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Using deep images from the Hyper Suprime-Cam (HSC) survey and taking advantage of its unprecedented weak lensing capabilities, we reveal a remarkably tight connection between the stellar mass distribution of massive central galaxies and their host dark matter halo mass. Massive galaxies with more extended stellar mass distributions tend to live in more massive dark matter haloes. We explain this connection with a phenomenological model that assumes, (1) a tight relation between the halo mass and the total stellar content in the halo, (2) that the fraction of in-situ and ex-situ mass at $r, 22 Pages, 12 Figures, 1 Table; Submitted to MNRAS. The model and Jupyter notebooks to reproduce the figures are available here: https://github.com/dr-guangtou/asap

Galaxies are complicated physical systems which obey complex scaling relationships; as a result, properties measured from broadband photometry are often highly correlated, degenerate, or both. Therefore, the accuracy of basic properties like stellar masses and star formation rates (SFRs) depend on the accuracy of many second-order galaxy properties, including star formation histories (SFHs), stellar metallicities, dust properties, and many others. Here, we re-assess measurements of galaxy stellar masses and SFRs using a 14-parameter physical model built in the Prospector Bayesian inference framework. We find that galaxies are ∼0.2 dex more massive and have ∼0.2 dex lower star formation rates than classic measurements. These measurements lower the observed cosmic star formation rate density and increase the observed buildup of stellar mass, finally bringing these two metrics into agreement at the factor-of-two level at 0.5 < z < 2.5.

We investigate the morphology of the stellar distribution in a sample of Milky Way (MW) like galaxies in the TNG50 simulation. Using a local in shell iterative method (LSIM) as the main approach, we explicitly show evidence of twisting (in about 52% of halos) and stretching (in 48% of them) in the real space. This is matched with the re-orientation observed in the eigenvectors of the inertia tensor and gives us a clear picture of having a re-oriented stellar distribution. We make a comparison between the shape profile of dark matter (DM) halo and stellar distribution and quite remarkably see that their radial profiles are fairly close, especially at small galactocentric radii where the stellar disk is located. This implies that the DM halo is somewhat aligned with stars in response to the baryonic potential. The level of alignment mostly decreases away from the center. We study the impact of substructures in the orbital circularity parameter. It is demonstrated that in some cases, far away substructures are counter-rotating compared with the central stars and may flip the sign of total angular momentum and thus the orbital circularity parameter. Truncating them above 150 kpc, however, retains the disky structure of the galaxy as per initial selection. Including the impact of substructures in the shape of stars, we explicitly show that their contribution is subdominant. Overlaying our theoretical results to the observational constraints from previous literature, we establish fair agreement., 29 pages, 21 figures, Accepted for publication in ApJ

For the past 150 years, the prevailing view of the local Interstellar Medium (ISM) was based on a peculiarity known as the Gould's Belt, an expanding ring of young stars, gas, and dust, tilted about 20$^\circ$ to the Galactic plane. Still, the physical relation between local gas clouds has remained practically unknown because the distance accuracy to clouds is of the same order or larger than their sizes. With the advent of large photometric surveys and the Gaia satellite astrometric survey this situation has changed. Here we report the 3-D structure of all local cloud complexes. We find a narrow and coherent 2.7 kpc arrangement of dense gas in the Solar neighborhood that contains many of the clouds thought to be associated with the Gould Belt. This finding is inconsistent with the notion that these clouds are part of a ring, disputing the Gould Belt model. The new structure comprises the majority of nearby star-forming regions, has an aspect ratio of about 1:20, and contains about 3 million solar masses of gas. Remarkably, the new structure appears to be undulating and its 3-D distribution is well described by a damped sinusoidal wave on the plane of the Milky Way, with an average period of about 2 kpc and a maximum amplitude of about 160 pc. Our results represent a first step in the revision of the local gas distribution and Galactic structure and offer a new, broader context to studies on the transformation of molecular gas into stars., Published in Nature on 7 January 2020. For data, interactive visualizations, and more information see: http://tinyurl.com/radwave (https://sites.google.com/cfa.harvard.edu/radcliffewave/)

