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PESSTO: survey description and products from the first data release by the Public ESO Spectroscopic Survey of Transient Objects

Context. The Public European Southern Observatory Spectroscopic Survey of Transient Objects (PESSTO) began as a public spectroscopic survey in April 2012. PESSTO classifies transients from publicly available sources and wide-field surveys, and selects science targets for detailed spectroscopic and photometric follow-up. PESSTO runs for nine months of the year, January - April and August - December inclusive, and typically has allocations of 10 nights per month. Aims. We describe the data reduction strategy and data products that are publicly available through the ESO archive as the Spectroscopic Survey data release 1 (SSDR1). Methods. PESSTO uses the New Technology Telescope with the instruments EFOSC2 and SOFI to provide optical and NIR spectroscopy and imaging. We target supernovae and optical transients brighter than 20.5m for classification. Science targets are selected for follow-up based on the PESSTO science goal of extending knowledge of the extremes of the supernova population. We use standard EFOSC2 set-ups providing spectra with resolutions of 13-18 Å between 3345-9995 Å. A subset of the brighter science targets are selected for SOFI spectroscopy with the blue and red grisms (0.935-2.53 μm and resolutions 23-33 Å) and imaging with broadband JHKs filters. Results. This first data release (SSDR1) contains flux calibrated spectra from the first year (April 2012-2013). A total of 221 confirmed supernovae were classified, and we released calibrated optical spectra and classifications publicly within 24 h of the data being taken (via WISeREP). The data in SSDR1 replace those released spectra. They have more reliable and quantifiable flux calibrations, correction for telluric absorption, and are made available in standard ESO Phase 3 formats. We estimate the absolute accuracy of the flux calibrations for EFOSC2 across the whole survey in SSDR1 to be typically ~15%, although a number of spectra will have less reliable absolute flux calibration because of weather and slit losses. Acquisition images for each spectrum are available which, in principle, can allow the user to refine the absolute flux calibration. The standard NIR reduction process does not produce high accuracy absolute spectrophotometry but synthetic photometry with accompanying JHKs imaging can improve this. Whenever possible, reduced SOFI images are provided to allow this. Conclusions. Future data releases will focus on improving the automated flux calibration of the data products. The rapid turnaround between discovery and classification and access to reliable pipeline processed data products has allowed early science papers in the first few months of the survey.

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Fractal dimension of optical cirrus in Stripe82

ABSTRACT The geometric characteristics of dust clouds provide important information on the physical processes that structure such clouds. One of such characteristics is the 2D fractal dimension D of a cloud projected on to the sky plane. In previous studies, which were mostly based on infrared (IR) data, the fractal dimension of individual clouds was found to be in a range from 1.1 to 1.7 with a preferred value of 1.2–1.4. In this work, we use data from Stripe82 of the Sloan Digital Sky Survey to measure the fractal dimension of the cirrus clouds. This is done here for the first time for optical data with significantly better resolution as compared to IR data. To determine the fractal dimension, the perimeter-area method is employed. We also consider IR (IRAS and Herschel) counterparts of the corresponding optical fields to compare the results between the optical and IR. We find that the averaged fractal dimension across all clouds in the optical is $\langle D \rangle =1.69^{+0.05}_{-0.05}$ which is significantly larger than the fractal dimension of its IR counterparts $\langle D\rangle =1.38^{+0.07}_{-0.06}$. We examine several reasons for this discrepancy (choice of masking and minimal contour level, image and angular resolution, etc.) and find that for approximately half of our fields the different angular resolution (point spread function) of the optical and IR data can explain the difference between the corresponding fractal dimensions. For the other half of the fields, the fractal dimensions of the IR and visual data remain inconsistent, which can be associated with physical properties of the clouds, but further physical simulations are required to prove it.

