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GALEV evolutionary synthesis models - I. Code, input physics and web-interface

Ralf Kotulla, Uta Fritze, Peter Weilbacher, Peter Anders

arXiv:0903.0378v1astro-ph.CO

TL;DR

GALEV addresses the need for evolutionary models that describe stellar populations, galaxies, and their chemical enrichment across metallicities and cosmic time. It presents an interactively accessible implementation combining spectral and chemical evolution, then demonstrates applications from clusters to local and high-redshift galaxies. The models reproduce observed galaxy spectra and broad colour ranges, while remaining limited by their one-zone treatment and unresolved correspondence between spectral and morphological types at high redshift.

  • Problem

    Evolutionary modeling must describe stellar populations and galaxies across metallicities, ages, chemical enrichment, and cosmic time while supporting varied observational applications.

  • Method

    GALEV combines spectral evolution with chemical evolution using metallicity-dependent stellar tracks, yields, atmospheres, lifetimes, and remnant-based ejection rates, delivered through a user-friendly web interface.

  • Results

    GALEV reproduces observed spectra across galaxy spectral types and can describe the full observed colour range of high-redshift field galaxies, including starburst and postburst phases.

  • Takeaways & Limitations

    The models provide user-defined evolutionary predictions for star clusters and diverse galaxy populations in both the local and high-redshift universe.

  • Takeaways & Limitations

    GALEV uses one-zone models without spatial resolution or dynamics, and spectral–morphological correspondence may not hold at high redshift.

Abstract

from arXiv · show

GALEV evolutionary synthesis models describe the evolution of stellar populations in general, of star clusters as well as of galaxies, both in terms of resolved stellar populations and of integrated light properties over cosmological timescales of > 13 Gyr from the onset of star formation shortly after the Big Bang until today. For galaxies, GALEV includes a simultaneous treatment of the chemical evolution of the gas and the spectral evolution of the stellar content, allowing for what we call a chemically consistent treatment: We use input physics (stellar evolutionary tracks, stellar yields and model atmospheres) for a large range of metallicities and consistently account for the increasing initial abundances of successive stellar generations. Here we present the latest version of the galev evolutionary synthesis models that are now interactively available at www.galev.org. We review the currently used input physics, and also give details on how this physics is implemented in practice. We explain how to use the interactive web-interface to generate models for user-defined parameters and also give a range of applications that can be studied using GALEV, ranging from star clusters, undisturbed galaxies of various types E ... Sd to starburst and dwarf galaxies, both in the local and the high-redshift universe.

1 INTRODUCTION

GALEV evolutionary synthesis models combine stellar spectral evolution with detailed chemical evolution across star clusters and galaxies. The latest version broadens access through a customized web interface while retaining simple, one-zone modeling assumptions.

  • GALEV models: GALEV models synthesize stellar populations with arbitrary star-formation histories while tracking chemical evolution of the interstellar medium.The models use the time evolution of stellar populations in the Hertzsprung–Russell diagram alongside chemical-evolution calculations.
  • Applications: Applications span star clusters, normal galaxies from E through Sd, dwarf and starburst galaxies, interacting systems, and high-redshift galaxies.Previous studies also covered galaxy transformation, mergers, and damped Lyman-α absorbers.
  • Web interface: The web interface provides existing star-cluster and galaxy models and lets users generate new models for specific applications.It supports time evolution for comparison with local observations and redshift evolution for galaxies.
  • Model scope: GALEV aims to use few free parameters while predicting many observational properties for comparison with data.This philosophy is implemented in one-zone models without spatial resolution or dynamics.

2 THE GALEV CODE: AN OVERVIEW

The GALEV code models stellar populations and galaxies using evolutionary synthesis, flexible stellar-population assumptions, and chemically consistent enrichment. Its applications include integrated spectra, resolved colour–magnitude diagrams, and metallicity-dependent galaxy evolution.