The $100^\circ$-long thin stellar stream in the Milky Way halo, GD-1, has an ensemble of features that may be due to dynamical interactions. Using high-resolution MMT/Hectochelle spectroscopy we show that a spur of GD-1-like stars outside of the main stream are kinematically and chemically consistent with the main stream. In the spur, as in the main stream, GD-1 has a low intrinsic radial velocity dispersion, $\sigma_{V_r}\lesssim1\,\rm km\,s^{-1}$, is metal-poor, $\rm [Fe/H]\approx-2.3$, with little $\rm [Fe/H]$ spread and some variation in $\rm [\alpha/Fe]$ abundances, which point to a common globular cluster progenitor. At a fixed location along the stream, the median radial velocity offset between the spur and the main stream is smaller than $0.5\,\rm km\,s^{-1}$, comparable to the measurement uncertainty. A flyby of a massive, compact object can change orbits of stars in a stellar stream and produce features like the spur observed in GD-1. In this scenario, the radial velocity of the GD-1 spur relative to the stream constrains the orbit of the perturber and its current on-sky position to $\approx5,000\,\rm deg^2$. The family of acceptable perturber orbits overlaps the stellar and dark-matter debris of the Sagittarius dwarf galaxy in present-day position and velocity. This suggests that GD-1 may have been perturbed by a globular cluster or an extremely compact dark-matter subhalo formerly associated with Sagittarius., Comment: submitted to AAS Journals

Accurate distances to local molecular clouds are critical for understanding the star and planet formation process, yet distance measurements are often obtained inhomogeneously on a cloud-by-cloud basis. We have recently developed a method which combines stellar photometric data with Gaia DR2 parallax measurements in a Bayesian framework to infer the distances of nearby dust clouds to a typical accuracy of $\sim5\%$. After refining the technique to target lower latitudes and incorporating deep optical data from DECam in the southern Galactic plane, we have derived a catalog of distances to molecular clouds in Reipurth (2008, Star Formation Handbook, vols I and II) which contains a large fraction of the molecular material in the solar neighborhood. Comparison with distances derived from maser parallax measurements towards the same clouds shows our method produces consistent distances with $\lesssim10\%$ scatter for clouds across our entire distance spectrum (150 pc $-$ 2.5 kpc). We hope this catalog of homogeneous distances will serve as a baseline for future work., Accepted for publication in Astronomy & Astrophysics. Full catalog of distances available at https://doi.org/10.7910/DVN/07L7YZ or the CDS

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-zs at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2pdbl-pdbl2.6 redshift range that the Euclid mission will probe. We designed a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data was divided into two samples: one calibration sample for which photometry and redshifts were provided to the participants; and the validation sample, containing only the photometry to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates the sources they consider unfit for use in cosmological analyses. The performance of each method was assessed through a set of informative metrics, using cross-matched spectroscopic and highly-accurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, that is to say sources for which the photo-z deviates by more than 0.15(1pdbl+pdblz) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. We find that no machine-learning method provides good results in the regions of galaxy color-space that are sparsely populated by spectroscopic-redshifts, for example zpdbl> pdbl1. However they generally perform better than template-fitting methods at low redshift (zpdbl< pdbl0.7), indicating that template-fitting methods do not use all of the information contained in the photometry. We introduce metrics that quantify both photo-z precision and completeness of the samples (post-rejection), since both contribute to the final figure of merit of the science goals of the survey (e.g., cosmic shear from Euclid). Template-fitting methods provide the best results in these metrics, but we show that a combination of template-fitting results and machine-learning results with rejection criteria can outperform any individual method. On this basis, we argue that further work in identifying how to best select between machine-learning and template-fitting approaches for each individual galaxy should be pursued as a priority., GD and AG acknowledge the support from the Sinergia program of the Swiss National Science Foundation. Part of this work was supported by the German Deutsche Forschungsgemeinschaft, DFG project number Ts 17/2–1. MB acknowledges the financial contribution from the agreement ASI/INAF 2018-23-HH.0, Euclid ESA mission – Phase D and the INAF PRIN-SKA 2017 program 1.05.01.88.04. SC acknowledges the financial contribution from FFABR 2017. The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, in particular the Academy of Finland, the Agenzia Spaziale Italiana, the Belgian Science Policy, the Canadian Euclid Consortium, the Centre National d’Etudes Spatiales, the Deutsches Zentrum für Luft- und Raumfahrt, the Danish Space Research Institute, the Fundação para a Ciência e a Tecnologia, the Ministerio de Economia y Competitividad, the National Aeronautics and Space Administration, the Netherlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Romanian Space Agency, the State Secretariat for Education, Research and Innovation (SERI) at the Swiss Space Office (SSO), and the United Kingdom Space Agency. A complete and detailed list is available on the Euclid website (http://www.euclid-ec.org).

