PhD Position in gas dynamics and galaxy evolution

Title: Accurate gas dynamics of distant galaxies: resolving the controversies

Supervisor: F. Fraternali

Scientific background

Understanding galaxy formation and evolution is one the main quests of modern astrophysics. To this aim, a number of unprecedented observational facilities have been built (e.g. Bacon+ 2010; ALMA partnership 2015) and an impressive theoretical effort has been carried out using sophisticated cosmological hydrodynamical simulations that are run on the World fastest supercomputers (e.g. Schaye+ 2015; Pillepich+ 2018). New detectors and telescopes are capable of observing galaxies at very large distances (high redshift or high-z), which correspond to the earliest epochs of the Universe, when galaxies had just formed. The interpretation of these revolutionary data and thus the possibility to properly constrain models relies on precise measurements. This NWO-funded project will provide this accuracy and precision with the focus on the gas dynamics of high-z galaxies.

Galaxy dynamics can be studied by measuring the Doppler shift of gas emission lines across the electromagnetic spectrum. This allows us to determine the amount of rotation at various radii in a galaxy and to estimate the mass of the, otherwise invisible, dark matter (Fig. 1a). Today we can study gas dynamics of very distant galaxies in a similar way at different wavelengths thanks to facilities like the Very Large Telescope (VLT) or the Atacama Large Millimetre Array (ALMA). In fact, one of the most important results of the last decade was that also very distant galaxies are often rotation dominated (e.g. Forster-Schreiber+ 2009; Jones+ 2017). However, distant galaxies are faint and small and determining their rotation curves is not trivial. This project uses a new technique, developed by the group of F. Fraternali, to overcome these limitations and allow precise measurements back to the very early epochs of galaxy formation. Other than rotation, another property that we will measure precisely is the gas velocity dispersion. This quantifies the turbulence present in the interstellar medium (ISM), which can then be linked to gas accretion, star-formation feedback and the thickness of the gaseous discs (e.g. Glazebrook+ 2013; Wisniowki+ 2015). The amount of rotation in galaxies drives fundamental scaling relations (e.g. Lelli+ 2016, Romanowsky & Fall 2012) and the determination of their evolution with time is a crucial test for formation models (Fig. 1b). 

Figure 1. a) The rotation curve (circular velocity as a function of radius, points) of the nearby dwarf galaxy WLM (Iorio, Fraternali+ 2017) and mass decomposition with stellar and gas discs (which have minor contribution) and two types of dark matter halos (Read+ 2016). b) Prediction of cosmological hydrodynamical simulations for the Tully-Fisher relation at z=1 (blue points and grey curve) and a comparison with observational data (orange diamonds), from Ferrero+ 2017.

Main goals of the project

The first goal is to derive rotation and gas velocity dispersions for galaxies at different redshifts from z~1 to z~6 using a homogeneous state-of-the-art methodology. At z=0, rotation curves derived both with neutral hydrogen (HI) (Fig. 1a) and optical emission lines (e.g. Noordermeer+ 2007) have made key contributions to the characterisation of the dark matter (e.g. Navarro+ 1996; Gentile+ 2005; Read+ 2016), the study of the central potentials (de Blok+ 2001) and the importance of stellar feedback (e.g. Pontzen & Governato 2012). They have had a major impact in the revision of theoretical models to produce more realistic galaxies (e.g. Scannapieco+ 2012; Marinacci+ 2014). However, z=0 is one snapshot of the whole history and going to higher redshift with these studies is of paramount importance.

The second goal is the derivation of the dark matter content in galaxies at these redshifts. To date, there have been only a few pioneering attempts to perform mass decompositions of high-z rotation curves (e.g. Uebler+ 2018) but even the shapes of these curves are a matter of debate (see e.g. Di Teodoro+ 2016 vs Genzel+ 2017). With this project we will obtain reliable mass decompositions of about one hundred high-z galaxies matching, for the first time, the statistics available at z=0.

The third goal is to analyse the resulting scaling relations, in particular the (baryonic) Tully-Fisher (rotation vs baryonic/stellar mass) relation (Tully & Fisher 1977; McGaugh 2005) and the “Fall” (specific angular momentum j vs stellar mass M*) relation (Fall 1983). From the observational point of view the question whether these relations are evolving with z and how is unanswered. Even at z=1, where the measures are relatively easy to obtain, some groups find that the Tully-Fisher relation is consistent with that at z=0 (e.g. Di Teodoro+ 2016; Harrison+ 2017), while others find that it evolves significantly towards higher velocities and/or lower masses (e.g. Tiley+ 2016; Uebler+ 2017). Thus two major improvements are needed: 1) enlarge the sample, 2) apply the same technique to galaxies at z>1. The study of the Fall relation is fundamental for galaxies because 1) specific angular momentum and mass are independent from each other, 2) they are conserved quantities and 3) one of the most important theories of galaxies formation (the tidal torque theory; Peebles 1969) makes clear and testable predictions. Thus it is a key benchmark for galaxy formation models (Posti, Fraternali+ 2018) and extending these investigations to higher z is extremely important to distinguish between different scenarios.

This project will also produce accurate velocity dispersions for a large number of galaxies and for different gas tracers including ionised, neutral and molecular gas. There is a general consensus that gas in high-z galaxies was, on average, more turbulent (higher velocity dispersion) than in local galaxies. However, quantifying the velocity dispersion has proved challenging and current measurements show a large spread with very large values that may be affected by observational biases (Fig. 2b). Our software 3D-Barolo allows us to overcome these biases returning the intrinsic value of the gas velocity dispersion in the disc. This is a key measure to understand the origin of turbulence (e.g. Krumholz & Burkhart 2016).

