Uncertainties in Population Synthesis

Models: Applications to Local and

Distant Galaxies

Gustavo Bruzual A.

CIDA, Mérida, Venezuela

Motivation:

Look at some problems or failures of current generation of population synthesis models and see what is the best we can do to understand them using available tools and data.

What we would like to have in the years to come…

My view:

There is not a perfect model or set of models. Depending on the application, a set of models built with a particular set of ingredients may be optimal.

Most data sets are incomplete and may remain incomplete for a long time

Work in collaboration with S. Charlot (soon to be published, CB10).

TypicalIsochrone

Marigo et al. (2008)

Theoretical HRD

TypicalIsochrone (detail)

Marigo et al. (2008)

Theoretical HRD

Stellar

libraries:

wavelength

coverage

Stellarlibraries:

Teffcoverage

IndoUS, Miles,and Stelib

[Fe/H]Distribution

Complete near Solar (more or less)

Increasing spectral resolution

• Coelho (< 1Å)

• IndoUS (~ 1Å)• Miles (2.4 Å)

• Stelib (3 Å)

• HNGSL (~ 5Å)• Pickles (5 Å)• Kurucz (20 Å)

Padova 94 tracks

Behaviour of line strength indices:Models vs SDSS bright galaxies

IndoUS (new) Stelib (BC03)

Caution:

Flux calibration

problem in

IndoUS library.

Calibration and stellar parameters under revision by Prugniel and collaborators

STIS NGSL UV coverage

NGSL (black) vs IUE (cyan) and Kurucz models (green)

Solar metallicity

1 Gyr SSP

Chabrier IMF

Padova 1994 tracks

STIS NGSL is being enlarged and recalibrated by Lindler & Heap and collaborators

STIS NGSL UV coverage

NGSL vs Kuruczmodels (green)

Z = 0.2 x Solar (blue)

0.4 x Solar (cyan)

1.0 x Solar (red)

12 Gyr SSP

Chabrier IMF

Padova 1994 tracks

Problem 1: Incompleteness of stellar libraries

U-UV spectral range.

Excess of U flux in population models built using incomplete stellar libraries.

Completeness matters

Walcher et al. (2008): VVDS data (grey shading) vs. models (contours) Conclude that the wavelength range from 3300 to 4050 Å is not correctly reproduced by

models based mostly in the Miles library, which contains few hot stars.

Walcher et al. (2008): Excess U flux is clearly seen in fit to typical

galaxy sed

Improving the U-UV spectral range

Tlusty Models:

Grid of NLTE plane parallel hydrostatic model atmospheres for:

O-stars: Lanz & Hubeny (2003)

B-stars: Lanz & Hubeny (2007)

High spectral resolution from 54.8 Å to FIR (R = 50,000)

15,000 ≤ Teff ≤ 55,000 K;

0 ≤ Z ≤ 2 x Zo

Improving the U-UV spectral range

Martins et al. (2005) Models:

Grid of NLTE plane parallel hydrostatic model atmospheres

Coverage:

3,000 ≤ Teff ≤ 27,500 K;

0.10 x Zo ≤ Z ≤ 2 x Zo

3000 to 7000 Å (R = 20,000)

Improving the U-UV spectral range

UVBLUE and BLURED:

Grid of model atmospheres based on Kurucz (1993) model atmospheres:

UVBLUE: Rodriguez-Merino et al. (2005)

Coverage: 3,000 to 50,000 K

850 to 4700 Å (R = 50,000)

-2.0 ≤ [Fe/H] ≤ +0.5

BLUERED: Bertone et al. (2008)

3500 to 7000 Å (R = 500,000)

Walcher (2009): VVDS data (grey shading) vs. models (contours) Major improvement after including Tlusty,

Martins et al., and UVBLUE stellar atmospheremodels to complement MILES library in SSP modelling

(work in progress).

Another look at the problem:

Pure Miles (black)

Extended Miles (red)

In the pure Miles case intermediate Teff stars were represented by hotter stars.

It is important to use a stellar library as complete as possible.

Ionizing photons: Depend on Tlusty models

For SSP’s of

Z = 0 0.0001

0.0004 0.001 0.002 0.004 0.008 0.017 0.040 (green) 0.070 (black)

Improvement over BaSeLAtlas values (e.g. HeII)

UV spectral indices

Defined by e.g. Fanelli et al.,can be computed directly from the UV sed, the same as in the visible range.

Z = 0.5 x Zo (blue) 1.0 x Zo (black)

2.5 x Zo (red)

Recent work on UV indices:

Maraston et al. (2008)Chavez et al. (2009)

Problem 2:Tracks should predict the right number of stars, at least in most relevan evolutionary phases (e.g. TP-AGB):

NIR stellar sed’s

Evolutionary tracks and the mass of galaxies

Improving the NIR spectral range

IRTF library:

Infrared Telescope Facility Spectral Library (Cool Stars)

Rayner et al. (2009)

Stellar Models for C-stars:

Aringer et al. (2009)

Both represent big improvements over previous data sets.

