1. A Study of the Abundances and Lyα Emission of Ultraviolet Selected Samples of Star Forming Galaxies in the Local Universe Ryan Mallery (Ph.D. thesis), R. Michael Rich, Jean-Michel Deharveng, and the Galex team UCLA

2. GALEX Telescope –Imaging and slitless grism spectroscopy –FUV (1300-1800 Å) 4.5” psf FWHM –NUV (1800-2800 Å) 6” psf FWHM –50 cm diameter –1.2 degree diameter FOV –8 Å spectral resolution SurveyExp timeAream lim Deep Imaging Survey 30,000s80 deg 2 25 AB Medium Imaging Survey 1500s1000 deg 2 23 AB All Sky Imaging Survey 100s26,000 deg 2 20.5 AB Medium Spectroscopic Survey 150,000s5 deg 2 22 AB

3. Lyα Emitters Motivation Issue: Lyα emission from galaxies is likely affected by a combination of dust extinction, gas kinematics, and spatial geometry but the order of importance of each of these is unknown, and may vary from galaxy to galaxy. Opportunity: Galex grism mode in Far-UV (FUV) used to discover the first known sample of low redshift LAE galaxies. Instead of studying LAEs at z~4, study them at z~0.3 Goal: Analyze photometry and spectroscopy of a local z~0.3 sample of ~76 LAEs and 107 non-LAEs to : –1) determine why Lyα escapes from some galaxies and not others. –2) determine the relative effect of gas kinematics, ISM geometry, and extinction by dust on the Lyα emission. Importance: Lyα is presently one of the most widely utilized spectral features for the discovery and identification of galaxies at the highest redshifts. –Due to the low redshifts, and hence relatively bright UV+optical fluxes, the sample represents a chance to understand the astrophysics of these sources in much more detail than can be done with high redshift LAEs

4. GALEX LAE Sample The First Systematic low redshift Survey for LAEs (first discovered by Deharveng et al. 2008) Northern Hemisphere Deep GALEX Spectroscopic Fields –Cosmological Evolution Survey (COSMOS) –All Wavelength Extended Groth Strip International Survey (AEGIS) –NOAO Deep Wide Field Survey (NDWFS) –Spitzer First Look Survey (FLS) 76 LAEs LAEs are matched to sources in publicly available datasets (SDSS, ACS, IRAC, MIPS) within 4” –75/76 with SDSS photometry –25/76 with IRAC photometry –20/76 with ACS photometry –32/76 with MIPS 24μm photometry

5. COSMOS UV spectroscopy exposure time: 35 hours 15 LAEs 14/15 with SDSS 15/15 with ACS imaging 14/15 with MIPS 24 detections

6. AEGIS UV spectroscopy exposure time: 80 hours 37 LAEs 37/37 with SDSS 6/37 with ACS imaging 13/37 with MIPS 24 detections

7. NDWFS UV spectroscopy exposure time: 43 hours 17 LAEs 17/17 with SDSS 0/17 with ACS imaging 0/17 with MIPS 24 detections

8. FLS UV spectroscopy exposure time: 22 hours 7 LAEs 7/7 with SDSS 0/7 with ACS imaging 5/7 with MIPS 24 detections

9. Non-LAEs Sources with GALEX spectroscopy, within the same redshift range as the LAEs, that lack detections of Lyα. 107 non-LAEs COSMOS: 39 sources AEGIS: 39 sources FLS: 29 sources Non-LAEs: black hashed histogram LAEs: black histogram

10. Non-LAEs Sources with GALEX spectroscopy, within the same redshift range as the LAEs, that lack detections of Lyα. 107 non-LAEs COSMOS: 39 sources AEGIS: 39 sources FLS: 29 sources Non-LAEs: black hashed histogram LAEs: black histogram non-LAEs serve as a control sample. Do LAEs have other physical properties that differ from non-LAEs? Are these properties related to Ly α emission/escape?

