The evolution of the dust and gas content in galaxies
Notice bibliographique
Résumé
We use deep Herschel observations taken with both PACS and SPIRE imaging cameras to estimate the dust mass of a sample of galaxies extracted from the GOODS-S, GOODS-N and the COSMOS fields. We divide the redshift–stellar mass (Mstar)–star formation rate (SFR) parameter space into small bins and investigate average properties over this grid. In the first part of the work we investigate the scaling relations between dust mass, stellar mass and SFR out to z = 2.5. No clear evolution of the dust mass with redshift is observed at a given SFR and stellar mass. We find a tight correlation between the SFR and the dust mass, which, under reasonableassumptions, is likely a consequence of the Schmidt-Kennicutt (S-K) relation. The previously observed correlation between the stellar content and the dust content flattens or sometimes disappears when considering galaxies with the same SFR. Our finding suggests that most of the correlation between dust mass and stellar mass obtained by previous studies is likely a consequence of the correlation between the dust mass and the SFR combined with the main sequence, i.e., the tight relation observed between the stellar mass and the SFR and followed by the majority of star-forming galaxies. We then investigate the gas content as inferred from dust mass measurements. We convert the dust mass into gas mass by assuming that the dust-to-gas ratio scales linearly with the gas metallicity (as supported by many observations). For normal star-forming galaxies (on the main sequence) the inferred relation between the SFR and the gas mass (integrated S-K relation) broadly agrees with the results of previous studies based on CO measurements, despite the completely different approaches. We observe that all galaxies in the sample follow, within uncertainties, the same S-K relation. However, when investigated in redshift intervals, the S-K relation shows a moderate, but significant redshift evolution. The bulk of the galaxy population at z ~ 2 converts gas into stars with an efficiency (star formation efficiency, SFE = SFR/Mgas, equal to the inverse of the depletion time) about 5 times higher than at z ~ 0. However, it is not clear what fraction of such variation of the SFE is due to an intrinsic redshift evolution and what fraction is simply a consequence of high-z galaxies having, on average, higher SFR, combined with the super-linear slope of the S-K relation (while other studies find a linear slope). We confirm that the gas fraction (fgas = Mgas/(Mgas + Mstar)) decreases with stellar mass and increases with the SFR. We observe no evolution with redshift once Mstarand SFR are fixed. We explain these trends by introducing a universal relation between gas fraction, stellar mass and SFR that does not evolve with redshift, at least out to z ~ 2.5. Galaxies move across this relation as their gas content evolves across the cosmic epochs. We use the 3D fundamental fgas–Mstar–SFR relation, along with the evolution of the main sequence with redshift, to estimate the evolution of the gas fraction in the average population of galaxies as a function of redshift and as a function of stellar mass: we find that Mstar ≳ 1011 M⊙ galaxies show the strongest evolution at z ≳ 1.3 and a flatter trend at lower redshift, while fgas decreases more regularly over the entire redshift range probed in Mstar ≲ 1011 M⊙ galaxies, in agreement with a downsizing scenario.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».