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<jats:title>Abstract</jats:title> <jats:p>We present new measurements of rest-UV luminosity functions and angular correlation functions from 4,100,221 galaxies at <jats:italic>z</jats:italic> ∼ 2–7 identified in the Subaru/Hyper Suprime-Cam survey and CFHT Large Area <jats:italic>U</jats:italic>-band Survey. The obtained luminosity functions at <jats:italic>z</jats:italic> ∼ 4–7 cover a very wide UV luminosity range of ∼<jats:inline-formula> <jats:tex-math> <?CDATA $0.002\mbox{--}2000{L}_{\mathrm{UV}}^{* }$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>0.002</mml:mn> <mml:mo>–</mml:mo> <mml:mn>2000</mml:mn> <mml:msubsup> <mml:mrow> <mml:mi>L</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>UV</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>*</mml:mo> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjsac3dfcieqn1.gif" xlink:type="simple" /> </jats:inline-formula> combined with previous studies, confirming that the dropout luminosity function is a superposition of the active galactic nucleus (AGN) luminosity function dominant at <jats:italic>M</jats:italic> <jats:sub>UV</jats:sub> ≲ −24 mag and the galaxy luminosity function dominant at <jats:italic>M</jats:italic> <jats:sub>UV</jats:sub> ≳ −22 mag, consistent with galaxy fractions based on 1037 spectroscopically identified sources. Galaxy luminosity functions estimated from the spectroscopic galaxy fractions show the bright-end excess beyond the Schechter function at ≳2<jats:italic>σ</jats:italic> levels, possibly made by inefficient mass quenching, low dust obscuration, and/or hidden AGN activity. By analyzing the correlation functions at <jats:italic>z</jats:italic> ∼ 2–6 with HOD models, we find a weak redshift evolution (within 0.3 dex) of the ratio of the star formation rate (SFR) to the dark matter accretion rate, <jats:inline-formula> <jats:tex-math> <?CDATA $\mathrm{SFR}/{\dot{M}}_{{\rm{h}}}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi>SFR</mml:mi> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:msub> <mml:mrow> <mml:mover accent="true"> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>̇</mml:mo> </mml:mrow> </mml:mover> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">h</mml:mi> </mml:mrow> </mml:msub> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjsac3dfcieqn2.gif" xlink:type="simple" /> </jats:inline-formula>, indicating the almost constant star formation efficiency at <jats:italic>z</jats:italic> ∼ 2–6, as suggested by our earlier work at <jats:italic>z</jats:italic> ∼ 4–7. Meanwhile, the ratio gradually increases with decreasing redshift at <jats:italic>z</jats:italic> &lt; 5 within 0.3 dex, which quantitatively reproduces the cosmic SFR density evolution, suggesting that the redshift evolution is primarily driven by the increase of the halo number density due to the structure formation, and the decrease of the accretion rate due to the cosmic expansion. Extrapolating this calculation to higher redshifts assuming the constant efficiency suggests a rapid decrease of the SFR density at <jats:italic>z</jats:italic> &gt; 10 with ∝ 10<jats:sup>−0.5(1+<jats:italic>z</jats:italic>)</jats:sup>, which will be directly tested with the James Webb Space Telescope.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Understanding the escape of Lyman continuum (LyC) and Ly<jats:italic>α</jats:italic> photons from giant molecular clouds (GMCs) is crucial if we are to study the reionization of the universe and to interpret spectra of observed galaxies at high redshift. To this end, we perform high-resolution, radiation-magnetohydrodynamic simulations of GMCs with self-consistent star formation and stellar feedback. We find that a significant fraction (15%–70%) of ionizing radiation escapes from the simulated GMCs with different masses (10<jats:sup>5</jats:sup> and 10<jats:sup>6</jats:sup> <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub>), as the clouds are dispersed within about 2–5 Myr from the onset of star formation. The fraction of LyC photons leaked is larger when the GMCs are less massive, metal poor, less turbulent, and less dense. The most efficient leakage of LyC radiation occurs when the total star formation efficiency of a GMC is about 20%. The escape of Ly<jats:italic>α</jats:italic> shows a trend similar to that of LyC photons, except that the fraction of Ly<jats:italic>α</jats:italic> photons escaping from the GMCs is larger (<jats:inline-formula> <jats:tex-math> <?CDATA ${f}_{\mathrm{Ly}\alpha }\approx {f}_{900}^{0.27}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>f</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>Ly</mml:mi> <mml:mi>α</mml:mi> </mml:mrow> </mml:msub> <mml:mo>≈</mml:mo> <mml:msubsup> <mml:mrow> <mml:mi>f</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>900</mml:mn> </mml:mrow> <mml:mrow> <mml:mn>0.27</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjsac426dieqn1.gif" xlink:type="simple" /> </jats:inline-formula>) and that a GMC with strong turbulence shows larger <jats:italic>f</jats:italic> <jats:sub>Ly<jats:italic>α</jats:italic> </jats:sub>. The simulated GMCs show a characteristic velocity separation of Δ<jats:italic>v</jats:italic> ≈ 120 km s<jats:sup>−1</jats:sup> in the time-averaged emergent Ly<jats:italic>α</jats:italic> spectra, suggesting that Ly<jats:italic>α</jats:italic> could be useful to infer the kinematics of the interstellar and circumgalactic medium. We show that Ly<jats:italic>α</jats:italic> luminosities are a useful indicator of the LyC escape, provided the number of LyC photons can be deduced through stellar population modeling. Finally, we find that the correlations between the escape fractions of Ly<jats:italic>α</jats:italic>, ultraviolet photons at 1500 Å, and the Balmer <jats:italic>α</jats:italic> line are weak.