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Characterization of Exoplanet Atmospheres with the Optical Coronagraph on WFIRST

Wide-Field Infrared Survey Telescope (WFIRST)-CGI is a NASA technology demonstration mission that is charged with demonstrating key technologies for future exo-Earth imaging missions in space. In the process, it will obtain images and low-resolution spectra of a handful to a dozen extrasolar planets and possibly protoplanetary disks. Its unprecedented contrast levels in the optical will provide astronomers’ with their first direct look at mature, Jupiter-sized planets at moderate separations. This paper addresses the question: what science can be done with such data? An analytic noise model, which is informed by the ongoing engineering developments, is used to compute maximum achievable signal-to-noise ratios and scientifically viable integration times for hypothetical star–planet systems, as well as to investigate the constraining power of various combinations of WFIRST-CGI photometric and spectral observations. This work introduces two simple models for planetary geometric albedos, which are inspired largely by the solar system’s gas giants. The first planet model is a hybrid Jupiter–Neptune model, which separately treats the short and long wavelengths where chromophores and methane dominate absorption, respectively. The second planet model fixes cloud and haze properties in CoolTLusty to match Jupiter’s albedo spectrum, it then perturbs only the metallicity. MCMC retrievals performed on simulated observations are used to assess the precision with which planet model parameters can be measured subject to different exposure times and observing cases. Planet radius is recovered within ±15% for all observing cases with both the hybrid model and the CoolTLusty metallicity grid. Fit results for both models’ parameterizations of geometric albedo spectra demonstrate that a rough indication of the metallicity or methane content should be possible for some WFIRST-CGI targets. We conclude that real observations will likely be able to differentiate between extreme cases using these models, but will lack the precision necessary to uncover subtle trends.

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Dark Energy Survey’s Observation Strategy, Tactics, and Exposure Scheduler

The Dark Energy Survey is a “stage III” dark energy experiment, performing an optical imaging survey to measure cosmological equation of state parameters using four independent methods. The scope and complexity of the survey, originally scheduled for 525 nights of observing spread over five years and combining a 5000 degree wide survey with a 10 field weekly time-domain survey, introduced complex strategic and tactical scheduling problems that needed to be addressed. We begin with an overview of the process used to develop DES strategy and tactics, from the inception of the project, to task forces that studied and developed strategy changes over the course of the survey, to the nightly pre-observing meeting in which immediate tactical issues were addressed. We then summarize the strategic choices made for each sub-survey, including metrics, scheduling considerations, choice of time domain fields and their sequences of exposures, and wide survey footprint and pointing layout choices. We go on to describe the detailed process that determined which specific exposures were taken at which specific times. We give a chronology of the strategic and tactical peculiarities of each year of observing, including the proposal and execution of a sixth year. We give an overview of obstac, the implementation of the DES scheduler used to simulate and evaluate strategic and tactical options, and automate exposure scheduling; and describe developments in obstac for use after DES. Appendices describe further details of data quality evaluation, t, and teff; airmass calculation; and modeling of the seeing and sky brightness. The significant corpus of DES data indicates that the simple scaling relations for seeing as a function of wavelength and airmass derived from the Kolmogorov turbulence model work adequately for exposure planning purposes: deviations from these relations are modest in comparison with short time-scale seeing variations.

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SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy

Abstract The Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ∼10 6 transient detections per night. For precision measurements of cosmological parameters and rates, it is critical to understand the detection efficiency, magnitude limits, artifact contamination levels, and biases in the selection and photometry. Here we rigorously test the LSST Difference Image Analysis (DIA) pipeline using simulated images from the Rubin Observatory LSST Dark Energy Science Collaboration Data Challenge (DC2) simulation for the Wide-Fast-Deep survey area. DC2 is the first large-scale (300 deg 2 ) image simulation of a transient survey that includes realistic cadence, variable observing conditions, and CCD image artifacts. We analyze ∼15 deg 2 of DC2 over a 5 yr time span in which artificial point sources from Type Ia supernova (SNIa) light curves have been overlaid onto the images. The magnitude limits per filter are u = 23.66 mag, g = 24.69 mag, r = 24.06 mag, i = 23.45 mag, z = 22.54 mag, and y = 21.62 mag. The artifact contamination levels are ∼90% of all detections, corresponding to ∼1000 artifacts deg –2 in g band, and falling to 300 deg –2 in y band. The photometry has biases <1% for magnitudes 19.5 < m < 23. Our DIA performance on simulated images is similar to that of the Dark Energy Survey difference-imaging pipeline on real images. We also characterize DC2 image properties to produce catalog-level simulations needed for distance bias corrections. We find good agreement between DC2 data and simulations for distributions of signal-to-noise ratio, redshift, and fitted light-curve properties. Applying a realistic SNIa cosmology analysis for redshifts z < 1, we recover the input cosmology parameters to within statistical uncertainties.

