Recovering Stellar Population Properties and Redshifts from Broad-Band Photometry of Simulated Galaxies: Lessons for SED Modeling

We present a detailed analysis of our ability to determine stellar masses, ages, reddening and extinction values, and star formation rates of high-redshift galaxies by modeling broad-band SEDs with stellar population synthesis. In order to do so, we computed synthetic optical-to-NIR SEDs for model galaxies taken from hydrodynamical merger simulations placed at redshifts 1.5 < z < 3. Viewed under different angles and during different evolutionary phases, the simulations represent a wide variety of galaxy types (disks, mergers, spheroids). We show that simulated galaxies span a wide range in SEDs and color, comparable to these of observed galaxies. In all star-forming phases, dust attenuation has a large effect on colors, SEDs, and fluxes. The broad-band SEDs were then fed to a standard SED modeling procedure and resulting stellar population parameters were compared to their true values. Disk galaxies generally show a decent median correspondence between the true and estimated mass and age, but suffer from large uncertainties. During the merger itself, we find larger offsets (e.g., log M_recovered - log M_true = -0.13^{+0.10}_{-0.14}). E(B-V) values are generally recovered well, but the estimated total visual absorption Av is consistently too low, increasingly so for larger optical depths. Since the largest optical depths occur during the phases of most intense star formation, it is for the highest SFRs that we find the largest underestimates. The masses, ages, E(B-V), Av, and SFR of merger remnants (spheroids) are very well reproduced. We discuss possible biases in SED modeling results caused by mismatch between the true and template star formation history, dust distribution, metallicity variations and AGN contribution.Comment: Accepted for publication in the Astrophysical Journal, 24 pages, 19 figure

Automated Galaxy Morphology: A Fourier Approach

We use automated surface photometry and pattern classification techniques to morphologically classify galaxies. The two-dimensional light distribution of a galaxy is reconstructed using Fourier series fits to azimuthal profiles computed in concentric elliptical annuli centered on the galaxy. Both the phase and amplitude of each Fourier component have been studied as a function of radial bin number for a large collection of galaxy images using principal component analysis. We find that up to 90 percent of the variance in many of these Fourier profiles may be characterized in as few as 3 principal components and their use substantially reduces the dimensionality of the classification problem. We use supervised learning methods in the form of artificial neural networks to train galaxy classifiers that detect morphological bars at the 85-90 percent confidence level and can identify the Hubble type with a 1-sigma scatter of 1.5 steps on the 16-step stage axis of the revised Hubble system. Finally, we systematically characterize the adverse effects of decreasing resolution and S/N on the quality of morphological information predicted by these classifiers.Comment: Accepted to Astrophysical Journal, 43 pages, 12 figure

Observing Galaxy Evolution in the Context of Large-Scale Structure

Galaxies form and evolve in the context of their local and large-scale environments. Their baryonic content that we observe with imaging and spectroscopy is intimately connected to the properties of their dark matter halos, and to their location in the "cosmic web" of large-scale structure. Very large spectroscopic surveys of the local universe (e.g., SDSS and GAMA) measure galaxy positions (location within large-scale structure), statistical clustering (a direct constraint on dark matter halo masses), and spectral features (measuring physical conditions of the gas and stars within the galaxies, as well as internal velocities). Deep surveys with the James Webb Space Telescope (JWST) will revolutionize spectroscopic measurements of redshifts and spectral properties for galaxies out to the epoch of reionization, but with numerical statistics and over cosmic volumes that are too small to map large-scale structure and to constrain halo properties via clustering. Here, we consider advances in understanding galaxy evolution that would be enabled by very large spectroscopic surveys at high redshifts: very large numbers of galaxies (outstanding statistics) over large co-moving volumes (large-scale structure on all scales) over broad redshift ranges (evolution over most of cosmic history). The required observational facility can be established as part of the probe portfolio by NASA within the next decade.Comment: 8 pages (including cover page and references), 3 figures. Science white paper submitted to Astro2020. arXiv admin note: substantial text overlap with arXiv:1802.0153

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo