Numerical modelling of the lobes of radio galaxies in cluster environments
By M. Hardcastle, Martin G. H. Krause. 2013
144 citations recorded by the source corpus.
We have carried out two-dimensional, axisymmetric, hydrodynamic numerical modelling of the evolution of radio galaxy lobes. The emphasis of our work is on including realistic hotgas environments in the simulations and on establishing what properties of the resulting radio lobes are independent of the choice of environmental properties and of other features of the models such as the initial jet Mach number. The simulated jet power we use is chosen so that we expect the inner parts of the lobes to come into pressure balance with the external medium on large scales; we show that this leads to the expected departure from self-similarity and the formation of characteristic central structures in the hot external medium. The work done by the expanding radio lobes on the external hot gas is roughly equal to the energy stored in the lobes for all our simulations once the lobes are well established. We show that the external pressure at the lobe midpoint is a reasonable estimate of the internal (lobe) pressure, with only a weak dependence on the environmental parameters: on the other hand, the predicted radio emission from a source of a given physical size has a comparatively strong dependence on the environment in which the lobe resides, introducing an order of magnitude of scatter into the jet power versus radio luminosity relationship. X-ray surface brightness and temperature visualizations of our simulations bear a striking resemblance to observations of some wellstudied radio galaxies.
Subfields: Astronomy and Astrophysics, Nuclear and High Energy Physics
View Paper: https://www.semanticscholar.org/paper/809eef9e4ca971215bee4898ce8aae8a021594a9
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Citations in the corpus
- Radio galaxies and feedback from AGN jets (2020, background): “In practice, this is simplistic, since we know that the radio luminosity for a source of constant jet power must vary not just with time but also with the environment of the radio source (Hardcastle and Krause, 2013) and with redshift, since inverse-Compton losses are redshift-”