  • Model inputs: Evolutionary synthesis requires assumptions about the stellar initial mass function, star-formation history, evolutionary tracks or isochrones, and spectral libraries.GALEV supports Salpeter, Kroupa, and Chabrier IMFs, with additional choices customizable.
  • Star clusters: For simple stellar populations, GALEV reproduces observed cluster colours and spectral indices as functions of age and metallicity.Age and metallicity calibrations are valid only at specified metallicities or ages, so extrapolation can mislead.
  • Star clusters: Nebular emission can contribute 50–60% of broad-band flux in young stellar populations, particularly at low metallicity.This contribution makes nebular emission important when interpreting photometry of young populations.
  • Galaxies: Galaxy models combine prescribed star-formation histories and IMFs with evolutionary inputs to match observed colours, spectra, luminosities, abundances, and gas content.The undisturbed galaxy sequence uses spectral types E, S0, Sa, Sb, Sc, and Sd, with Salpeter IMFs extending from 0.1 M⊙ to roughly 70–120 M⊙.
  • Code capabilities: GALEV extends evolutionary synthesis by combining integrated spectral evolution with resolved colour–magnitude diagrams and self-consistent chemical evolution.This treatment accounts for stellar subpopulations with different metallicities within galaxies.
  • Chemical evolution: Chemically consistent modeling uses metallicity-dependent tracks, atmospheres, lifetimes, and yields while increasing the initial abundances of successive stellar generations.Chemical evolution follows many elements and delayed material return from winds, planetary nebulae, and supernovae.
  • Chemical evolution: Coexisting stellar ages and metallicities cause different wavelength regions to be dominated by different stellar subpopulations.This affects metallicity indicators and calibrations based on Hα, [O II], and FUV luminosities.
  • Colour–magnitude diagrams: Synthetic colour–magnitude diagrams can be computed in arbitrary passband combinations to study age–metallicity effects and optimize observations.They support systematic studies of star-formation-history recovery and filter selection.

3 INPUT PHYSICS

GALEV combines metallicity-dependent stellar evolution, stellar atmospheres, gaseous emission, chemical yields, and remnant prescriptions to model evolving stellar populations and galaxies. These inputs capture how metallicity changes stellar spectra, lifetimes, emission, and chemical enrichment.

  • 3.1 Stellar evolutionary tracks and/or isochrones: GALEV uses Padova isochrones at five metallicities and includes the thermally pulsing asymptotic giant branch phase.The metallicity grid spans [Fe/H] = −1.7, −0.7, −0.4, 0.0, and +0.4.
  • 3.1 Stellar evolutionary tracks and/or isochrones: Lower metallicity shifts stellar tracks toward higher luminosities and effective temperatures, producing bluer, more luminous populations with stronger gaseous emission.The combined effects substantially alter galaxy spectra, including colours, luminosities, and line and continuum emission.
  • 3.2 Stellar spectra: GALEV assigns BaSeL stellar-library spectra by metallicity, effective temperature, and surface gravity, with metallicity-driven absorption and line blanketing especially strong in cool stars.For very hot stars above 50,000 K, missing library spectra are approximated with black-body spectra.
  • 3.3 Gaseous emission: lines and continuum: Gaseous emission is computed from ionizing photons and metallicity-dependent line ratios, with 4 Myr spectra spanning five metallicities from 1/50 to 2.5 Z⊙.The extreme metallicities differ by about a factor of 10 in overall emission-line strength; Hα/[N II] is approximately 48 at low metallicity and 7 at solar metallicity.
  • 3.5 Stellar yields: GALEV models chemical enrichment using metallicity-dependent yields for many elements, stellar lifetimes, and remnant-mass prescriptions for black holes, neutron stars, and white dwarfs.For stars with M⋆ ≥ 30 M⊙, the remnant is assigned mBH = 8.0 M⊙, while 30 M⊙ ≥ M⋆ ≥ 6.0 M⊙ produces a neutron star.
  • 3.6 Ejection rates and remnant masses: Main-sequence lifetimes depend on both initial mass and metallicity: low-mass stars live longer at high metallicity, whereas high-mass stars live longer at low metallicity.A 20 M⊙ star has a 10% longer lifetime at Z = 1/10 Z⊙ than at Z = Z⊙.

4 PROGRAM STRUCTURE

GALEV turns age- and metallicity-dependent stellar inputs into population spectra, chemical evolution, and photometric predictions through a staged modeling pipeline. The program interpolates coarse stellar grids and can extend predictions across filters, dust attenuation, and redshift.

