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PhD Positions in gas accretion and galactic winds

Embedding: This project is part of the ERC Advance Grant project "FLOWS": Gas flows in and out of galaxies: solving the cosmic baryon cycle

Group: The FLOWS group will consist of 3 PhD students, 2 postdocs and the PI

PI: Prof. F. Fraternali

Collaborators: Prof. K. Rubin (San Diego State University, USA) and Prof. F. Marinacci (University of Bologna, Italy)

Scientific background


The majority of matter in the Universe is in the form of gas, found in galaxies and their surrounding environments. Gas flows, including accretion and ejection, play a crucial role in the growth, star formation, and overall properties of galaxies. However, our understanding of these gas flows is limited. Observationally, we have gathered a significant amount of data on gas in and outside of galaxies, but the interpretation is uncertain. Theoretical models also lack a clear understanding of how large-scale gas flows relate to gas accretion onto galaxies and the effectiveness of ejective feedback in removing gas. This project aims to address these gaps in knowledge by investigating all gas flows and incorporating observations into a coherent physical picture.

PhD 1.  Cool gas flows in the circum-galactic medium

In this PhD project, the focus will be on investigating the properties of the cool circumgalactic medium (CGM) surrounding star-forming galaxies over cosmic time. This will be achieved through the analysis of absorption-line observations towards quasars (QSOs). The primary objective is to determine the direction of gas flows and quantify the flow rates at various locations within the CGM. To accomplish this, we will use a novel approach that combines the advantages of ultra-high-resolution (UHR) magneto-hydrodynamical simulations (Fig. 1) with global CGM-scale models, resulting in the development of simulation-informed analytic models (SIAMs).

The initial step involves constructing a comprehensive library of UHR simulations, which will simulate the movement of clouds and filaments through the hot corona under different initial conditions. These conditions include variations in cloud mass, size, metallicities, density, and temperature of the hot gas. The simulations will incorporate various physical processes such as radiative cooling, the influence of the UV background, thermal conduction, magnetic fields, external gravity, and self-gravity. To cover the parameter space adequately, we estimate that approximately 300 simulations will be necessary.

The SIAMs we develop will be applicable to cosmological inflow and outflows resulting from galactic winds. Additionally, alternative scenarios such as stripping from satellite galaxies and condensation in the corona will also be considered. The behaviour of the CGM clouds in these models will be entirely determined by the UHR simulations. We will generate mock realisations based on these models, which will then be treated as "observed" absorption features. To infer the parameters governing the gas flow, we will employ a Markov Chain Monte Carlo (MCMC) approach, simultaneously fitting the data from tens of galaxies. We will utilise data from various surveys, including COS-GASS (Borthakur+ 2015), CGM2 (Wilde+ 2021), and others (Urbano Stawinski+, in prep.), which provide information on the absorption features surrounding thousands of galaxies within the redshift range of 0 ≤ z ≤ 3.5. Both hydrogen and metal lines will be considered in our analysis.

Plan of the work.
Year 1: starting to run the UHR simulations and development of the SIAM (1 paper)

Year 2: application of the SIAMs to low-z observations (1 paper)

Year 3: application of the SIAMs across cosmic time and determination of inflow and outflow rates within the CGM for galaxies of varying masses (2 papers) 

Year 4: exploration of the role played by alternative scenarios (1 paper) and release to the community of the library of UHR simulations depicting the behaviour of CGM clouds


Figure 1. Temperature slice of a magneto-hydrodynamical simulation of a cloud moving (along x) through the hot CGM. The magnetic field is initially perpendicular to the motion and the simulation also includes radiative cooling and anisotropic thermal conduction.  All gas below 20000 K has been coloured dark blue, gas above a million degree is in red. From Kooij et al. (2021).