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THE PROPER MOTION OF PALOMAR 5

Palomar 5 (Pal 5) is a faint halo globular cluster associated with narrow tidal tails. It is a useful system to understand the process of tidal dissolution, as well as to constrain the potential of the Milky Way. A well-determined orbit for Pal 5 would enable detailed study of these open questions. We present here the first CCD-based proper motion measurement of Pal 5 obtained using SDSS as a first epoch and new Large Binocular Telescope/Large Binocular Camera (LBC) images as a second, giving a baseline of 15 years. We perform relative astrometry, using SDSS as a distortion-free reference, and images of the cluster and also of the Pal 5 stream for the derivation of the distortion correction for LBC. The reference frame is made up of background galaxies. We correct for differential chromatic refraction using relations obtained from SDSS colors as well as from flux-calibrated spectra, finding that the correction relations for stars and for galaxies are different. We obtain μ{sub α} = −2.296 ± 0.186 mas yr{sup −1} and μ{sub δ} = −2.257 ± 0.181 mas yr{sup −1} for the proper motion of Pal 5. We use this motion, and the publicly available code galpy, to model the disruption of Pal 5 in different Milky Way models consisting of a bulge, a disk, and a spherical dark matter halo. Our fits to the observed stream properties (streak and radial velocity gradient) result in a preference for a relatively large Pal 5 distance of around 24 kpc. A slightly larger absolute proper motion than what we measure also results in better matches but the best solutions need a change in distance. We find that a spherical Milky Way model, with V{sub 0} = 220 km s{sup −1} and V{sub 20} {sub kpc}, i.e., approximately at the apocenter of Pal 5, of 218 km s{sup −1}, can match the data well, at least for our choice of disk and bulge parametrization.

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Star cluster classification using deep transfer learning with PHANGS- HST

Currently available star cluster catalogues from the Hubble Space Telescope (HST) imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. Here, the time-consuming nature of this process has limited the production of reliable catalogues and thus also post-observation analysis. To address this problem, deep transfer learning has recently been used to create neural network models that accurately classify star cluster morphologies at production scale for nearby spiral galaxies (D ≲ 20 Mpc). Here, we use HST ultraviolet (UV)–optical imaging of over 20 000 sources in 23 galaxies from the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey to train and evaluate two new sets of models: (i) distance-dependent models, based on cluster candidates binned by galaxy distance (9–12, 14–18, and 18–24 Mpc), and (ii) distance-independent models, based on the combined sample of candidates from all galaxies. We find that the overall accuracy of both sets of models is comparable to previous automated star cluster classification studies (~60–80 per cent) and shows improvement by a factor of 2 in classifying asymmetric and multipeaked clusters from PHANGS-HST. Somewhat surprisingly, while we observe a weak negative correlation between model accuracy and galactic distance, we find that training separate models for the three distance bins does not significantly improve classification accuracy. We also evaluate model accuracy as a function of cluster properties such as brightness, colour, and spectral energy distribution (SED)-fit age. Based on the success of these experiments, our models will provide classifications for the full set of PHANGS-HST candidate clusters (N ~ 200 000) for public release.

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PARALLEL EVOLUTION OF QUASI-SEPARATRIX LAYERS AND ACTIVE REGION UPFLOWS

