Prof. Matt Jarvis

Abstract:

Computer simulations are invaluable tools for scientific discovery. However, accurate simulations are often slow to execute, which limits their applicability to extensive parameter exploration, large-scale data analysis, and uncertainty quantification. A promising route to accelerate simulations by building fast emulators with machine learning requires large training datasets, which can be prohibitively expensive to obtain with slow simulations. Here we present a method based on neural architecture search to build accurate emulators even with a limited number of training data. The method successfully emulates simulations in 10 scientific cases including astrophysics, climate science, biogeochemistry, high energy density physics, fusion energy, and seismology, using the same super-architecture, algorithm, and hyperparameters. Our approach also inherently provides emulator uncertainty estimation, adding further confidence in their use. We anticipate this work will accelerate research involving expensive simulations, allow more extensive parameters exploration, and enable new, previously unfeasible computational discovery.

Abstract:

We describe the survey design, calibration, commissioning, and emission-line detection algorithms for the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the redshifts of over a million Lyα emitting galaxies between 1.88 < z < 3.52, in a 540 deg2 area encompassing a co-moving volume of 10.9 Gpc3. No pre-selection of targets is involved; instead the HETDEX measurements are accomplished via a spectroscopic survey using a suite of wide-field integral field units distributed over the focal plane of the telescope. This survey measures the Hubble expansion parameter and angular diameter distance, with a final expected accuracy of better than 1%. We detail the project’s observational strategy, reduction pipeline, source detection, and catalog generation, and present initial results for science verification in the COSMOS, Extended Groth Strip, and GOODS-N fields. We demonstrate that our data reach the required specifications in throughput, astrometric accuracy, flux limit, and object detection, with the end products being a catalog of emission-line sources, their object classifications, and flux-calibrated spectra.

Abstract:

Active galactic nuclei (AGN) are typically identified through radio, mid-infrared, or X-ray emission or through the presence of broad and/or narrow emission lines. AGN can also leave an imprint on a galaxy’s spectral energy distribution (SED) through the re-processing of photons by the dusty torus. Using the SED fitting code PROSPECT with an incorporated AGN component, we fit the far-ultraviolet to far-infrared SEDs of ∼494 000 galaxies in the D10-COSMOS field and ∼230 000 galaxies from the GAMA survey. By combining an AGN component with a flexible star formation and metallicity implementation, we obtain estimates for the AGN luminosities, stellar masses, star formation histories, and metallicity histories for each of our galaxies. We find that PROSPECT can identify AGN components in 91 per cent of galaxies pre-selected as containing AGN through narrow-emission line ratios and the presence of broad lines. Our PROSPECT-derived AGN luminosities show close agreement with luminosities derived for X-ray selected AGN using both the X-ray flux and previous SED fitting results. We show that incorporating the flexibility of an AGN component when fitting the SEDs of galaxies with no AGN has no significant impact on the derived galaxy properties. However, in order to obtain accurate estimates of the stellar properties of AGN host galaxies, it is crucial to include an AGN component in the SED fitting process. We use our derived AGN luminosities to map the evolution of the AGN luminosity function for 0 < z < 2 and find good agreement with previous measurements and predictions from theoretical models.

Abstract:

We present Lyα and ultraviolet (UV)-continuum luminosity functions (LFs) of galaxies and active galactic nuclei (AGNs) at z = 2.0-3.5 determined by the untargeted optical spectroscopic survey of the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). We combine deep Subaru imaging with HETDEX spectra resulting in 11.4 deg2 of fiber spectra sky coverage, obtaining 18,320 galaxies spectroscopically identified with Lyα emission, 2126 of which host type 1 AGNs showing broad (FWHM > 1000 km s-1) Lyα emission lines. We derive the Lyα (UV) LF over 2 orders of magnitude covering bright galaxies and AGNs in (-27 < MUV < -20) by the 1/Vmax estimator. Our results reveal that the bright-end hump of the Lyα LF is composed of type 1 AGNs. In conjunction with previous spectroscopic results at the faint end, we measure a slope of the best-fit Schechter function to be αSch=-1.70-0.14+0.13, which indicates that αSch steepens from z = 2-3 toward high redshift. Our UV LF agrees well with previous AGN UV LFs and extends to faint-AGN and bright-galaxy regimes. The number fraction of Lyα-emitting objects (XLAE) increases from MUV∗ ∼ -21 to bright magnitude due to the contribution of type 1 AGNs, while previous studies claim that XLyα decreases from faint magnitudes to MUV∗, suggesting a valley in the XLyα-magnitude relation at MUV∗. Comparing our UV LF of type 1 AGNs at z = 2-3 with those at z = 0, we find that the number density of faint (MUV > -21) type 1 AGNs increases from z ∼ 2 to 0, as opposed to the evolution of bright (MUV < -21) type 1 AGNs, suggesting AGN downsizing in the rest-frame UV luminosity.