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Low-frequency radio observatories are reaching unprecedented levels of sensitivity in an effort to detect the 21 cm signal from the Cosmic Dawn. High precision is needed because the expected signal is overwhelmed by foreground contamination, largely from so-called diffuse emission—a nonlocalized glow comprising Galactic synchrotron emission and radio galaxies. The impact of this diffuse emission on observations may be better understood through detailed simulations, which evaluate the Radio Interferometry Measurement Equation (RIME) for a given instrument and sky model. Evaluating the RIME involves carrying out an integral over the full sky, which is naturally discretized for point sources but must be approximated for diffuse emission. The choice of integration scheme can introduce errors that must be understood and isolated from the instrumental effects under study. In this paper, we present several analytically defined patterns of unpolarized diffuse sky emission for which the RIME integral is manageable, yielding closed-form or series visibility functions. We demonstrate the usefulness of these RIME solutions for validation by comparing them to simulated data and show that the remaining differences behave as expected with varied sky resolution and baseline orientation and length.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We examine statistics of magnetic-field vector components to explore how intermittency evolves from near-Sun plasma to radial distances as large as 10 au. Statistics entering the analysis include autocorrelation, magnetic structure functions of the order of <jats:italic>n</jats:italic> (SF<jats:sub> <jats:italic>n</jats:italic> </jats:sub>), and scale-dependent kurtosis (SDK), each grouped in ranges of heliocentric distance. The Goddard Space Flight Center Space Physics Data Facility provides magnetic-field measurements for resolutions of 6.8 ms for Parker Solar Probe, 6 s for Helios, and 1.92 s for Voyager 1. We compute SF<jats:sub>2</jats:sub> to determine the scales encompassing the inertial range and examine SDK to investigate the degree of non-Gaussianity. Autocorrelations are used to resolve correlation scales. Correlation lengths and ion inertial lengths provide an estimate of effective Reynolds number (R<jats:sub>e</jats:sub>). Variation in R<jats:sub>e</jats:sub> allows us to examine for the first time the relationship between SDK and R<jats:sub>e</jats:sub> in an interplanetary plasma. A conclusion from this observed relationship is that regions with lower R<jats:sub>e</jats:sub> at a fixed physical scale have on average lower kurtosis, implying less intermittent behavior. Kolmogorov refined similarity hypothesis is applied to magnetic SF<jats:sub> <jats:italic>n</jats:italic> </jats:sub> and kurtosis to calculate intermittency parameters and fractal scaling in the inertial range. A refined Voyager 1 magnetic-field data set is generated.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Both NASA’s Solar Dynamics Observatory (SDO) and the JAXA/NASA Hinode mission include spectropolarimetric instruments designed to measure the photospheric magnetic field. SDO’s Helioseismic and Magnetic Imager (HMI) emphasizes full-disk, high-cadence, and good-spatial-resolution data acquisition while Hinode’s Solar Optical Telescope Spectro-Polarimeter (SOT-SP) focuses on high spatial resolution and spectral sampling at the cost of a limited field of view and slower temporal cadence. This work introduces a deep-learning system, named the Synthetic Inversion Approximation (SynthIA), that can enhance both missions by capturing the best of each instrument’s characteristics. We use SynthIA to produce a new magnetogram data product, the Synthetic Hinode Pipeline (SynodeP), that mimics magnetograms from the higher-spectral-resolution Hinode/SOT-SP pipeline, but is derived from full-disk, high-cadence, and lower-spectral-resolution SDO/HMI Stokes observations. Results on held-out data show that SynodeP has good agreement with the Hinode/SOT-SP pipeline inversions, including magnetic fill fraction, which is not provided by the current SDO/HMI pipeline. SynodeP further shows a reduction in the magnitude of the 24 hr oscillations present in the SDO/HMI data. To demonstrate SynthIA’s generality, we show the use of SDO/Atmospheric Imaging Assembly data and subsets of the HMI data as inputs, which enables trade-offs between fidelity to the Hinode/SOT-SP inversions, number of observations used, and temporal artifacts. We discuss possible generalizations of SynthIA and its implications for space-weather modeling. This work is part of the NASA Heliophysics DRIVE Science Center at the University of Michigan under grant NASA 80NSSC20K0600E, and will be open-sourced.