Persistent plasma upflows were observed with Hinode’s EUV Imaging Spectrometer (EIS) at the edges of active region (AR) 10978 as it crossed the solar disk. We analyze the evolution of the photospheric magnetic and velocity fields of the AR, model its coronal magnetic field, and compute the location of magnetic null-points and quasi-sepratrix layers (QSLs) searching for the origin of EIS upflows. Magnetic reconnection at the computed null points cannot explain all of the observed EIS upflow regions. However, EIS upflows and QSLs are found to evolve in parallel, both temporarily and spatially. Sections of two sets of QSLs, called outer and inner, are found associated to EIS upflow streams having different characteristics. The reconnection process in the outer QSLs is forced by a large-scale photospheric flow pattern, which is present in the AR for several days. We propose a scenario in which upflows are observed, provided that a large enough asymmetry in plasma pressure exists between the pre-reconnection loops and lasts as long as a photospheric forcing is at work. A similar mechanism operates in the inner QSLs; in this case, it is forced by the emergence and evolution of the bipoles between the two main AR polarities. Our findings provide strong support for the results from previous individual case studies investigating the role of magnetic reconnection at QSLs as the origin of the upflowing plasma. Furthermore, we propose that persistent reconnection along QSLs does not only drive the EIS upflows, but is also responsible for the continuous metric radio noise-storm observed in AR 10978 along its disk transit by the Nançay Radio Heliograph.

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Second data release of the Hyper Suprime-Cam Subaru Strategic Program

This paper presents the second data release of the Hyper Suprime-Cam Subaru Strategic Program, a wide-field optical imaging survey using the 8.2 m Subaru Telescope. We report the release includes data from 174 nights of observation through 2018 January. The Wide layer data cover about 300 deg$^2$ in all five broad-band filters ($grizy$) to the nominal survey exposure (10 min in $gr$ and 20 min in $izy$). Partially observed areas are also included in the release; about 1100 deg$^2$ is observed in at least one filter and one exposure. The median seeing in the i-band is ${0_{.}^{\prime \prime }6}$, demonstrating the superb image quality of the survey. The Deep (26 deg$^2$) and UltraDeep (4 deg$^2$) data are jointly processed and the UltraDeep-COSMOS field reaches an unprecedented depth of $i\sim 28$ at $5 \, \sigma$ for point sources. In addition to the broad-band data, narrow-band data are also available in the Deep and UltraDeep fields. This release includes a major update to the processing pipeline, including improved sky subtraction, PSF modeling, object detection, and artifact rejection. The overall data quality has been improved, but this release is not without problems; there is a persistent deblender problem as well as new issues with masks around bright stars. The user is encouraged to review the issue list before utilizing the data for scientific explorations. All the image products as well as catalog products are available for download. The catalogs are also loaded into a database, which provides an easy interface for users to retrieve data for objects of interest. In addition to these main data products, detailed galaxy shape measurements withheld from Public Data Release 1 (PDR1) are now available to the community. The shape catalog is drawn from the S16A internal release, which has a larger area than PDR1 (160 deg$^2$). All products are available at the data release site, https://hsc-release.mtk.nao.ac.jp/.

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Alignments in the orientation of radio jets from AGN and their host galaxies

It is well established that active galactic nuclei (AGNs) play an important role in the evolution of galaxies. These AGNs can be linked to the accretion processes onto massive black holes and past merger events in their host galaxies, which may lead to different alignments of the jets with respect to the host galaxies. This paper presents a study of the position angle (PA) differences between radio and optical images of radio-AGNs based on the second data release (DR2) of the Low Frequency Array (LOFAR) Two-Meter Sky Survey (LoTSS), theKarl G. JanskyVery Large Array Faint Images of the Radio Sky at Twenty-Centimeters Survey (FIRST), the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, and the Sloan Digital Sky Survey (SDSS). We assessed PA measurement biases in the data and classified the radio-AGNs based on the radio luminosity and infrared colour from the Wide-field Infrared Survey Explorer (WISE). This resulted in the largest sample of radio AGNs with reliable radio and optical PA measurements published to date, with a total of 3682 AGNs. The PA difference (dPA) distributions for the radio-AGN sample show a prominent minor-axis alignment tendency. Based on some simple assumptions, we simulated the projection effect to estimate the intrinsic jet-galaxy alignment. The observed dPA distribution can be well described by a two-component jet-alignment model in which one component is more aligned with the minor axis of the host galaxy than the other. The fitting results indicate that the jet alignment is dependent on radio luminosity and the shape of the host galaxies, with the jets being more likely to be aligned with the minor axis of the galaxy for lower radio luminosity and for optically more elongated radio-AGNs. The minor-axis alignment of the entire sample may suggest a coherent accretion model present in most AGN host galaxies, while a considerable number of luminous radio-AGNs with massive host galaxies might have undergone accretion – according to the chaotic model – or past merger events.

