From seagull to hummingbird: New diagnostic methods for resolving galaxy activity

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985815%3A_____%2F25%3A00616749" target="_blank" >RIV/67985815:_____/25:00616749 - isvavai.cz</a>

Výsledek na webu

<a href="https://hdl.handle.net/11104/0365442" target="_blank" >https://hdl.handle.net/11104/0365442</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1051/0004-6361/202451323" target="_blank" >10.1051/0004-6361/202451323</a>

Jazyk výsledku

angličtina

Název v původním jazyce

From seagull to hummingbird: New diagnostic methods for resolving galaxy activity

Popis výsledku v původním jazyce

Context. One of the principal challenges in astrophysics involves the classification of galaxies based on their activity. Currently, the characterization of galactic activity usually requires multiple diagnostics to fully cover the diverse spectrum of galaxy activity types. Additionally, the presence of multiple sources of excitation with similar observational signatures hinders the exploration of the activity of a galaxy. Aims. In this study our objective is to develop an activity diagnostic tool that addresses the degeneracy inherent in the existing emission line diagnostics by identifying the underlying excitation mechanisms of the principal components of a mixed-activity galaxy (star formation, active nucleus, or old stellar populations) and identifying the dominant ones. Methods. We utilized the random forest machine-learning algorithm, trained on three primary activity classes: star-forming, active galactic nucleus (AGN), and passive, these classes represent the three key gas excitation mechanisms. This diagnostic relies on four discriminating features: the equivalent widths of three spectral lines, [O III] lambda 5007, [N II] lambda 6584, and H alpha, along with the D4000 continuum break index. Results. We find that this classifier achieves almost perfect performance scores in the principal activity classes. In particular, the achieved overall accuracy is similar to 99%, while the recall scores are similar to 100% for star-forming, similar to 98% for AGN, and similar to 99% for passive. The nearly perfect scores achieved enable the decomposition of mixed-activity classes into the three primary gas excitation mechanisms with high confidence, thereby resolving the degeneracy inherent in current activity classification methods. Furthermore, we find that our classifier scheme can be simplified to a two-dimensional diagnostic diagram of D4000 index versus the log10(EW([O III])2) line without significant loss of its diagnostic power. Conclusions. We introduce a diagnostic capable of classifying galaxies based on their primary gas excitation mechanisms. Simultaneously, it can deconstruct the activity of mixed-activity galaxies into these principal components. This diagnostic encompasses the entire range of galaxy activity. Additionally, the D4000 index serves as a valuable indicator for resolving the degeneracy among various activity components by estimating the age of the stellar populations within a galaxy.

Název v anglickém jazyce

From seagull to hummingbird: New diagnostic methods for resolving galaxy activity

Popis výsledku anglicky

Context. One of the principal challenges in astrophysics involves the classification of galaxies based on their activity. Currently, the characterization of galactic activity usually requires multiple diagnostics to fully cover the diverse spectrum of galaxy activity types. Additionally, the presence of multiple sources of excitation with similar observational signatures hinders the exploration of the activity of a galaxy. Aims. In this study our objective is to develop an activity diagnostic tool that addresses the degeneracy inherent in the existing emission line diagnostics by identifying the underlying excitation mechanisms of the principal components of a mixed-activity galaxy (star formation, active nucleus, or old stellar populations) and identifying the dominant ones. Methods. We utilized the random forest machine-learning algorithm, trained on three primary activity classes: star-forming, active galactic nucleus (AGN), and passive, these classes represent the three key gas excitation mechanisms. This diagnostic relies on four discriminating features: the equivalent widths of three spectral lines, [O III] lambda 5007, [N II] lambda 6584, and H alpha, along with the D4000 continuum break index. Results. We find that this classifier achieves almost perfect performance scores in the principal activity classes. In particular, the achieved overall accuracy is similar to 99%, while the recall scores are similar to 100% for star-forming, similar to 98% for AGN, and similar to 99% for passive. The nearly perfect scores achieved enable the decomposition of mixed-activity classes into the three primary gas excitation mechanisms with high confidence, thereby resolving the degeneracy inherent in current activity classification methods. Furthermore, we find that our classifier scheme can be simplified to a two-dimensional diagnostic diagram of D4000 index versus the log10(EW([O III])2) line without significant loss of its diagnostic power. Conclusions. We introduce a diagnostic capable of classifying galaxies based on their primary gas excitation mechanisms. Simultaneously, it can deconstruct the activity of mixed-activity galaxies into these principal components. This diagnostic encompasses the entire range of galaxy activity. Additionally, the D4000 index serves as a valuable indicator for resolving the degeneracy among various activity components by estimating the age of the stellar populations within a galaxy.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10308 - Astronomy (including astrophysics,space science)

Projekt

<a href="/cs/project/EF18_053%2F0016972" target="_blank" >EF18_053/0016972: Podpora mezinárodní spolupráce v astronomii</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Astronomy & Astrophysics

ISSN

0004-6361

e-ISSN

1432-0746

Svazek periodika

693

Číslo periodika v rámci svazku

Jan.

Stát vydavatele periodika

FR - Francouzská republika

Počet stran výsledku

19

Strana od-do

A95

Kód UT WoS článku

001406577300008

EID výsledku v databázi Scopus

2-s2.0-85214679024