PhD 2. Dissecting galactic winds

Galactic winds, powered by supernova explosions and active galactic nuclei, are thought to play critical roles in shaping several properties of galaxies, including their stellar mass and scaling relations. However, the properties of the gas outflows produced by galactic winds remain largely undetermined and the theoretical models poorly constrained. This PhD project aims to determine these properties, such as the mass loading factor, with a new methodology applied to emission-line observations of both ionised and neutral gas over cosmic time.

Previous research in this field has primarily relied on fitting individual line profiles with multiple Gaussian components or selecting specific regions in 2D kinematic maps. Our approach, instead, will be groundbreaking as we intend to develop 6D models of biconical galactic winds (comprising of 3 positions and 3 velocities). These models will then be projected along a line of sight to generate 3D mock emission-line datacubes (Fig. 2), which can be directly compared with actual data using an MCMC method and our dedicated computer cluster. By utilizing the information contained within the datacubes, we will be able to differentiate between rotating discs and winds, and simultaneously fit both a wind and a rotating disc, which is not feasible using 1D or 2D methods.

Initially, we will apply our 3D software to datacubes obtained from nearby starburst galaxies, utilizing ionised gas as well as cooler tracers. These datacubes will be sourced from studies such as Reichardt Chu et al. (2022). Concurrently, we will also utilize publicly available hydrodynamical cosmological simulations (e.g., Wetzel et al. 2022) and isolated-galaxy simulations (e.g., Marinacci et al. 2019) to construct mock datacubes before applying our software. Subsequently, our focus will shift towards high-redshift main-sequence galaxies, where we will analyse optical rest-frame emission-line data (specifically Ha and [OIII]) as well as ALMA data. Numerous observations are already present in archives. Additionally, forthcoming data from the JWST and ERIS will also be incorporated. 

Plan of the work.

Year 1: Develop a 3D modelling software to study galactic winds and test it on mock datacubes from idealised hydrodynamical simulations and on nearby starburst galaxies (1 paper).

Year 2: Expand the 3D software including  tests on cosmological simulations from which we will generate mock data cubes.

Year 3: Transition to high-z main-sequence galaxies and apply the 3D software to optical rest-frame emission-line data, including Ha and [OIII], as well as ALMA data (2 papers).

Year 4: Consolidate findings and release the 3D modeling software to the scientific community; provide outflow rate measurements for local starburst and high-z galaxies (1 paper).


Figure 2. 3D rendering of an emission-line (HI) datacube and a rotating-disc model obtained with 3DBarolo that has been fitted to the data. The green emission, not reproduced by the model, is outflowing gas. This type of emission will be reproduced by our new software developed by in PhD project.

To apply for one or both positions go to:


Borthakur, S., Heckman, T., Tumlinson, J., Bordoloi, R., Thom, C., Catinella, B., Schiminovich, D., Davé, R., Kauffmann, G., Moran, S. M., and Saintonge, A. 2015, ApJ, 813, 46

Kooij, R., Grønnow, A., and Fraternali, F. 2021, MNRAS, 502, 1263
Marinacci, F., Sales, L. V., Vogelsberger, M., Torrey, P., and Springel, V. 2019, MNRAS, 489, 4233

Reichardt Chu, B., Fisher, D. B., Nielsen, N. M., Chisholm, J., Girard, M., Kacprzak, G. G., Bolatto, A., Herrera-Camus, R., Sandstrom, K., Li, M., et al. 2022, MNRAS, 511, 5782

Wetzel, A., Hayward, C. C., Sanderson, R. E., Ma, X., Angles-Alcazar, D., Feldmann, R., Chan, T. K., El-Badry, K., Wheeler, C., Garrison-Kimmel, S., Nikakhtar, F., et al. P. F. 2022

Wilde, M. C., Werk, J. K., Burchett, J. N., Prochaska, J. X., Tchernyshyov, K., Tripp, T. M., Tejos, N., Lehner, N., Bordoloi, R., O'Meara, J. M., and Tumlinson, J. 2021, ApJ, 912, 9

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