Transcript The Effect of Crowding on the GSMT Stellar Populations Science Case Knut Olsen, Bob Blum (NOAO), François Rigaut (Gemini) GSMT SWG Presentation Hilo 2002

The Effect of Crowding on the
GSMT Stellar Populations
Science Case
Knut Olsen, Bob Blum (NOAO),
François Rigaut (Gemini)
GSMT SWG Presentation
Hilo 2002
Motivation
Studying 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
Crowding introduces photometric error through luminosity
fluctuations within a single resolution element of the telescope
due to the unresolved stellar sources in that element.
V
I
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
Artificial stellar populations and artificial star tests
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
of
Gemini+Hokupa’a, 8-m NGST, and GSMT
•GSMT simulations of the Arches cluster and the bulge of
M33
The Center of M32
30”
20”
20”
Davidge et al. (2000)
Krist (1999) 8-m NGST PSF
F. Rigaut GSMT PSF
~0.”12 FWHM H&K
0.”032 J, 0.”057 K FWHM
0.”035 pixels
0.”009 J, 0.”015 K FWHM
0.”005 pixels
Gemini N + Hokupa’a
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
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
0.”035 J, 0.”057 K
0.”07 J, 0.”057 K
DAOPHOT
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
0.”009J, 0.”015 K
0.”005 J, 0.”005 K
DAOPHOT
Beyond M32
100-m
30-m ++V,I
100-m
J,K
J,K
Crowding error also measures completeness
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
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?