  • 4 PROGRAM STRUCTURE: GALEV first convolves each age–metallicity isochrone with the specified IMF, assigns stellar spectra, adds young-population gas emission, and derives gas and metal ejection rates.The isochrone spectra are normalized to an IMF of 1 M⊙ before subsequent population synthesis.
  • 4 PROGRAM STRUCTURE: It then combines isochrone spectra over timesteps according to the star-formation history to compute the chemical and spectral evolution of stellar populations.Older star-formation episodes contribute through integration over previous timesteps.
  • 4 PROGRAM STRUCTURE: The final stage convolves integrated spectra with requested filter functions and applies zero-points to produce absolute magnitudes, optionally as functions of redshift and dust extinction.A cosmological model can convert galaxy age into redshift and include intergalactic attenuation.
  • 4.1 Interpolation: To match isochrone points to stellar libraries, GALEV interpolates spectra in effective temperature and surface gravity while weighting them by stellar luminosity.The interpolation brackets the required parameters with up to four spectra and uses Johnson-V or Bessell-H-band luminosities depending on stellar temperature.
  • 4.2 Interpolation between isochrones: For ages and metallicities between available isochrones, GALEV interpolates logarithmically in age and linearly in metallicity expressed as log(Z) ∼ [Fe/H].This maps the coarse isochrone grid onto the finer grid required for galaxy evolution.

5 CALIBRATION OF THE GALEV MODELS AND COMPARISON TO OBSERVATIONS

GALEV models reproduce a broad set of observed star-cluster and galaxy properties while simultaneously predicting spectral, photometric, chemical, and gas evolution. Their calibration is strongest within the empirical regimes represented by the comparisons, with explicit limitations for simplified histories, missing physics, and extrapolation beyond local galaxy types.

  • Model calibration: GALEV predicts absolute time evolution of spectra, luminosities, colours, gas content, and chemical enrichment without a posteriori normalization.The predictions require a chosen IMF, mass limits, and total system mass.
  • Star clusters: 12–13 Gyr SSP colours from U through K agree very well with observed colours of M31 and Milky Way globular clusters at their metallicities.Small blue-band deviations are attributed to Blue Straggler stars not included in standard single-star isochrones.
  • Star clusters: GALEV reproduces old-cluster colour–metallicity and Lick-index calibrations within their empirical ranges, but these relations are age-dependent and should not be extrapolated indiscriminately.The colour relations are supported for old clusters over −2.3 ⩽ [Fe/H] ⩽ −0.5, while metal-sensitive indices also depend on age.
  • Galaxies: Models for spectral types E through Sd match observed gas fractions, colours, spectra, metallicities, and star-formation rates reasonably well.Examples include predicted (B−V) colours from 0.86 for E to 0.43 for Sd and spectra reproducing absorption and emission features despite lower resolution.
  • Scope and limitations: The models are one-zone, omit spatial dynamics and dust treatment, and represent spectral rather than necessarily morphological galaxy types at earlier cosmic times.Standard models also do not reproduce mass–metallicity relations unless users parameterize star-formation histories as a function of galaxy mass.
  • Galaxies: The calibrated galaxy models yield V-band mass-to-light ratios of 11.8, 8.2, 5.9, 4.5, and 3.0 for E, Sa, Sb, Sc, and Sd, respectively.These values include the FVM=0.5 treatment of mass locked in sub-stellar objects, which also affects chemical evolution.
  • Disturbed galaxies: Starbursts & SF truncation: GALEV also models starbursts and star-formation truncation, but burst strength depends on gas available at onset and is fully determined only after the burst ends.Before the burst ends, only lower limits to its strength can be estimated.

6 THE WEB INTERFACE

The GALEV web interface lets users run standard or customized stellar-population and galaxy models online, with parameter checks, selectable input physics, cosmological settings, and configurable outputs.

  • The interface provides online access to existing star-cluster and galaxy models and lets users run new models for specific applications.
  • Web-based checks address frequent input problems and provide users with the latest input physics, including isochrone sets and stellar libraries.
  • A four-step workflow collects model and output parameters, checks them, and runs the selected model on the web server.
  • Users can choose galaxy types, bursts or truncations, filters, metallicity treatments, stellar libraries, gas emission, and star-formation-history parameters.
  • Cosmological parameters and a formation redshift enable redshift evolution, while output restrictions and selectable magnitude systems control computation and downloads.
  • Integrated spectra are the primary output, from which magnitudes and redshifted spectra are derived alongside diagnostic quantities such as masses, star-formation rates, metallicity, and ionizing flux.
  • The current interface supports spectra and colours, while Lick indices and colour-magnitude diagrams are being implemented for future online access.

7 FUTURE PROSPECTS

Future GALEV development targets higher-resolution stellar libraries, self-consistent dust treatment, and coupling to dynamical galaxy models for spatially resolved data.