Astronomy & Astrophysics↗

Global energetics of solar flares. III. Nonthermal energies

This study entails the third part of a global flare energetics project, in which Ramaty High-Energy Solar Spectroscopic Imager (RHESSI) data of 191 M and X-class flare events from the first 3.5 years of the Solar Dynamics Observatory mission are analyzed. We fit a thermal and a nonthermal component to RHESSI spectra, yielding the temperature of the differential emission measure (DEM) tail, the nonthermal power-law slope and flux, and the thermal/nonthermal cross-over energy e {sub co}. From these parameters, we calculate the total nonthermal energy E {sub nt} in electrons with two different methods: (1) using the observed cross-over energy e {sub co} as low-energy cutoff, and (2) using the low-energy cutoff e {sub wt} predicted by the warm thick-target bremsstrahlung model of Kontar et al. Based on a mean temperature of T {sub e} = 8.6 MK in active regions, we find low-energy cutoff energies of e{sub wt}=6.2±1.6 keV for the warm-target model, which is significantly lower than the cross-over energies e{sub co}=21±6 keV. Comparing with the statistics of magnetically dissipated energies E {sub mag} and thermal energies E {sub th} from the two previous studies, we find the following mean (logarithmic) energy ratios with the warm-target model: E{sub nt}=0.41 E{sub mag}, E{sub th}=0.08 E{sub mag}, and E{sub th}=0.15 E{sub nt}. The total dissipated magnetic energy exceeds the thermal energy in 95% and the nonthermal energy in 71% of the flare events, which confirms that magnetic reconnection processes are sufficient to explain flare energies. The nonthermal energy exceeds the thermal energy in 85% of the events, which largely confirms the warm thick-target model.

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Actuated Hybrid Mirror Telescope

The figure depicts the planned Actuated Hybrid Mirror Telescope (AHMT), which is intended to demonstrate a new approach to the design and construction of wide-aperture spaceborne telescopes for astronomy and Earth science. This technology is also appropriate for Earth-based telescopes. The new approach can be broadly summarized as using advanced lightweight mirrors that can be manufactured rapidly at relatively low cost. More specifically, it is planned to use precise replicated metallic nanolaminate mirrors to obtain the required high-quality optical finishes. Lightweight, dimensionally stable silicon carbide (SiC) structures will support the nanolaminate mirrors in the required surface figures. To enable diffraction- limited telescope performance, errors in surface figures will be corrected by use of mirror-shape-control actuators that will be energized, as needed, by a wave-front-sensing and control system. The concepts of nanolaminate materials and mirrors made from nanolaminate materials were discussed in several previous NASA Tech Briefs articles. Nanolaminates constitute a relatively new class of materials that can approach theoretical limits of stiffness and strength. Nanolaminate mirrors are synthesized by magnetron sputter deposition of metallic alloys and/or compounds on optically precise master surfaces to obtain optical-quality reflector surfaces backed by thin shell structures. As an integral part of the deposition process, a layer of gold that will constitute the reflective surface layer is deposited first, eliminating the need for a subsequent and separate reflective-coating process. The crystallographic textures of the nanolaminate will be controlled to optimize the performance of the mirror. The entire deposition process for making a nanolaminate mirror takes less than 100 hours, regardless of the mirror diameter. Each nanolaminate mirror will be bonded to its lightweight SiC supporting structure. The lightweight nanolaminate mirrors and SiC supporting structures will be fabricated from reusable master molds. The mirror-shape-control actuators will be low-power, high-capacitance lead magnesium niobate electrostrictive actuators that will be embedded in the SiC structures. The mode of operation of these actuators will be such that once power was applied, they will change in length and once power was removed, they will maintain dimensional stability to nanometer precision. This mode of operation will enable the use of low-power, minimally complex electronic control circuitry. The wave-front-sensing and control system will be designed and built according to a two-stage architecture. The first stage will be implemented by a Shack- Hartmann (SH) sensor subsystem, which will provide a large capture range. The second, higher-performance stage will be implemented by an image-based wave-front-sensing subsystem that will include a phase-retrieval camera (PRC), and will utilize phase retrieval and other techniques to measure wavefront error directly. Phase retrieval is a process in which multiple images of an unresolved object are iterated to estimate the phase of the optical system that acquired the images. The combination of SH and phase-retrieval sensors will afford the virtues of both a dynamic range of 105 and an accuracy of <10 nm.