11. UV, Optical, IR distributions Black hashed histogram: non-LAEs Black Histogram: all LAEs Blue Histogram: non- AGN LAEs Red Histogram: AGN LAEs FUV: LAEs are on average slightly more luminous Optical: LAEs are bimodal. The more luminous peak being due in part to AGN contamination. IR: LAEs and non-LAEs have statistically similar distributions.

12. Color Magnitude Diagram: LAEs not special LAEs and non-LAEs span 2 orders of magnitude in optical luminosity Have similar NUV-r distributions At M r >-21 the LAEs tend to have bluer UV colors, related to star formation history. LEGEND Blue: non-AGN LAEs Red: AGN LAEs  Squares: non-LAEs (symbols sized according to EW Lyα )

13. Dust and Extinction L IR is derived from MIPS 24um and Chary & Elbaz (2001) dust models. LAEs tend to have FUV luminosities comparable to the highest FUV luminosities of non-LAEs. LAEs and non-LAEs span a similar range of IRX. 1/3 of LAEs have bluer UV colors than non-LAEs with similar IRX. Dust extinction is not likely to be the reason why Lyα is not detected in the non- LAEs.

14. Dust, Extinction, UV color and Starbursts Create a grid of Bruzual & Charlot (2003) Stellar population synthesis galaxy evolution models, varying star formation history and extinction. Half with and half without a bursts of star formation. The blue UV colors of LAEs can be explained by starbursts which form at least 10% of the galaxy’s stellar mass.

15. Morphology of LAEs Since there appears to be little evidence to suggest that dust extinction is inhibiting Lyα emission from the non-LAE sample, perhaps the sources have different morphologies/geometries? 20/76 LAEs & 64/107 non-LAEs with ACS F814W imaging with 0”.03 pix -1 resolution.

17. LAE/non-LAE Morphologies The size of the LAEs correlates with optical luminosity. I FUV is likely underestimated for the large sources as the UV flux is likely emitted from HII regions within the disks. There are no compact low luminosity non-LAEs, which is likely a selection effect of the GALEX spectroscopy. Overall there is no major difference between the F814W geometries of the LAEs and non-LAEs.

18. Outflows and Star formation Heckman (2002) found that for a sample of nearby sources, outflows were present in all galaxies with a star formation rate surface density, Σ SFR > 0.1 M  yr -1 kpc -2 Rupke et al. (2004) found a correlation between SFR and outflow velocity. log (Outflow Velocity / km s -1 )

19. Σ SFR of LAEs and non-LAEs All compact LAEs (r< 7 kpc) are offset from non-LAEs in Σ SFR - UV color. As Σ SFR is an indicator of outflows, this implies that the presence of outflows is the discriminating factor between LAEs and non-LAEs. Higher resolution UV imaging is required to investigate Σ SFR for the larger disk sources where the UV sizes may be poorly estimated by the F814W imaging.

20. Lyα Luminosity and the UV continuum Lyα to first order is correlated with the FUV luminosity, and to second order with the FUV luminosity density (I FUV ).

21. What influences the emergent Lyα flux? For the GALEX LAEs, no correlation is found between the equivalent widths and UV luminosity, IR luminosity, or UV extinction (as indicated by IRX). This in contrast to the results of Shapley et al. (2003), Kornei et al. (2009) for z~3 LAEs, and Atek et al. (2009) for z~0 LAEs

22. Lyα Escape Fraction f esc = Lyα/Hα/8.7 Hα/Hβ probes extinction, E(B-V) Scarlata et al. (2010)Atek et al. (2009) f esc, decreases with increasing extinction Large scatter: due to kinematics and/or different dust properties/distributions?

23. The Lyα escape fraction For 21 LAEs, flux calibrated optical spectroscopy was obtained with measured Hα and Hα fluxes. 13/21 were obtained with long slit aperture matched spectroscopy at Lick and KPNO. 8/21 were observed at Keck with 1”.5 long slit spectroscopy. LEGEND Dotted lines: CASE B recombintion ratios. Dashed line: Calzetti extinction law. Dot-dashed line: Cardelli exinction law The mean escape fraction for these sources decreases with increasing  ratios, indicating that dust extinction does have an effect on the amount of emergent Lyα flux

24. Escape Fraction and Equivalent width (EW) The EW increases for increasing escape fractions. –The notable exceptions are the sources without aperture matched spectroscopic observations.

