PHANGS-ML: Dissecting multiphase gas and dust in nearby galaxies using machine learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985815%3A90106%2F24%3A00617609" target="_blank" >RIV/67985815:90106/24:00617609 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.3847/1538-4357/ad39e5" target="_blank" >https://doi.org/10.3847/1538-4357/ad39e5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3847/1538-4357/ad39e5" target="_blank" >10.3847/1538-4357/ad39e5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

PHANGS-ML: Dissecting multiphase gas and dust in nearby galaxies using machine learning

Popis výsledku v původním jazyce

The PHANGS survey uses Atacama Large Millimeter/submillimeter Array, Hubble Space Telescope, Very Large Telescope, and JWST to obtain an unprecedented high-resolution view of nearby galaxies, covering millions of spatially independent regions. The high dimensionality of such a diverse multiwavelength data set makes it challenging to identify new trends, particularly when they connect observables from different wavelengths. Here, we use unsupervised machine-learning algorithms to mine this information-rich data set to identify novel patterns. We focus on three of the PHANGS-JWST galaxies, for which we extract properties pertaining to their stellar populations, warm ionized and cold molecular gas, and polycyclic aromatic hydrocarbons (PAHs), as measured over 150 pc scale regions. We show that we can divide the regions into groups with distinct multiphase gas and PAH properties. In the process, we identify previously unknown galaxy-wide correlations between PAH band and optical line ratios and use our identified groups to interpret them. The correlations we measure can be naturally explained in a scenario where the PAHs and the ionized gas are exposed to different parts of the same radiation field that varies spatially across the galaxies. This scenario has several implications for nearby galaxies: (i) The uniform PAH ionized fraction on 150 pc scales suggests significant self-regulation in the interstellar medium, (ii) the PAH 11.3/7.7 mu m band ratio may be used to constrain the shape of the non-ionizing far-ultraviolet to optical part of the radiation field, and (iii) the varying radiation field affects line ratios that are commonly used as PAH size diagnostics. Neglecting this effect leads to incorrect or biased PAH sizes.

Název v anglickém jazyce

PHANGS-ML: Dissecting multiphase gas and dust in nearby galaxies using machine learning

Popis výsledku anglicky

The PHANGS survey uses Atacama Large Millimeter/submillimeter Array, Hubble Space Telescope, Very Large Telescope, and JWST to obtain an unprecedented high-resolution view of nearby galaxies, covering millions of spatially independent regions. The high dimensionality of such a diverse multiwavelength data set makes it challenging to identify new trends, particularly when they connect observables from different wavelengths. Here, we use unsupervised machine-learning algorithms to mine this information-rich data set to identify novel patterns. We focus on three of the PHANGS-JWST galaxies, for which we extract properties pertaining to their stellar populations, warm ionized and cold molecular gas, and polycyclic aromatic hydrocarbons (PAHs), as measured over 150 pc scale regions. We show that we can divide the regions into groups with distinct multiphase gas and PAH properties. In the process, we identify previously unknown galaxy-wide correlations between PAH band and optical line ratios and use our identified groups to interpret them. The correlations we measure can be naturally explained in a scenario where the PAHs and the ionized gas are exposed to different parts of the same radiation field that varies spatially across the galaxies. This scenario has several implications for nearby galaxies: (i) The uniform PAH ionized fraction on 150 pc scales suggests significant self-regulation in the interstellar medium, (ii) the PAH 11.3/7.7 mu m band ratio may be used to constrain the shape of the non-ionizing far-ultraviolet to optical part of the radiation field, and (iii) the varying radiation field affects line ratios that are commonly used as PAH size diagnostics. Neglecting this effect leads to incorrect or biased PAH sizes.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10308 - Astronomy (including astrophysics,space science)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Astrophysical Journal

ISSN

0004-637X

e-ISSN

1538-4357

Svazek periodika

968

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

37

Strana od-do

24

Kód UT WoS článku

001258533100001

EID výsledku v databázi Scopus

2-s2.0-85195607529