We develop a data-driven model to map stellar parameters (effective temperature, surface gravity and metallicity) accurately and precisely to broad-band stellar photometry. This model must, and does, simultaneously constrain the passband-specific dust reddening vector in the Milky Way. The model uses a neural network to learn the (de-reddened) absolute magnitude in one band and colors across many bands, given stellar parameters from spectroscopic surveys and parallax constraints from Gaia. To demonstrate the effectiveness of this approach, we train our model on a dataset with spectroscopic parameters from LAMOST, APOGEE and GALAH, Gaia parallaxes, and optical and near-infrared photometry from Gaia, Pan-STARRS~1, 2MASS and WISE. Testing the model on these datasets leads to an excellent fit and a precise - and by construction accurate - prediction of the color-magnitude diagrams in many bands. This flexible approach rigorously links spectroscopic and photometric surveys, and also results in an improved, stellar-temperature-dependent reddening vector. As such, it provides a simple and accurate method for predicting photometry in stellar evolutionary models. Our model will form a basis to infer stellar properties, distances and dust extinction from photometric data, which should be of great use in 3D mapping of the Milky Way. Our trained model may be obtained at https://doi.org/10.5281/zenodo.3902382., Comment: 30 pages, 13 figures. Revised version published in ApJ, including new Fig. 13

We leverage the 1 pc spatial resolution of the Leike et al. 2020 3D dust map to characterize the three-dimensional structure of nearby molecular clouds ($d \lesssim 400$ pc). We start by "skeletonizing" the clouds in 3D volume density space to determine their "spines," which we project on the sky to constrain cloud distances with $\approx 1\%$ uncertainty. For each cloud, we determine an average radial volume density profile around its 3D spine and fit the profiles using Gaussian and Plummer functions. The radial volume density profiles are well-described by a two-component Gaussian function, consistent with clouds having broad, lower-density outer envelopes and narrow, higher-density inner layers. The ratio of the outer to inner envelope widths is $\approx 3:1$. We hypothesize that these two components may be tracing a transition between atomic and diffuse molecular gas or between the unstable and cold neutral medium. Plummer-like models can also provide a good fit, with molecular clouds exhibiting shallow power-law wings with density, $n$, falling off like $n^{-2}$ at large radii. Using Bayesian model selection, we find that parameterizing the clouds' profiles using a single Gaussian is disfavored. We compare our results with 2D dust extinction maps, finding that the 3D dust recovers the total cloud mass from integrated approaches with fidelity, deviating only at higher levels of extinction ($A_V \gtrsim 2 - 3$ mag). The 3D cloud structure described here will enable comparisons with synthetic clouds generated in simulations, offering unprecedented insight into the origins and fates of molecular clouds in the interstellar medium., Comment: Published in ApJ. For data behind the figures see https://dataverse.harvard.edu/dataverse/3D_cloud_structure . For interactive gallery of local clouds see https://faun.rc.fas.harvard.edu/czucker/Paper_Figures/3D_Cloud_Topologies/gallery.html . Companion paper to Bialy et al. 2021 (arXiv:2109.09763). For press see https://www.cfa.harvard.edu/news/gigantic-cavity-space-sheds-new-light-how-stars-form

Inference of the physical properties of stellar populations from observed photometry and spectroscopy is a key goal in the study of galaxy evolution. In recent years the quality and quantity of the available data has increased, and there have been corresponding efforts to increase the realism of the stellar population models used to interpret these observations. Describing the observed galaxy spectral energy distributions in detail now requires physical models with a large number of highly correlated parameters. These models do not fit easily on grids and necessitate a full exploration of the available parameter space. We present prospector, a flexible code for inferring stellar population parameters from photometry and spectroscopy spanning UV through IR wavelengths. This code is based on forward modeling the data and Monte Carlo sampling the posterior parameter distribution, enabling complex models and exploration of moderate dimensional parameter spaces. We describe the key ingredients of the code and discuss the general philosophy driving the design of these ingredients. We demonstrate some capabilities of the code on several datasets, including mock and real data., Submitted to AASJournals. 27 pages, 5 appendices, and 8 figures including one interactive figure viewable in Adobe Reader or at https://prospect.readthedocs.io/en/latest/demo.html . Prospector is available at https://github.com/bd-j/prospector . Monte Carlo samples as well as code to perform the fits and produce the figures are available in a github repo at https://github.com/bd-j/exspect