25. IRX vs Hα/Hβ Hα/Hβ is uncorrelated with both IRX and FUV-NUV. The global extinctions (e.g. IRX) do not correctly represent the line of sight extinctions into the HII regions as probed by the Balmer emission lines.

26. Escape, Extinction and Σ SFR The Facts: Sources with large EW >50 Å have both low E(B-V) ≲ 0.07 and high Σ SFR ≳ 0.1 Sources with low E(B-V) ≲ 0.07 and low Σ SFR ≲ 0.1 have low EW. One source, that has the lowest EW of the sample, has both a low E(B-V) and high Σ SFR but is highly inclined (b/a = 0.36)

27. Escape, Extinction and Σ SFR Conclusions: Both low E(B-V) ≲ 0.07 and high Σ SFR ≳ 0.1may be required for large escape fractions and EW. Both high E(B-V) ≳ 0.07 and low Σ SFR ≲ 0.1can greatly reduce the observed escape fraction and EW. For the one source with both a low E(B-V) and high Σ SFR, the highly inclined (b/a = 0.36) morphology of the source may lead to increased scattering opacity along the line of sight which gives the source such a low EW.

28. Results The GALEX LAEs are a heterogeneous assortment of star forming galaxies. The distributions of IR-luminosities and optical luminosities span 2 orders of magnitude. The optical distribution is bimodal in part due to AGN contamination as 11/22 LAEs with 0.0 M r < -22.5 are AGN. Dust extinction is likely not the dominant effect inhibiting Lyα from escaping the non-LAE sources. It may play a role at high L IR. LAEs have higher Σ SFR than non-LAEs: this implies that the LAEs have outflows, while the non-LAEs do not.

29. Results (cont) The Lyα EWs of these sources are not correlated with the global photometric properties for the sample, including L FUV, and IRX (extinction). –For IRX, this is likely because the IRX values probe a large area than the lines of sight into the HII regions that give rise to Lyα and the Balmer lines. Both geometry, extinction, and Σ SFR play a role in the Lya escape fraction: all 3 factors can inhibit the observed escape along the line of sight.

30. Project 2: Future Work Obtain aperture matched optical spectroscopy of entire GALEX LAE sample. Obtain high resolution UV spectra of sources with Cosmic Origins Spectrograph on HST –Measure kinematics Obtain high resolution UV images of the LAEs. Lyα imaging? –Compare Σ SFR vs kinematics Compare/contrast the GALEX LAEs to high redshift samples (i.e. SFH, M *, size, EW)

32. BACKUP SLIDES

33. Measuring Oxygen Abundances O3N2 {Pettini & Pagel et al 2005} –Calibration to T e abundance data, O/H = f(O3N2) –O3N2 = [OIII]/  / [NII]  –Not corrected for ionization M91 {McGaugh et al (1991)} –Photoionization Model, O/H = f( R 23 ) –R 23 = ([OIII]5007+[OIII]4959 + [OII]3727)/  –O/H has 2 values for each R 23 value T04 {Tremonti et al 2004} –Bayesian approach using photoionization models of Charlot & Longhetti (2001) –O/H < 8.2 : N/H ∝ (O/H) –O/H > 8.2 : N/H ∝ (O/H) 2

34. Measuring the Nitrogen Abundance Log N + /O + = Log [NII6584]/[OII3727] + 0.307 - 0.02 Log T NII - 0.726/T NII –from Pagel et al. (1992) –Empirical calibration from T e abundances –Applicability to high metallicities is unknown. T NII =.6065+.1600 log R 23 +.1878 (log R 23 ) 2 +.2803 (log R 23 ) 3 – from Thurston, Edmonds & Henry (1996) T NII from Cloudy photoionization models T NII ~ 500K uncertainty