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In compact stellar triple systems, an evolved tertiary star can overflow its Roche lobe around the inner binary. Subsequently, the tertiary star can transfer mass to the inner binary in a stable manner, or Roche lobe overflow (RLOF) can be unstable and lead to common-envelope (CE) evolution. In the latter case, the inner binary enters the extended envelope of the tertiary star and spirals in toward the donor’s core, potentially leading to mergers or ejections. Although studied in detail for individual systems, a comprehensive statistical view on the various outcomes of triple RLOF is lacking. Here, we carry out 10<jats:sup>5</jats:sup> population synthesis simulations of tight triples, self-consistently taking into account stellar evolution, binary interactions, and gravitational dynamics. Also included are prescriptions for the long-term evolution of stable triple mass transfer, and triple CE evolution. Although simple and ignoring hydrodynamic effects, these prescriptions allow for a qualitative statistical study. We find that triple RLOF occurs in ∼0.06% of all triple systems. Of these 0.06%, ∼64% of cases lead to stable mass transfer, and ∼36% to triple CE evolution. Triple CE is most often (∼76%) followed by one or multiple mergers in short succession, most likely an inner binary merger of two main-sequence stars. Other outcomes of triple CE are a binary+single system (∼23%, most of which do not involve exchange interactions), and a stable triple (∼1%). We also estimate the rate of type Ia supernovae involving white dwarf mergers following triple RLOF, but find only a negligible contribution.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>By combining spectroscopic data from the LAMOST DR7, Sloan Digital Sky Survey (SDSS) DR12, and corrected photometric data from the Gaia EDR3, we apply the stellar color regression (SCR) method to recalibrate the SDSS Stripe 82 standard stars catalog of Ivezić et al. With a total number of about 30,000 spectroscopically targeted stars, we have mapped out the relatively large and strongly correlated photometric zero-point errors present in the catalog, ∼2.5% in the <jats:italic>u</jats:italic> band and ∼1% in the <jats:italic>griz</jats:italic> bands. Our study also confirms some small but significant magnitude dependence errors in the <jats:italic>z</jats:italic> band for some charge-coupled devices. Various tests show that we have achieved an internal precision of about 5 mmag in the <jats:italic>u</jats:italic> band and about 2 mmag in the <jats:italic>griz</jats:italic> bands, which is about five times better than previous results. We also apply the method to the latest version of the catalog (v4.2), and find modest systematic calibration errors of up to ∼1% along the R.A. direction and smaller errors along the decl. direction. The results demonstrate the power of the SCR method when combining spectroscopic data and Gaia photometry in breaking the 1% precision barrier of ground-based photometric surveys. Our work paves the way for the recalibration of the whole SDSS photometric survey and has important implications for the calibration of future surveys. Future implementations and improvements of the SCR method under different situations are also discussed.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We report the combined results of eight searches for strong gravitational lens systems in the full 5000 square degrees of Dark Energy Survey (DES) observations. The observations accumulated by the end of the third observing season fully covered the DES footprint in five filters (<jats:italic>grizY</jats:italic>), with an <jats:italic>i</jats:italic>-band limiting magnitude (at 10<jats:italic>σ</jats:italic>) of 23.44. In four searches, a list of potential candidates was identified using a color and magnitude selection from the object catalogs created from the first three observing seasons. Three other searches were conducted at the locations of previously identified galaxy clusters. Cutout images of potential candidates were then visually scanned using an object viewer. An additional set of candidates came from a data-quality check of a subset of the color–coadd tiles created from the full DES six-season data set. A short list of the most promising strong-lens candidates was then numerically ranked according to whether or not we judged them to be bona fide strong gravitational lens systems. These searches discovered a diverse set of 247 strong-lens candidate systems, of which 81 are identified for the first time. We provide the coordinates, magnitudes, and photometric properties of the lens and source objects, and an estimate of the Einstein radius for 81 new systems and 166 previously reported systems. This catalog will be of use for selecting interesting systems for detailed follow up, studies of galaxy cluster and group mass profiles, as well as a training/validation set for automated strong-lens searches.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We have updated and applied a convolutional neural network (CNN) machine-learning model to discover and characterize damped Ly<jats:italic>α</jats:italic> systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99% for spectra that have signal-to-noise ratios (S/N) above 5 per pixel. The classification accuracy is the rate of correct classifications. This accuracy remains above 97% for lower S/N ≈1 spectra. This CNN model provides estimations for redshift and H <jats:sc>i</jats:sc> column density with standard deviations of 0.002 and 0.17 dex for spectra with S/N above 3 pixel<jats:sup>−1</jats:sup>. Also, this DLA finder is able to identify overlapping DLAs and sub-DLAs. Further, the impact of different DLA catalogs on the measurement of baryon acoustic oscillations (BAO) is investigated. The cosmological fitting parameter result for BAO has less than 0.61% difference compared to analysis of the mock results with perfect knowledge of DLAs. This difference is lower than the statistical error for the first year estimated from the mock spectra: above 1.7%. We also compared the performances of the CNN and Gaussian Process (GP) models. Our improved CNN model has moderately 14% higher purity and 7% higher completeness than an older version of the GP code, for S/N &gt; 3. Both codes provide good DLA redshift estimates, but the GP produces a better column density estimate by 24% less standard deviation. A credible DLA catalog for the DESI main survey can be provided by combining these two algorithms.</jats:p>