Although photometric redshifts (photo-z's) are crucial ingredients for current and upcoming large-scale surveys, the high-quality spectroscopic redshifts currently available to train, validate, and test them are substantially non-representative in both magnitude and color. We investigate the nature and structure of this bias by tracking how objects from a heterogeneous training sample contribute to photo-z predictions as a function of magnitude and color, and illustrate that the underlying redshift distribution at fixed color can evolve strongly as a function of magnitude. We then test the robustness of the galaxy-galaxy lensing signal in 120 deg$^2$ of HSC-SSP DR1 data to spectroscopic completeness and photo-z biases, and find that their impacts are sub-dominant to current statistical uncertainties. Our methodology provides a framework to investigate how spectroscopic incompleteness can impact photo-z-based weak lensing predictions in future surveys such as LSST and WFIRST., Submitted to MNRAS; 21 pages, 12 figures

Nonparametric star formation histories (SFHs) have long promised to be the `gold standard' for galaxy spectral energy distribution (SED) modeling as they are flexible enough to describe the full diversity of SFH shapes, whereas parametric models rule out a significant fraction of these shapes {\it a priori}. However, this flexibility is not fully constrained even with high-quality observations, making it critical to choose a well-motivated prior. Here, we use the SED-fitting code \texttt{Prospector} to explore the effect of different nonparametric priors by fitting SFHs to mock UV-IR photometry generated from a diverse set of input SFHs. First, we confirm that nonparametric SFHs recover input SFHs with less bias and return more accurate errors than do parametric SFHs. We further find that, while nonparametric SFHs robustly recover the overall shape of the input SFH, the primary determinant of the size and shape of the posterior star formation rate (SFR) as a function of time is the choice of prior, rather than the photometric noise. As a practical demonstration, we fit the UV-IR photometry of $\sim$6000 galaxies from the GAMA survey and measure inter-prior scatters in mass (0.1 dex), SFR$_{100\; \mathrm{Myr}}$ (0.8 dex), and mass-weighted ages (0.2 dex), with the bluest star-forming galaxies showing the most sensitivity. An important distinguishing characteristic for nonparametric models is the characteristic timescale for changes in SFR(t). This difference controls whether galaxies are assembled in bursts or in steady-state star formation, corresponding respectively to (feedback-dominated/accretion-dominated) models of galaxy formation and to (larger/smaller) confidence intervals derived from SED-fitting. High-quality spectroscopy has the potential to further distinguish between these proposed models of SFR(t)., replacing with ApJ accepted version

We present a comprehensive study of the applications of the pixel color-magnitude diagram (pCMD) technique for measuring star formation histories (SFHs) and other stellar population parameters of galaxies, and demonstrate that the technique can also constrain distances. SFHs have previously been measured through either the modeling of resolved-star CMDs or of integrated-light SEDs, yet neither approach can easily be applied to galaxies in the "semi-resolved regime". The pCMD technique has previously been shown to have the potential to measure stellar populations and star formation histories in semi-resolved galaxies. Here we present Pixel Color-Magnitude Diagrams with Python (pcmdpy), a GPU-accelerated package that makes significant computational improvements to the original code and including more realistic physical models. These advances include the simultaneous fitting of distance, modeling a Gaussian metallicity-distribution function, and an observationally-motivated dust model. GPU-acceleration allows these more realistic models to be fit roughly 7x faster than the simpler models in the original code. We present results from a suite of mock tests, showing that with proper model assumptions, the code can simultaneously recover SFH, [Fe/H], distance, and dust extinction. Our results suggest the code, applied to observations with HST-like resolution, should constrain these properties with high precision within 10 Mpc and can be applied to systems out to as far as 100 Mpc. pCMDs open a new window to studying the stellar populations of many galaxies that cannot be readily studied through other means., 18 pages, 11 figures. Resubmitted to ApJ after addressing referee comments

We present a uniform catalog of accurate distances to local molecular clouds informed by the Gaia DR2 data release. Our methodology builds on that of Schlafly et al. (2014). First, we infer the distance and extinction to stars along sightlines towards the clouds using optical and near-infrared photometry. When available, we incorporate knowledge of the stellar distances obtained from Gaia DR2 parallax measurements. We model these per-star distance-extinction estimates as being caused by a dust screen with a 2-D morphology derived from Planck at an unknown distance, which we then fit for using a nested sampling algorithm. We provide updated distances to the Schlafly et al. (2014) sightlines towards the Dame et al. (2001) and Magnani et al. (1985) clouds, finding good agreement with the earlier work. For a subset of 27 clouds, we construct interactive pixelated distance maps to further study detailed cloud structure, and find several clouds which display clear distance gradients and/or are comprised of multiple components. We use these maps to determine robust average distances to these clouds. The characteristic combined uncertainty on our distances is approximately 5-6%, though this can be higher for clouds at farther distances, due to the limitations of our single-cloud model., Comment: Accepted for publication in The Astrophysical Journal. Many figures are interactive; click the link in the figure captions of the PDF to access, or see the online version of the published article

