How does dust affect estimates of galaxy ages?

1. How does dust affect estimates of galaxy ages? By Justin Griggs Supervisor: Jason Melbourne Advisor: David Koo

2. Outline • Background information • Methods • Results • Limitations of the method • Conclusion • Acknowledgements

3. Light Emission is Indication of: • Age • Temperature • Dust • The Effects of Dust: • Redder Appearance • Older, yet Cooler look

4. Examples of Real Galaxies

5. No Dust Lots of Dust Use Adaptive Optics to estimate the age of galaxies with dust

6. Method Experimental Models Program reads in files Random photometric error Compares 1 model to all ages Plot of age vs. dust using probability Calculate probability

7. Sample: 5x5 array Old Age Young Less More Dust Flux Wavelength Models • 219 ages • 14 dust models • 3-8 colors • SSP star formation • Photometric error: 5-50%

8. Sample: 5x5 array Old Age Young Less More Dust Flux = Model + error Wavelength Program

9. Results Use probability to plot age vs dust to narrow down “good” models by eliminating “bad” ones. • Using different colors (with and without AO) • Using different errors (high-low)

10. Bad estimate Good estimate Bad estimate 10 billion years 10 million years • Standard model: dust=0 • 3 colors • Age~8.00 log yrs. • Photometric error: ~10% Hubble Space Telescope (HST) withoutAdaptive Optics More Dust Less Dust

11. Bad estimate Good estimate Bad estimate 10 billion years 10 million years • Standard model: dust=0 • 6 colors • Age~8.00 log yrs. • Photometric error: ~10% HST + Adaptive Optics More Dust Less Dust

12. Bad estimate Good estimate Bad estimate 10 billion years 10 million years • Standard model: dust=0 • 8 colors • Age~8.00 log yrs. • Photometric error: ~10% Future? More Dust Less Dust

13. Bad estimate Good estimate Bad estimate 10 billion years 10 million years • Standard model: dust=1 • 6 colors • Age~9.00 log yrs. • Photometric error: ~20% HST + Adaptive Optics with high photometric error More Dust Less Dust

14. Bad estimate Good estimate Bad estimate 10 billion years 10 million years • Standard model: dust=1 • 6 colors • Age~9.00 log yrs. • Photometric error: ~10% HST + Adaptive Optics with medium photometric error More Dust Less Dust

15. Bad estimate Good estimate Bad estimate 10 billion years 10 million years • Standard model: dust=1 • 6 colors • Age~9.00 log yrs. • Photometric error: ~6% HST + Adaptive Optics with low photometric error More Dust Less Dust

16. Limitations • Dust models are simple • Galaxy star formation model is very simple (SSP)

17. Conclusion Dust Causes galaxies to appear redder and thus older than their actual age. Adaptive Optics vs. HST: • AO enables estimates of ages to be within 25% accuracy for a photometric error of 10% • Age estimates better with photometric error between 5 and 10%

18. Acknowledgements • Funding provided through the Center For Adaptive Optics, a National Science Foundation Science and Technology Center (STC), AST-987683 • Jason Melbourne, Post doc in astronomy at UCSC • David Koo, professor in astronomy at UCSC