The origin of the H α line profiles in simulated disc galaxies

Timmy Ejdetjärn, Oscar Agertz, Göran Östlin, Martin P Rey, Florent Renaud

Research output: Contribution to journalArticlepeer-review

Abstract

Observations of ionized H αgas in high-redshift disc galaxies have ubiquitously found significant line broadening, σH α∼10 -100 km s-1 . To understand whether this broadening reflects gas turbulence within the interstellar medium (ISM) of galactic discs, or arises from out-of-plane emission in mass-loaded outflows, we perform radiation hydrodynamic simulations of isolated Milky Way-mass disc galaxies in a gas-poor (low-redshift) and gas rich (high-redshift) condition and create mock H αemission line profiles. We find that the majority of the total (integrated) H αemission is confined within the ISM, with extraplanar gas contributing ∼45 per cent of the extended profile wings ( v z ≥200 km s-1 ) in the gas-rich galaxy. This substantiates using the H αemission line as a tracer of mid-plane disc dynamics. We investigate the relative contribution of diffuse and dense H αemitting gas, corresponding to diffuse ionized gas (DIG; ρ ≲ 0 . 1 cm -3 , T ∼8 000 K) and H II regions ( ρ ≳ 10 cm -3 , T ∼10 000 K), respectively, and find that DIG contributes f DIG ≲ 10 per cent of the total L H α. Ho we ver, the DIG can reach upwards of σH α∼60 -80 km s-1 while the H II regions are much less turbulent σH α∼10 -40 km s-1 . This implies that the σH αobserved using the full H αemission line is dependent on the relative H αcontribution from DIG/H II regions and a larger f DIG would shift σH αto higher v alues. Finally, we sho w that σH αevolves, in both the DIG and H II regions, with the galaxy gas fraction. Our high-redshift equi v alent galaxy is roughly twice as turbulent, except for in the DIG which has a more shallow evolution.

Original languageEnglish
Pages (from-to)135-150
Number of pages16
JournalMonthly Notices of the Royal Astronomical Society
Volume534
Issue number1
Early online date9 Sept 2024
DOIs
Publication statusPublished - 1 Oct 2024

Data Availability Statement

The data underlying this article will be shared on reasonable request to the corresponding author.

Acknowledgements

The computations and data storage were enabled by resources provided by LUNARC – The Centre for Scientific and Technical Computing at Lund University. OA acknowledges support from the Knut and Alice Wallenberg Foundation, and from the Swedish Research Council (grant 2019–04659). MPR is supported by the Beecroft Fellowship funded by Adrian Beecroft. FR acknowledges support provided by the University of Strasbourg Institute for Advanced Study (USIAS), within the French national programme Investment for the Future (Excellence Initiative) IdEx-Unistra.

Simulation outputs were analysed using tools from the YT project (Turk et al. 2011), numpy (Harris et al. 2020), and matplotlib for python (Hunter 2007).

Funding

The computations and data storage were enabled by resources provided by LUNARC \u2013 The Centre for Scientific and Technical Computing at Lund University. OA acknowledges support from the Knut and Alice Wallenberg Foundation, and from the Swedish Research Council (grant 2019\u201304659). MPR is supported by the Beecroft Fellowship funded by Adrian Beecroft. FR acknowledges support provided by the University of Strasbourg Institute for Advanced Study (USIAS), within the French national programme Investment for the Future (Excellence Initiative) IdEx-Unistra. The computations and data storage were enabled by resources provided by LUNARC -The Centre for Scientific and Technical Computing at Lund Uni versity. OA ackno wledges support from the Knut and Alice Wallenberg Foundation, and from the Swedish Research Council (grant 2019-04659). MPR is supported by the Beecroft Fellowship funded by Adrian Beecroft. FR acknowledges support provided by the University of Strasbourg Institute for Advanced Study (USIAS), within the French national programme Investment for the Future (Excellence Initiative) IdEx-Unistra. Simulation outputs were analysed using tools from the YT project (Turk et al. 2011), NUMPY (Harris et al. 2020), and MATPLOTLIB for PYTHON (Hunter 2007).

FundersFunder number
Vetenskapsrådet2019–04659

    Keywords

    • ISM: evolution
    • ISM: kinematics and dynamics
    • galaxies: disc
    • galaxies: star formation
    • methods: numerical
    • turbulence

    ASJC Scopus subject areas

    • Astronomy and Astrophysics
    • Space and Planetary Science

    Fingerprint

    Dive into the research topics of 'The origin of the H α line profiles in simulated disc galaxies'. Together they form a unique fingerprint.

    Cite this