We present MINESweeper, a tool to measure stellar parameters by jointly fitting observed spectra and broadband photometry to model isochrones and spectral libraries. This approach enables the measurement of spectrophotometric distances, in addition to stellar parameters such as Teff, log(g), [Fe/H], [a/Fe], and radial velocity. MINESweeper employs a Bayesian framework and can easily incorporate a variety of priors, including Gaia parallaxes. Mock data are fit in order to demonstrate how the precision of derived parameters depends on evolutionary phase and SNR. We then fit a selection of data in order to validate the model outputs. Fits to a variety of benchmark stars including Procyon, Arcturus, and the Sun result in derived stellar parameters that are in good agreement with the literature. We then fit combined spectra and photometry of stars in the open and globular clusters M92, M13, M3, M107, M71, and M67. Derived distances, [Fe/H], [a/Fe], and log(g)-Teff, relations are in overall good agreement with literature values, although there are trends between metallicity and log(g), within clusters that point to systematic uncertainties at the ~0.1 dex level. Finally, we fit a large sample of stars from the H3 Spectroscopic Survey in which high quality Gaia parallaxes are also available. These stars are fit without the Gaia parallaxes so that the geometric parallaxes can serve as an independent test of the spectrophotometric distances. Comparison between the two reveals good agreement within their formal uncertainties after accounting for the Gaia zero point uncertainties., Comment: 20 pages, 14 figures, Accepted by ApJ

We present a new three-dimensional map of dust reddening, based on Gaia parallaxes and stellar photometry from Pan-STARRS 1 and 2MASS. This map covers the sky north of a declination of -30 degrees, out to a distance of several kiloparsecs. This new map contains three major improvements over our previous work. First, the inclusion of Gaia parallaxes dramatically improves distance estimates to nearby stars. Second, we incorporate a spatial prior that correlates the dust density across nearby sightlines. This produces a smoother map, with more isotropic clouds and smaller distance uncertainties, particularly to clouds within the nearest kiloparsec. Third, we infer the dust density with a distance resolution that is four times finer than in our previous work, to accommodate the improvements in signal-to-noise enabled by the other improvements. As part of this work, we infer the distances, reddenings and types of 799 million stars. We obtain typical reddening uncertainties that are ~30% smaller than those reported in the Gaia DR2 catalog, reflecting the greater number of photometric passbands that enter into our analysis. Our 3D dust map can be accessed at https://doi.org/10.7910/DVN/2EJ9TX or through the Python package "dustmaps," and can be queried interactively at http://argonaut.skymaps.info. Our catalog of stellar parameters can be accessed at https://doi.org/10.7910/DVN/AV9GXO., Comment: 43 pages, 19 figures

The origins of most stellar streams in the Milky Way are unknown. With improved proper motions provided by Gaia EDR3, we show that the orbits of 23 Galactic stellar streams are highly clustered in orbital phase space. Based on their energies and angular momenta, most streams in our sample can plausibly be associated with a specific (disrupted) dwarf galaxy host that brought them into the Milky Way. For eight streams we also identify likely globular cluster progenitors (four of these associations are reported here for the first time). Some of these stream progenitors are surprisingly far apart, displaced from their tidal debris by a few to tens of degrees. We identify stellar streams that appear spatially distinct, but whose similar orbits indicate they likely originate from the same progenitor. If confirmed as physical discontinuities, they will provide strong constraints on the mass-loss from the progenitor. The nearly universal ex-situ origin of existing stellar streams makes them valuable tracers of galaxy mergers and dynamical friction within the Galactic halo. Their phase-space clustering can be leveraged to construct a precise global map of dark matter in the Milky Way, while their internal structure may hold clues to the small-scale structure of dark matter in their original host galaxies., submitted to AAS Journals

We report the discovery of 15 stars in the H3 survey that lie, in projection, near the tip of the trailing gaseous Magellanic Stream (MS). The stars have Galactocentric velocities $< -155$ km s$^{-1}$, Galactocentric distances of $\approx 40$ to 80 kpc (increasing along the MS), and [Fe/H] consistent with that of stars in the Small Magellanic Cloud. These 15 stars comprise 94% (15 of 16) of the H3 observed stars to date that have $R_{GAL} > 37.5$ kpc, $-$350 km s$^{-1} < V_{GSR} < -155$ km s$^{-1}$, and are not associated with the Sagittarius Stream. They represent a unique portion of the Milky Way's outer halo phase space distribution function and confirm that unrelaxed structure is detectable even at radii where H3 includes only a few hundred stars. Due to their statistical excess, their close association with the MS and H I compact clouds in the same region, both in position and velocity space, and their plausible correspondence with tidal debris in a published simulation, we identify these stars as debris of past Magellanic Cloud encounters. These stars are evidence for a stellar component of the tidal debris field far from the Clouds themselves and provide unique constraints on the interaction., Accepted for publication in ApJL