Hickey, Gregory↗

A SPATIALLY RESOLVED STUDY OF THE SYNCHROTRON EMISSION AND TITANIUM IN TYCHO’S SUPERNOVA REMNANT USING NuSTAR

We report results from deep observations (∼750 ks) of Tycho's supernova remnant (SNR) with NuSTAR. Using these data, we produce narrow-band images over several energy bands to identify the regions producing the hardest X-rays and to search for radioactive decay line emission from {sup 44}Ti. We find that the hardest (>10 keV) X-rays are concentrated in the southwest of Tycho, where recent Chandra observations have revealed high emissivity “stripes” associated with particles accelerated to the knee of the cosmic-ray spectrum. We do not find evidence of {sup 44}Ti, and we set limits on its presence and distribution within the SNR. These limits correspond to an upper-limit {sup 44}Ti mass of M{sub 44} < 2.4 × 10{sup −4} M{sub ⊙} for a distance of 2.3 kpc. We perform a spatially resolved spectroscopic analysis of 66 regions across Tycho. We map the best-fit rolloff frequency of the hard X-ray spectra, and we compare these results to measurements of the shock expansion and ambient density. We find that the highest energy electrons are accelerated at the lowest densities and in the fastest shocks, with a steep dependence of the rolloff frequency with shock velocity. Such a dependence is predicted by models where the maximum energy of accelerated electrons is limited by the age of the SNR rather than by synchrotron losses, but this scenario requires far lower magnetic field strengths than those derived from observations in Tycho. One way to reconcile these discrepant findings is through shock obliquity effects, and future observational work is necessary to explore the role of obliquity in the particle acceleration process.

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Machine Learning Algorithms for Matching Theories, Simulations, and Observations in Cosmology (Final Project)

The search for simple and elegant equations to explain and predict observable natural phenomena has been a driving force in scientific theory for several centuries. The great successes of Newton's laws, Maxwell's equations, the Schrodinger equation, and the theory of General Relativity have encouraged this perspective, and perhaps a beautiful equation comprising a “theory of everything” remains to be discovered. But now scientists are grappling with systems of ever-increasing complexity, fraught with nonlinearity, and with the quantities of interest often only indirectly observed. Nature may resist a simple description, and the most important discoveries of the next century may be complex theories with countless variables and parameters. The era of big data opens up a promising new approach to scientific discovery in this setting. The predictions of modern theories, even if complex or nonlinear, can be examined through detailed and computationally-intensive simulations that take days or weeks to run and fill petabytes of disk space. The upcoming generation of scientific instruments will provide petabytes of observations at unprecedented resolution and depth. The challenge is to compare data to simulations so as to test theories and identify those that best match the observations. The data are numerous and rich but are subject to noise and various systematic biases. The simulations are large and detailed but are so costly that the effective sample size is small. Moreover, the mapping from data to simulation to the parameters of interest is typically complicated and ill-conditioned. Although these challenges, and the solutions we propose, apply across the sciences, we will ground our efforts by focusing on cosmology. Here, we are truly entering the era of big data in several senses. Ever larger experiments survey larger and larger cosmological volumes, resulting in enormous amounts of pixel data to process and extract the information of cosmological interest. These include large imaging surveys, which collect all the light in broad wavelength ranges over significant fractions of the sky, and spectroscopic surveys, which measure the light as a function of wavelength to map out 3D distances. These experiments are designed to shed light on the big unanswered questions in cosmology. Distilling the petabytes of data into observed quantities for comparison with theory is a daunting task. But these large experiments do not only result in large amounts of data to analyze: if we wish to compare to theories of physics, then we need increasingly extensive predictions for the observed quantities as well, which requires ever-larger cosmological simulations that take substantial -- and at times prohibitive -- computational resources to produce. Our goal is to develop statistical and machine learning methods for using observed and simulated data to advance machine learning with applications cosmology. In particular, we focus our research efforts on the following tasks: The challenge for automated science is that it is computationally impossible and statistically dangerous to consider every possible model in order to find the best one. We will develop Bayesian Optimization based active-learning methods that accelerate both the execution of the simulations and the search for best-fitting parameters. The key idea is to make the simulations adaptive -- across resolutions, time, and parameters -- using the data to search as the simulation runs; Most ML methods operate on simple finite dimensional feature vectors. However, many cosmology and other science applications require ML methods that can operate on more complex objects as inputs or outputs such as functions, distributions, or sets and point clouds. Our goal is to develop efficient ML methods for this problem and demonstrate their applicability in Cosmology, Astrophysics, and other science problems.