AGB

candidates

from SAGE

LMC survey

(Srinavasan et al. 2009)

AGB candidatesfrom SAGE LMCsurvey

Must take into account effects of dusty envelope and mass loss.

Dusty code

Poster by González-Lopezlira et al.

AGB candidatesfrom SAGE LMCsurvey

Must take into account effects of dusty envelope and mass loss.

Dusty code

Poster by González-Lopezlira et al.

Evolutionary tracks and the mass of galaxies

Bertelli et al. (2008):

Z = 0, 0.0001, 0.0004, 0.001, 0.002, 0.004, 0.008, 0.017, 0.040, 0.070

TP-AGB evolutionary prescriptions by:

Marigo & Girardi (2007): calibrated with MC clusters and star counts

Bertelli et al (2008): extrapolate results from the Marigo and Girardi

prescription to different chemical content of the

stellar envelope. Hence they

are uncalibrated.

olor Color evolution vs. MC cluster data

TP-AGB stars contribute roughly 60% of K light in the galaxy rest frame in the redshift range from 3 to 8

TP-AGB

more

numerous,

brighter,

and redder

(240 vs 60

per 1

million Mo

cluster)

Inferred mass

in B and K

HUDF data

CB07

SSP’s

τ(V) = 0

t=0.6 – 1.3 Gyr

M11=0.09–0.25

HUDF data

CB07

SSP’s

τ(V) = 1

t=0.7 – 1.3 Gyr

M11 = 0.1 – 0.3

HUDF data

CB07

SSP’s

τ(V) = 3

t=0.7 – 0.9 Gyr

M11 = 0.1 – 0.5

Problem 3:Why different codes produce different results?

Show example

All these models

are for the same

Z = 0.008 and

IMF (Salpeter)

LMC clusters

Different tracks

Different sed’s

Tracks Padova 2008,

Different Z’s

Stochastic effects

Large amount of work by many groups on:Alpha-enhanced stellar and population models:

Vazdekis and collaborators; Coelho and collaborators;

Maraston and collaborators; Thomas and collaborators

Variable light/heavy element ratio stellar and population models:

Worthey and collaborators

Star formation history in large galaxy samples:

A legion of really bright and hard workers

The role of binaries

Vanbeveren, Zhanwen Han

Propagation of uncertainties in population synthesis models and derived properties of galaxies:

Series of papers by Conroy, Gunn, & White

The future:

The answers to distant galaxy problems will come from understanding nearby stars

We have collected more photons from distant galaxies than from nearby stars

Population synthesis models can get better only if ingredients get better. Most of the uncertainties come from critical stages in the evolutionary tracks or missing spectra of important stellar evolutionary phases.

This can happen both from the observational and the theoretical framework

Basic things that we do not know well enough:

Distance to star clusters needed for calibration of stellar evolution models to a higher precision than at present. These errors translate into errors in the age of galaxies or other stellar populations dated using synthesis models.

Physical properties of more stars distributted all over the HR diagram: mass, Teff, radius, chemical abundance, chemical anomalies…

Blue stragglers, origin and role in stellar evolution and relevance in galaxies as integrated populations

The role of binaries in the evolution of stellar populations of various ages and metallicities, and in different environments (stellar density)

Basic things that we do not know well enough:

Evolutionary tracks or evolutionary prescription for EHB stars. Frequency, lifetimes, dependence on metallicity

The role of mass loss.

Is the IMF universal?

Effects of dust

More complete stellar spectral libraries (HST ?) that fill the current gaps (TP-AGB, EHB, Blue stragglers) in as wide a wavelength range as possible and with a good flux calibration, or

Model stellar atmospheres that can be used instead of the observed spectra mentioned in the previous point, including complete line lists and the right geometry and kinematics

Basic things that we do not know well enough:

Can stellar rotation be neglected (as we always do)?

Up to what extent can multiple MS in “SSPs” be neglected?

Do light/heavy element ratios vary from star to star or galaxy to galaxy in a way we can understand? Are models a la Worthey really necessary?

IndoUS vs STELIB

HNGSL UV coverage

HNGSL (black) vs IUE

(cyan) and Kurucz

models (green)

Solar metallicity

12 Gyr SSP

Chabrier IMF

Padova 1994 tracks

HNGSL UV coverage

HNGSL (black) vs IUE

(cyan) and Kurucz

models (green)

Solar metallicity

500 Myr SSP

Chabrier IMF

Padova 1994 tracks

HNGSL UV coverage

HNGSL vs Kurucz

models (green)

Z = 0.2 x Solar (blue)

0.4 x Solar (cyan)

1.0 x Solar (red)

1 Gyr SSP

Chabrier IMF

Padova 1994 tracks

HNGSL in the visible range

HNGSL (black) vs

STELIB (red),

Kurucz models

(green), and Pickles

library (cyan)

Solar metallicity

12 Gyr SSP

Chabrier IMF

Padova 1994 tracks

Flux

calibration

problem in

IndoUS

library

Flux

calibration

problem in

IndoUS

library