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| Funder | Science and Technology Facilities Council |
|---|---|
| Recipient Organization | University of Oxford |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Mar 30, 2028 |
| Duration | 1,277 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2929501 |
populations (if any), trace the relics' internal dynamics and the distributions of their luminous and dark matter. Hence, their first practical task in year 1, will be to work with a very small sample of 3 relics from the E-INSPIRE sample for which spatially resolved spectroscopy is available (MaNGA).
The student will learn how open and read a datacube, how to analyse the line-of-sight velocity distribution and the stellar populations of the galaxy using the ppxf code, developed by the co-supervisor Prof. Michele Cappellari. Benefitting from the co-supervisor experience, who is a world-wide expert in this field, the student will model the velocity
dispersion profiles using spherical isotropic Jeans equations to estimate the dynamical mass within the effective radius and put constraints on the dark matter fraction and distribution. They will moreover perform spatially resolved spectroscopic stellar population analysis, using the same techniques developed for the INSPIRE data, but extended to spatiallyresolved
data. They will obtain spatial profiles for age, metallicity, and single element abundance, ultimately confirming that the great majority of stars have been formed via a single high-z star formation burst. At the same time, they will learn how to navigate archival publicly available data to look for photometric fluxed in different wavelength (UV, IR, etc).
This will be incredibly helpful to further characterise the stellar population, in particular, searching for a sub-percental star formation, which has recently been reported in the innermost region of very massive galaxies as well in a relic in the local Universe Salvador- Rusiñol, et al., 2022, MNRAS, 515, 4514; 2021, MNRAS, 500, 3368; 2020, Nature Astronomy,
4, 252). At least one scientific publication (under the E-INSPIRE umbrella) is foreseen for this part of the project. Moreover, with a high-risk, high-gain philosophy, in the future, within the E-INSPIRE team, we plan to apply for a ESO LP to obtain high-resolution, spatially resolved MUSE data on the
most interesting objects found so far within E-INSPIRE, pushing the performance of the instrument to its limits. Enlarging the number of galaxies for which spatially resolved information is available is crucial to investigate possible correlations between the structural, kinematical and dynamical characteristics, the environment and the star formation
histories. In case the proposal will not be successful, we will investigate, together with the student, which will participate in all phases of the proposal hence gaining very useful skills for their future career, further possibilities to acquire spatially resolved data. Having characterised the internal structure and spatially-resolved populations of observed
relics, the student will try to dig into the formation mechanisms that act at high-z and form red nuggets, as well as on the cosmic evolution of these incredibly dense and compact systems. Firstly, they will use cosmological hydrodynamical simulations to identify simulated relics at low-z (ultra-massive and compact galaxies with small sizes and a very high fraction
of "in-situ" mass) and follow their evolution back in time, until their first mass assembly. The student will therefore be able to quantify the fundamental physical parameters of relic galaxies at each epoch in order to unravel the formation scenario and cosmic evolution of these extremely compact, passive, and massive objects with the goal of understanding the
conditions that allowed them to survive pristine to the present day. This part of the project has the potential to produce two papers. The first one will be based on simulations only, indeed tracing simulated relics across cosmic time. The second will instead compare the prediction on number densities in different redshift bins from
simulations with the observational results obtained within E-INSPIRE in the same redshift window
University of Oxford
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