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HETDEX Public Source Catalog 1: 220 K Sources Including Over 50 K Ly$α$ Emitters from an Untargeted Wide-area Spectroscopic Survey*

We present the first publicly released catalog of sources obtained from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). HETDEX is an integral field spectroscopic survey designed to measure the Hubble expansion parameter and angular diameter distance at 1.88 < z < 3.52 by using the spatial distribution of more than a million Lyα-emitting galaxies over a total target area of 540 deg 2 . The catalog comes from contiguous fiber spectra coverage of 25 deg 2 of sky from 2017 January through 2020 June, where object detection is performed through two complementary detection methods: one designed to search for line emission and the other a search for continuum emission. The HETDEX public release catalog is dominated by emission-line galaxies and includes 51,863 Ly$α$-emitting galaxy (LAE) identifications and 123,891 [O ii]-emitting galaxies at z < 0.5. Also included in the catalog are 37,916 stars, 5274 low-redshift (z < 0.5) galaxies without emission lines, and 4976 active galactic nuclei. The catalog provides sky coordinates, redshifts, line identifications, classification information, line fluxes, [O ii] and Ly$α$ line luminosities where applicable, and spectra for all identified sources processed by the HETDEX detection pipeline. Extensive testing demonstrates that HETDEX redshifts agree to within Δz < 0.02, 96.1% of the time to those in external spectroscopic catalogs. We measure the photometric counterpart fraction in deep ancillary Hyper Suprime-Cam imaging and find that only 55.5% of the LAE sample has an r-band continuum counterpart down to a limiting magnitude of r ~ 26.2 mag (AB) indicating that an LAE search of similar sensitivity to HETDEX with photometric preselection would miss nearly half of the HETDEX LAE catalog sample. Data access and details about the catalog can be found online at http://hetdex.org/. A copy of the catalogs presented in this work (Version 3.2) is available to download at Zenodo doi:10.5281/zenodo.7448504.

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Eight new luminous z ≥ 6 quasars discovered via SED model fitting of VISTA, WISE and Dark Energy Survey Year 1 observations

We present the discovery and spectroscopic confirmation with the ESO NTT and Gemini South telescopes of eight new 6.0 < z < 6.5 quasars with z$_{AB}$ < 21.0. These quasars were photometrically selected without any star-galaxy morphological criteria from 1533 deg$^{2}$ using SED model fitting to photometric data from the Dark Energy Survey (g, r, i, z, Y), the VISTA Hemisphere Survey (J, H, K) and the Wide-Field Infrared Survey Explorer (W1, W2). The photometric data was fitted with a grid of quasar model SEDs with redshift dependent Lyman-{\alpha} forest absorption and a range of intrinsic reddening as well as a series of low mass cool star models. Candidates were ranked using on a SED-model based $\chi^{2}$-statistic, which is extendable to other future imaging surveys (e.g. LSST, Euclid). Our spectral confirmation success rate is 100% without the need for follow-up photometric observations as used in other studies of this type. Combined with automatic removal of the main types of non-astrophysical contaminants the method allows large data sets to be processed without human intervention and without being over run by spurious false candidates. We also present a robust parametric redshift estimating technique that gives comparable accuracy to MgII and CO based redshift estimators. We find two z $\sim$ 6.2 quasars with HII near zone sizes < 3 proper Mpc which could indicate that these quasars may be young with ages < 10$^6$ - 10$^7$ years or lie in over dense regions of the IGM. The z = 6.5 quasar VDESJ0224-4711 has J$_{AB}$ = 19.75 is the second most luminous quasar known with z > 6.5.

