The Effect of Crowding on the GSMT Stellar Populations

Science Case

Knut Olsen, Bob Blum (NOAO), François Rigaut (Gemini)

GSMT SWG Presentation

Hilo 2002

MotivationStudying galaxy formation through the star and chemical enrichment histories of galaxies requires precise photometry

What sources contribute to random photometric error?•Photon statistics•Errors in PSF fitting•Crowding•The pitfalls of photometry with AO systems

Modeling crowding effects

V I

Crowding introduces photometric error through luminosity fluctuations within a single resolution element of the telescope due to the unresolved stellar sources in that element.

To calculate the effects of crowding on magnitudes and colors, we need only consider the Poisson statistics of the luminosity functions (e.g. Tonry & Schneider 1988)

Issues:•characterizing resolution•luminosity range over which fluctuations are important

For magnitudes:

For colors:

Simulations

Overview:

•3 simulations of LMC globular cluster NGC 1835, at seeing-limited, HST, and GSMT resolution

•3 simulations of the center of M32, at resolution ofGemini+Hokupa’a, 8-m NGST, and GSMT

•GSMT simulations of the Arches cluster and the bulge of M33

Artificial stellar populations and artificial star tests

The Center of M32

Davidge et al. (2000)

~0.”12 FWHM H&K

Gemini N + Hokupa’a

Krist (1999) 8-m NGST PSF

0.”032 J, 0.”057 K FWHM 0.”035 pixels

30” 20” 20”

M32 Population: 10% 1 Gyr ([Fe/H]=0), 45% 5 Gyr ([Fe/H]=0), 45% 10 Gyr ([Fe/H]=-0.3); cent = 10.1 mag arcsec-2

F. Rigaut GSMT PSF

0.”009 J, 0.”015 K FWHM 0.”005 pixels

Gemini+Hokupa’a•Photometry with DAOPHOT/ALLSTAR

•Calibrated with Davidge et al. (2000) photometry

•14500 artificial stars added, PSF rederived and photometry repeated

•CMD and errors shown for 7.”4 < r < 13.”1 annulus centered on M32

•Crowding limit H,K~16.5

Crowding model

DAOPHOT

NGST•Artificial population

•Photometry with DAOPHOT/ALLSTAR

•Zero points adjusted to fit input magnitudes

•CMD and errors shown for 7.”4 < r < 13.”1 annulus centered on M32

•Crowding limit J~20.5,K~19.5

DAOPHOT

0.”07 J, 0.”057 K

0.”035 J, 0.”057 K

GSMT•Artificial population

•Photometry with DAOPHOT/ALLSTAR

•Zero points adjusted to fit input magnitudes

•CMD and errors shown for 7.”4 < r < 13.”1 annulus centered on M32

•Crowding limit J~23.5, K~22

DAOPHOT

0.”005 J, 0.”005 K

0.”009J, 0.”015 K

Beyond M32

Girardi et al. (2000) tracks

0.1,1,2,5,8,10,14 Gyr

[Fe/H]=-1.0, 0.0

K=19, V=22 mag arcsec-2

30-m + J,K100-m + J,K100-m + V,I

Crowding error also measures completeness

Conclusions

•Crowding is likely the limiting factor for the stellar populations science

•Analytical predictions are adequate for evaluating effects of crowding, but full understanding of photometry requires simulations

•Realistic GSMT simulations need, at the very least, to include the effect of stars placed at sub-pixel positions

•GSMT provides giant leap for stellar populations mainly through its resolution; how large does the Strehl need to be?