Figure 2. a) The relation between stellar specific angular momentum (j*) and stellar mass for a sample of galaxy discs at z~1 (squares) compared to that at z=0 (grey band), from Marasco, Fraternali+ 2019. b) The velocity dispersion of the ionised gas versus redshift for various samples of star-forming galaxies, from Di Teodoro+ 2016 and Di Teodoro, Grillo, Fraternali+ 2018. The large red circles are obtained with 3D-Barolo.


During the past years, there has been a revolution in the ways we can study gas dynamics in high-z galaxies. This is thanks to the development of new optical Integral Field Units (IFUs) such as KMOS and MUSE that allow us to detect gas emission lines (e.g. Halpha and [OII]) at high z and large millimetre interferometers, in particular ALMA that, allow us to study CO rotational and the [CII] fine-structure transitions. These data are opening a completely new window on the physics of galaxy formation and changing our view of the early Universe. Unfortunately, all the kinematic data obtained for high-z galaxies are at low angular resolution, often at low spectral resolution (typically s>30 km/s for IFUs) and at low signal to noise (S/N) because of the distance.To deal with these data, the most reliable approach is to model the emission of the galaxy in 3D producing artificial data to compare to the real data (e.g. Swaters 1999; Josza+ 2007). The group of F. Fraternali has developed the most advanced and most used of such software: 3D-Barolo (DiTeodoro & Fraternali 2015). The exploitation of this software at high-z is at the core of my methodology. For details about the software and its performance see here.

Once the rotation velocity of the gas is determine and corrected for pressure support (Iorio, Fraternali+ 2017), we obtain the circular speed (goal 1). This is a measure of the gravitation potential and so allows us to infer the distribution of dark matter (goal 2) and enters the Tully-Fisher relation (goal 3). The last two goals require the use of data at different wavelengths, in particular optical/IR data for the distribution of the stellar light. These data are available for most of the galaxies that we will study as they are often part of large programmes, where the fields have been targeted because of the availability of HST imaging. Examples are the COSMOS, the UDS or the GOODS fields, observed by KMOS and MUSE. Spatially resolved SED fitting or similar techniques will be used to extract density profiles (DiTeodoro, Grillo, Fraternali+ 2018; Marasco, Fraternali+ 2019). At z>3, excellent data will be available after the launch of James Webb Space Telescope (JWST).


ALMA partnership 2015, ApJL, 808L, 3

Bacon, R.; et al. 2010, SPIE, 7735E, 08

de Blok E.; et al. 2001, ApJL, 552, 23

Di Teodoro; E. M. & Fraternali, F. 2015, MNRAS, 451, 3021

Di Teodoro, E. M.; Fraternali, F.; Miller, S. H. 2016, A&A, 594, A77

Di Teodoro, E. M.; Grillo, C.; Fraternali, F.; et al. 2018, MNRAS, 476, 804 Fall, S. M. 1983, IAUS, 100, 391

Ferrero, I.; et al. 2017, MNRAS, 464, 4736

Forster Schreiber, N. M.; et al. 2009, ApJ, 706, 1364

Gentile, G.; et al. 2005, ApJL, 634, 145

Genzel, R.; et al. 2017, Nature, 543, 397

Glazebrook, K. 2013, PASA, 30, 56

Harrison, C. M.; et al. 2017, MNRAS, 467, 1965

Iorio, G.; Fraternali F.; et al. 2017, MNRAS, 466, 4159

Krumholz, M. R. & Burkhart, B. 2016, MNRAS, 458, 1671

Jones, G.; et al. 2017, ApJ, 850, 180

Jozsa, G. I. G.; et al. 2007, A&A, 468, 731

Lelli, F.; et al. 2016, ApJ, 816, L14

Marasco, A.; Fraternali, F; et al. 2019, A&A Letters, 621, L6

Marinacci, F.; et al. 2014, MNRAS, 437, 1750

McGaugh, S. S. 2005, ApJ, 632, 859

Navarro, J.; et al. 1996, ApJ, 462, 563

Noordermeer, E.; et al. 2007, MNRAS, 376, 1513

Peebles, P. J. E. 1969, ApJ, 155, 393

Pillepich, A; et al. 2018, MNRAS, 473, 4077

Pontzen, A. & Governato, F. 2012, MNRAS, 421, 3464

Posti, L.; Fraternali, F.; et al. 2018, A&A Letters, 612, L6

Read, J. I.; Iorio, G.; Agertz, O. & Fraternali, F. 2016, MNRAS, 462, 3628

Romanowsky, A. & Fall S.M. 2012, ApJS, 203, 17

Scannapieco, C.; et al. 2012, MNRAS, 423, 1726

Schaye, J., et al. 2015, MNRAS, 446, 521

Swaters, R. A. 1999, Ph.D. thesis, University of Groningen

Tiley, A. L.; 2016, MNRAS, 460, 103

Tully R. B. & Fisher J. R. 1977, A&A, 54, 661

Uebler, H.; et al. 2017, ApJ, 842, 121

Uebler, H.; et al. 2018, ApJ, 854, L24

Wisnioski, E.; et al. 2015, ApJ, 799, 209