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LoCuSS: THE SLOW QUENCHING OF STAR FORMATION IN CLUSTER GALAXIES AND THE NEED FOR PRE-PROCESSING

We present a study of the spatial distribution and kinematics of star-forming galaxies in 30 massive clusters at 0.15 < z < 0.30, combining wide-field Spitzer 24 μm and GALEX near-ultraviolet imaging with highly complete spectroscopy of cluster members. The fraction (f{sub SF}) of star-forming cluster galaxies rises steadily with cluster-centric radius, increasing fivefold by 2r{sub 200}, but remains well below field values even at 3r{sub 200}. This suppression of star formation at large radii cannot be reproduced by models in which star formation is quenched in infalling field galaxies only once they pass within r{sub 200} of the cluster, but is consistent with some of them being first pre-processed within galaxy groups. Despite the increasing f{sub SF}-radius trend, the surface density of star-forming galaxies actually declines steadily with radius, falling ∼15× from the core to 2r{sub 200}. This requires star formation to survive within recently accreted spirals for 2–3 Gyr to build up the apparent over-density of star-forming galaxies within clusters. The velocity dispersion profile of the star-forming galaxy population shows a sharp peak of 1.44 σ{sub ν} at 0.3r{sub 500}, and is 10%–35% higher than that of the inactive cluster members at all cluster-centric radii, while their velocity distribution shows a flat, top-hat profile within r{sub 500}. All of these results are consistent with star-forming cluster galaxies being an infalling population, but one that must also survive ∼0.5–2 Gyr beyond passing within r{sub 200}. By comparing the observed distribution of star-forming galaxies in the stacked caustic diagram with predictions from the Millennium simulation, we obtain a best-fit model in which star formation rates decline exponentially on quenching timescales of 1.73 ± 0.25 Gyr upon accretion into the cluster.

79 ASTRONOMY AND ASTROPHYSICS↗

HerMES: ALMA imaging of Herschel-selected dusty star-forming galaxies

The Herschel Multi-tiered Extragalactic Survey (HerMES) has identified large numbers of dusty star-forming galaxies (DSFGs) over a wide range in redshift. A detailed understanding of these DSFGs is hampered by the limited spatial resolution of Herschel. We present 870 μm 0.″45 resolution imaging obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) of a sample of 29 HerMES DSFGs that have far-infrared (FIR) flux densities that lie between the brightest of sources found by Herschel and fainter DSFGs found via ground-based surveys in the submillimeter region. The ALMA imaging reveals that these DSFGs comprise a total of 62 sources (down to the 5σ point-source sensitivity limit in our ALMA sample; σ≈0.2 mJy). Optical or near-infrared imaging indicates that 36 of the ALMA sources experience a significant flux boost from gravitational lensing (μ>1.1), but only six are strongly lensed and show multiple images. We introduce and make use of uvmcmcfit, a general-purpose and publicly available Markov chain Monte Carlo visibility-plane analysis tool to analyze the source properties. Combined with our previous work on brighter Herschel sources, the lens models presented here tentatively favor intrinsic number counts for DSFGs with a break near 8 mJy at 880 μm and a steep fall-off at higher flux densities. Nearly 70% of the Herschel sources break down into multiple ALMA counterparts, consistent with previous research indicating that the multiplicity rate is high in bright sources discovered in single-dish submillimeter or FIR surveys. The ALMA counterparts to our Herschel targets are located significantly closer to each other than ALMA counterparts to sources found in the LABOCA ECDFS Submillimeter Survey. Theoretical models underpredict the excess number of sources with small separations seen in our ALMA sample. The high multiplicity rate and small projected separations between sources seen in our sample argue in favor of interactions and mergers plausibly driving both the prodigious emission from the brightest DSFGs as well as the sharp downturn above S{sub 880}=8 mJy.

79 ASTRONOMY AND ASTROPHYSICS↗