations to observations. This ability to accurately create mock
observations from past telescopes such as Chandra aptly leads to the application of
these tools towards simulating observations for future X-ray telescope projects such as
Athena. As such we move from using these tools to validate the simulation, to using
the simulations to make predictions.