The tidal disruption of the Sagittarius dwarf galaxy has generated a spectacular stream of stars wrapping around the entire Galaxy. We use data from $Gaia$ and the H3 Stellar Spectroscopic Survey to identify 823 high-quality Sagittarius members based on their angular momenta. The H3 Survey is largely unbiased in metallicity, and so our sample of Sagittarius members is similarly unbiased. Stream stars span a wide range in [Fe/H] from $-0.2$ to $\approx -3.0$, with a mean overall metallicity of $\langle$[Fe/H]$\rangle=-0.99$. We identify a strong metallicity-dependence to the kinematics of the stream members. At [Fe/H]$\gt -0.8$ nearly all members belong to the well-known cold ($\sigma_v \lt 20$ km/s) leading and trailing arms. At intermediate metallicities ($-1.9 \lt$[Fe/H]$\lt -0.8$) a significant population (24$\%$) emerges of stars that are kinematically offset from the cold arms. These stars also appear to have hotter kinematics. At the lowest metallicities ([Fe/H]$\lesssim-2$), the majority of stars (69$\%$) belong to this kinematically-offset diffuse population. Comparison to simulations suggests that the diffuse component was stripped from the Sagittarius progenitor at earlier epochs, and therefore resided at larger radius on average, compared to the colder metal-rich component. We speculate that this kinematically diffuse, low metallicity, population is the stellar halo of the Sagittarius progenitor system., Comment: 18 pages, 12 figures, 1 table. Submitted to ApJ

We present optimized source galaxy selection schemes for measuring cluster weak lensing (WL) mass profiles unaffected by cluster member dilution from the Subaru Hyper Suprime-Cam Strategic Survey Program (HSC-SSP). The ongoing HSC-SSP survey will uncover thousands of galaxy clusters to $z\lesssim1.5$. In deriving cluster masses via WL, a critical source of systematics is contamination and dilution of the lensing signal by cluster {members, and by foreground galaxies whose photometric redshifts are biased}. Using the first-year CAMIRA catalog of $\sim$900 clusters with richness larger than 20 found in $\sim$140 deg$^2$ of HSC-SSP data, we devise and compare several source selection methods, including selection in color-color space (CC-cut), and selection of robust photometric redshifts by applying constraints on their cumulative probability distribution function (PDF; P-cut). We examine the dependence of the contamination on the chosen limits adopted for each method. Using the proper limits, these methods give mass profiles with minimal dilution in agreement with one another. We find that not adopting either the CC-cut or P-cut methods results in an underestimation of the total cluster mass ($13\pm4\%$) and the concentration of the profile ($24\pm11\%$). The level of cluster contamination can reach as high as $\sim10\%$ at $R\approx 0.24$ Mpc/$h$ for low-z clusters without cuts, while employing either the P-cut or CC-cut results in cluster contamination consistent with zero to within the 0.5% uncertainties. Our robust methods yield a $\sim60\sigma$ detection of the stacked CAMIRA surface mass density profile, with a mean mass of $M_\mathrm{200c} = (1.67\pm0.05({\rm {stat}}))\times 10^{14}\,M_\odot/h$., Comment: 19 pages, 4 tables, 12 figures, accepted to PASJ special issue

Galaxy observations are influenced by many physical parameters: stellar masses, star formation rates (SFRs), star formation histories (SFHs), metallicities, dust, black hole activity, and more. As a result, inferring accurate physical parameters requires high-dimensional models which capture or marginalize over this complexity. Here we re-assess inferences of galaxy stellar masses and SFRs using the 14-parameter physical model Prospector-$��$ built in the Prospector Bayesian inference framework. We fit the photometry of 58,461 galaxies from the 3D-HST catalogs at $0.5 < z < 2.5$. The resulting stellar masses are $\sim0.1-0.3$ dex larger than the fiducial masses while remaining consistent with dynamical constraints. This change is primarily due to the systematically older SFHs inferred with Prospector. The SFRs are $\sim0.1-1+$ dex lower than UV+IR SFRs, with the largest offsets caused by emission from "old" ($t>100$ Myr) stars. These new inferences lower the observed cosmic star formation rate density by $\sim0.2$ dex and increase the observed stellar mass growth by $\sim 0.1$ dex, finally bringing these two quantities into agreement and implying an older, more quiescent Universe than found by previous studies at these redshifts. We corroborate these results by showing that the Prospector-$��$ SFHs are both more physically realistic and are much better predictors of the evolution of the stellar mass function. Finally, we highlight examples of observational data which can break degeneracies in the current model; these observations can be incorporated into priors in future models to produce new & more accurate physical parameters., Replaced w/ accepted version