  • Additional stellar libraries are planned to provide high-resolution spectra for comparison with modern spectroscopic surveys, but they have shorter wavelength coverage and are not colour-corrected like the current library.
  • Current galaxy evolutionary synthesis models lack a self-consistent treatment of dust absorption and reemission because dust properties depend on geometry, gas content, abundances, and radiation fields.
  • Coupling GALEV to dynamical models is feasible, but an earlier attempt failed to reproduce correct local disk sizes and parameters, indicating a need for improved feedback descriptions.

8 APPLICATIONS

GALEV applications span cluster parameter recovery, stellar-population diagnostics, galaxy evolution, starbursts, mergers, tidal dwarfs, transformation, and high-redshift photometry. These studies show both the model’s broad applicability and important observational constraints on interpreting colours, star-formation indicators, and star-formation histories.

  • 8.1 Star clusters: Multi-band GALEV fitting derives cluster ages, masses, metallicities, and extinction, requiring at least three bands with one externally constrained parameter or four otherwise.The preferred filter coverage includes a short-wavelength U or B band and a near-infrared H or K band.
  • 8.2 Colour-magnitude diagrams: GALEV computes colour-magnitude diagrams for simple and composite populations in arbitrary passband combinations to disentangle age and metallicity effects.This capability has been used to identify suitable passbands across different cluster age ranges.
  • 8.3 Galaxy evolution: Star-formation indicators Hα, [OII], NUV, and FUV significantly depend on metallicity, with worst-case errors reaching factors of a few.The result applies to studies of the chemical evolutionary state of galaxies and their star-formation-rate indicators.
  • 8.3.1 Starbursts in Blue Compact Dwarf Galaxies: Weak bursts can dominate optical light in metal-poor blue compact dwarf galaxies, while an underlying old component is detectable in the near-infrared.Burst strengths were only a few percent in stellar mass and decreased systematically with increasing galaxy mass.
  • 8.4 Interacting galaxies and mergers: The NGC 7252 interaction-induced burst began about 600−900 Myr ago and was 1−2 orders of magnitude stronger than bursts in blue compact dwarf galaxies.GALEV estimated a present central star-formation rate of about 3 M⊙yr−1 and projected evolution toward an elliptical or S0 galaxy over 1−3 Gyr, depending on future star formation.
  • 8.5 Tidal dwarf galaxies: Optical data alone can hide even a 90% inherited stellar mass fraction in tidal dwarf candidates when a burst contributes only 10% of the mass.Optical-near-infrared colours are needed to detect the inherited component.
  • 8.6 High redshift galaxies and photometric redshifts: Including blue starburst and extremely red postburst phases allows GALEV to reproduce the full observed colour range of Hubble Deep Field galaxies without dust.Subsolar metallicities also improve photometric-redshift estimates for high-redshift galaxies compared with solar-metallicity models alone.
  • 8.7 Redshift evolution of ISM abundances: spiral models vs. DLAs: Moderate infall is required: increasing total mass from redshift 2 to the present by more than about a factor of 2 loses agreement with spectral or chemical constraints.The result comes from studying the impact of different infall amounts.

9 SUMMARY

The paper presents the web-available GALEV models, their input physics, chemically consistent treatment, outputs, and applications. GALEV supports customizable cluster and galaxy models across metallicities, star-formation histories, filter systems, and cosmological redshift evolution, while the paper also discusses limitations and future prospects.

  • 9 SUMMARY: GALEV models for star clusters, undisturbed galaxies, starbursts, and star-formation truncation are available through a web interface.The paper presents their input physics, calibrations, interface, and selected applications.
  • 9 SUMMARY: Cluster spectral evolution supports multiple stellar IMFs, metallicities from −1.7 ≤ [Fe/H] ≤ +0.4, many filter systems, and the full set of Lick absorption indices.
  • 9 SUMMARY: Chemically consistent modelling jointly evolves the interstellar medium and stellar spectra using input physics appropriate to the increasing abundances of successive stellar generations.The model includes tracks, atmospheres, gaseous emission, lifetimes, yields, and remnant masses at the relevant abundances.
  • 9 SUMMARY: Galaxy models can use chemical evolution or fixed metallicity and provide spectra, emission lines, Lick features, photometry, abundances, masses, and star-formation rates for user-specified histories.Cosmological models additionally provide redshift evolution with evolutionary and cosmological corrections and intergalactic neutral-hydrogen attenuation.
  • 9 SUMMARY: The paper explicitly discusses current limitations and future prospects alongside the models, input physics, calibrations, interface, and applications.

APPENDIX A: WORKING IN PICTURES

The appendix explains GALEV through a sequence of modelling steps, using examples to connect its input physics to galaxy modelling.

