The effects of stochasticity on the luminosities of stellar populations are an often neglected but crucial element for understanding populations in the low-mass or the low star formation rate regime. To address this issue, we present SLUG, a new code to "Stochastically Light Up Galaxies." SLUG synthesizes stellar populations using a Monte Carlo technique that properly treats stochastic sampling including the effects of clustering, the stellar initial mass function, star formation history, stellar evolution, and cluster disruption. This code produces many useful outputs, including (1) catalogs of star clusters and their properties such as their stellar initial mass distributions and their photometric properties in a variety of filters, (2) two dimensional histograms of color-magnitude diagrams of every star in the simulation, and (3) the photometric properties of field stars and the integrated photometry of the entire simulated galaxy. After presenting the SLUG algorithm in detail, we validate the code through comparisons with STARBURST99 in the well-sampled regime, and with observed photometry of Milky Way clusters. Finally, we demonstrate SLUG's capabilities by presenting outputs in the stochastic regime. SLUG is publicly distributed through the Web site http://sites.google.com/site/runslug/. © 2012. The American Astronomical Society. All rights reserved.

Da Silva, R., Fumagalli, M., Krumholz, M. (2012). Slug - Stochastically lighting up galaxies. I. Methods and validating tests. THE ASTROPHYSICAL JOURNAL, 745(2), 145 [10.1088/0004-637X/745/2/145].

Slug - Stochastically lighting up galaxies. I. Methods and validating tests

Fumagalli M.;
2012

Abstract

The effects of stochasticity on the luminosities of stellar populations are an often neglected but crucial element for understanding populations in the low-mass or the low star formation rate regime. To address this issue, we present SLUG, a new code to "Stochastically Light Up Galaxies." SLUG synthesizes stellar populations using a Monte Carlo technique that properly treats stochastic sampling including the effects of clustering, the stellar initial mass function, star formation history, stellar evolution, and cluster disruption. This code produces many useful outputs, including (1) catalogs of star clusters and their properties such as their stellar initial mass distributions and their photometric properties in a variety of filters, (2) two dimensional histograms of color-magnitude diagrams of every star in the simulation, and (3) the photometric properties of field stars and the integrated photometry of the entire simulated galaxy. After presenting the SLUG algorithm in detail, we validate the code through comparisons with STARBURST99 in the well-sampled regime, and with observed photometry of Milky Way clusters. Finally, we demonstrate SLUG's capabilities by presenting outputs in the stochastic regime. SLUG is publicly distributed through the Web site http://sites.google.com/site/runslug/. © 2012. The American Astronomical Society. All rights reserved.
Articolo in rivista - Articolo scientifico
galaxies: star clusters: general; galaxies: stellar content; methods: numerical; methods: statistical; stars: formation; techniques: photometric
English
2012
745
2
145
145
open
Da Silva, R., Fumagalli, M., Krumholz, M. (2012). Slug - Stochastically lighting up galaxies. I. Methods and validating tests. THE ASTROPHYSICAL JOURNAL, 745(2), 145 [10.1088/0004-637X/745/2/145].
File in questo prodotto:
File Dimensione Formato  
da_Silva_2012_ApJ_745_145.pdf

accesso aperto

Tipologia di allegato: Publisher’s Version (Version of Record, VoR)
Dimensione 2.89 MB
Formato Adobe PDF
2.89 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/280711
Citazioni
  • Scopus 164
  • ???jsp.display-item.citation.isi??? 156
Social impact