We measure cosmic weak lensing shear power spectra with the Subaru Hyper Suprime-Cam (HSC) survey first-year shear catalog covering 137deg$^2$ of the sky. Thanks to the high effective galaxy number density of $\sim$17 arcmin$^{-2}$ even after conservative cuts such as magnitude cut of $i, Comment: 43 pages, 21 figures, accepted for publication in PASJ

We present a new technique to determine distances to major star-forming regions across the Perseus Molecular Cloud, using a combination of stellar photometry, astrometric data, and $\rm ^{12} CO$ spectral-line maps. Incorporating the Gaia DR2 parallax measurements when available, we start by inferring the distance and reddening to stars from their Pan-STARRS1 and 2MASS photometry, based on a technique presented in Green et al. 2014; Green et al. 2015 and implemented in their 3D "Bayestar" dust map of three-quarters of the sky. We then refine the Green et al. technique by using the velocity slices of a CO spectral cube as dust templates and modeling the cumulative distribution of dust along the line of sight towards these stars as a linear combination of the emission in the slices. Using a nested sampling algorithm, we fit these per-star distance-reddening measurements to find the distances to the CO velocity slices towards each star-forming region. This results in distance estimates explicitly tied to the velocity structure of the molecular gas. We determine distances to the B5, IC348, B1, NGC1333, L1448, and L1451 star-forming regions and find that individual clouds are located between $\approx 275-300$ pc, with typical combined uncertainties of $\approx 5\%$. We find that the velocity gradient across Perseus corresponds to a distance gradient of about 25 pc, with the eastern portion of the cloud farther away than the western portion. We determine an average distance to the complex of $294\pm 17$ pc, about 60 pc higher than the distance derived to the western portion of the cloud using parallax measurements of water masers associated with young stellar objects. The method we present is not limited to the Perseus Complex, but may be applied anywhere on the sky with adequate CO data in the pursuit of more accurate 3D maps of molecular clouds in the solar neighborhood and beyond., Comment: Accepted for publication in The Astrophysical Journal

We present an optically-selected cluster catalog from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The HSC images are sufficiently deep to detect cluster member galaxies down to $M_*\sim 10^{10.2}M_\odot$ even at $z\sim 1$, allowing a reliable cluster detection at such high redshifts. We apply the CAMIRA algorithm to the HSC Wide S16A dataset covering $\sim 232$ deg$^2$ to construct a catalog of 1921 clusters at redshift $0.115$ that roughly corresponds to $M_{\rm 200m}\gtrsim 10^{14}h^{-1}M_\odot$. We confirm good cluster photometric redshift performance, with the bias and scatter in $\Delta z/(1+z)$ being better than 0.005 and 0.01 over most of the redshift range, respectively. We compare our cluster catalog with large X-ray cluster catalogs from XXL and XMM-LSS surveys and find good correlation between richness and X-ray properties. We also study the miscentering effect from the distribution of offsets between optical and X-ray cluster centers. We confirm the high ($>0.9$) completeness and purity for high mass clusters by analyzing mock galaxy catalogs., Comment: 18 pages, 18 figures, accepted for publication in PASJ; cluster catalogs are available at http://www.slac.stanford.edu/~oguri/cluster/

Photometric redshifts are a key component of many science objectives in the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). In this paper, we describe and compare the codes used to compute photometric redshifts for HSC-SSP, how we calibrate them, and the typical accuracy we achieve with the HSC five-band photometry (grizy). We introduce a new point estimator based on an improved loss function and demonstrate that it works better than other commonly used estimators. We find that our photo-z's are most accurate at 0.2, Comment: 30 pages, 15 figures, 5 tables, moderate revision, accepted for publication in PASJ