  • APPENDIX A: WORKING IN PICTURES: The appendix guides readers through sequential modelling steps and illustrates how GALEV input physics is used throughout galaxy modelling.

A1 General steps

The first modelling step combines isochrones, a stellar IMF, a spectral library, and atomic physics to construct an integrated isochrone spectrum.

  • A1 General steps: An integrated isochrone spectrum is built from Padova isochrones, a Salpeter IMF spanning 0.1M⊙ to 100M⊙, Lejeune stellar spectra, and solar metallicity.

Step 1: Choose set of isochrones

GALEV begins by selecting age- and metallicity-dependent stellar isochrones, which define the evolutionary stages and photometric properties of the model population.

  • Step 1: Choose set of isochrones: Solar-metallicity isochrones are shown for ages of 4 Myr, 100 Myr, and 1 Gyr in a colour-magnitude diagram.Young isochrones reach very luminous high-mass main-sequence stars, while older ones show RGB and AGB phases.
  • Step 1: Choose set of isochrones: The selected isochrones provide the stellar evolutionary stages later used to construct integrated population properties.
  • Step 1: Choose set of isochrones: The model examples use Padova isochrones to represent stellar populations at different evolutionary ages.

Step 2: Select Initial Mass Function

GALEV then selects an initial mass function to determine how many stars of each mass populate the chosen isochrones.

  • Step 2: Select Initial Mass Function: Salpeter and Kroupa IMFs predict comparable star numbers above 1 M⊙ but differ substantially below 1 M⊙.These low-mass differences affect mass-to-light ratios, spectra, and chemical enrichment.
  • Step 2: Select Initial Mass Function: The IMF specifies the number of stars formed as a function of stellar mass.
  • Step 2: Select Initial Mass Function: Choosing an IMF is a required assumption of evolutionary synthesis models alongside the galaxy’s star formation history.

Step 3: Populate isochrones with stars

GALEV populates each isochrone by assigning stars according to the IMF, producing a synthetic colour-magnitude diagram while retaining short-lived evolutionary phases for visualization.

  • Step 3: Populate isochrones with stars: For each isochrone mass point, the IMF determines how many stars are assigned to that mass.
  • Step 3: Populate isochrones with stars: The resulting synthetic colour-magnitude diagram adds scatter around individual points for a smoother, more realistic appearance.
  • Step 3: Populate isochrones with stars: At least one star is added to every isochrone point to display all evolutionary phases, although real populations may lack extremely short-lived phases.Very young, extremely hot white-dwarf phases are given as an example of stages that may be underrepresented in reality.

Step 4: Assign a spectrum to each star

GALEV assigns stellar spectra, integrates them into isochrone spectra, adds gaseous emission, interpolates ages and metallicities, and combines populations into galaxy spectra with cosmological and attenuation effects.

  • Step 4: Assign a spectrum to each star: Each star receives a spectrum from its isochrone parameters, including effective temperature and derived surface gravity.Sample spectra illustrate temperature-dependent stellar emission at fixed log g = 4.0.
  • Step 4: Assign a spectrum to each star: Integrating stars with their evolutionary luminosities produces age-dependent isochrone spectra dominated by massive hot stars at young ages.At 1 Gyr, little UV flux remains and stars near 2 M⊙ dominate the spectrum.
  • Step 4: Assign a spectrum to each star: GALEV adds gaseous continuum and line emission using the metallicity and ionizing-photon flux derived from each isochrone and IMF.Emission lines are prominent at 4 Myr and weaken at later stages.
  • Step 4: Assign a spectrum to each star: The model repeats these calculations across available ages and metallicities, then interpolates spectra to obtain finer age grids.Interpolation is based on the approximately linear spectral variation with logarithmic time.
  • Step 4: Assign a spectrum to each star: Galaxy spectra are assembled by weighting populations of different ages and metallicities by their star formation rates and timestep durations.The toy model demonstrates combining two bursts into spectra at 300 Myr and 1 Gyr.
  • Step 4: Assign a spectrum to each star: For galaxy modelling, chemical evolution tracks stellar, gas, and metal masses using star formation, stellar lifetimes, remnants, and returned material.
  • Step 4: Assign a spectrum to each star: At redshift z = 3, GALEV accounts for evolutionary state, dust reddening, cosmological redshifting, and intergalactic attenuation.Figure A14 shows these effects added successively to an elliptical-galaxy spectrum.
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