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) is a three-layered imaging survey aimed at addressing some of the most outstanding questions in astronomy today, including the nature of dark matter and dark energy. The survey has been awarded 300 nights of observing time at the Subaru Telescope and it started in March 2014. This paper presents the first public data release of HSC-SSP. This release includes data taken in the first 1.7 years of observations (61.5 nights) and each of the Wide, Deep, and UltraDeep layers covers about 108, 26, and 4 square degrees down to depths of i~26.4, ~26.5, and ~27.0 mag, respectively (5sigma for point sources). All the layers are observed in five broad bands (grizy), and the Deep and UltraDeep layers are observed in narrow bands as well. We achieve an impressive image quality of 0.6 arcsec in the i-band in the Wide layer. We show that we achieve 1-2 per cent PSF photometry (rms) both internally and externally (against Pan-STARRS1), and ~10 mas and 40 mas internal and external astrometric accuracy, respectively. Both the calibrated images and catalogs are made available to the community through dedicated user interfaces and database servers. In addition to the pipeline products, we also provide value-added products such as photometric redshifts and a collection of public spectroscopic redshifts. Detailed descriptions of all the data can be found online. The data release website is https://hsc-release.mtk.nao.ac.jp/., 34 pages, 20 figures, 7 tables, moderate revision, accepted for publication in PASJ

In Paper I (Safarzadeh & Berger 2019) we studied the determination of the delay time distribution (DTD) of binary neutron stars (BNS) through scaling relations between halo/stellar mass and the star formation history (SFH) of galaxies hosting gravitational wave (GW) events in the local universe. Here we explore how a detailed reconstruction of the individual SFHs of BNS merger host galaxies can improve on the use of the scaling relations. We use galaxies from the Galaxy and Mass Assembly (GAMA) survey, which is mass complete at $M_*>10^9$ M$_\odot$ in the redshift range $0.05, Comment: Accepted for publication at ApJ Letters

We propose a method to substantially increase the flexibility and power of template fitting-based photometric redshifts by transforming a large numbers of galaxy spectral templates into a corrresponding collection of "fuzzy archetypes" using a suitable set of perturbative priors designed to account for empirical variation in dust attenuation and emission line strengths. To bypass widely seperated degeneracies in parameter space (e.g., the redshift-reddening degeneracy), we train Self-Organizing Maps (SOMs) on a large "model catalogs" generated from appropriate Monte Carlo sampling of our fuzzy archetypes to cluster the predicted observables in a topologically smooth fashion. Subsequent sampling over the SOM then allows full reconstruction of the relevant probability distribution functions (PDFs) using the associated set of inverse mappings from the SOM to the underlying model parameters. This combined approach enables the multi-modal exploration of known variation among galaxy spectral energy distributions (SEDs) using large numbers of archetypes with minimal modeling assumptions. We demonstrate the power of this approach to recover full redshift PDFs using discrete Markov Chain Monte Carlo (MCMC) sampling methods combined with SOMs constructed from model catalogs based on LSST $ugrizY$ and Euclid $YJH$ mock photometry., 26 pages, 11 figures, 1 table; submitted to MNRAS

Using a grid of $\sim 2$ million elements ($\Delta z = 0.005$) adapted from COSMOS photometric redshift (photo-z) searches, we investigate the general properties of template-based photo-z likelihood surfaces. We find these surfaces are filled with numerous local minima and large degeneracies that generally confound rapid but "greedy" optimization schemes, even with additional stochastic sampling methods. In order to robustly and efficiently explore these surfaces, we develop BAD-Z [Brisk Annealing-Driven Redshifts (Z)], which combines ensemble Markov Chain Monte Carlo (MCMC) sampling with simulated annealing to sample arbitrarily large, pre-generated grids in approximately constant time. Using a mock catalog of 384,662 objects, we show BAD-Z samples $\sim 40$ times more efficiently compared to a brute-force counterpart while maintaining similar levels of accuracy. Our results represent first steps toward designing template-fitting photo-z approaches limited mainly by memory constraints rather than computation time., Comment: 14 pages, 8 figures; submitted to MNRAS; comments welcome

Middle-aged, cooling neutron stars are observed both as relatively rapidly spinning radio pulsars and as more slowly spinning, strongly magnetized isolated neutron stars (INSs), which stand out by their thermal X-ray spectra. The difference between the two classes may be that the INSs initially had much stronger magnetic fields, which decayed. To test this, we used the Chandra X-ray Observatory to observe 1RXS J072559.8-261229, a possible X-ray counterpart to PSR J0726-2612, which, with its 3.44s period and 3e13G inferred magnetic field strength, is the nearest and least extincted among the possible slowly-spinning, strong-field INS progenitors (it likely is in the Gould Belt, at ~1 kpc). We confirm the identification and find that the pulsar has a spectrum consistent with being purely thermal, with blackbody temperature kT=87+/-5 eV and radius R=5.7+2.6-1.3 km at a distance of 1 kpc. We detect sinusoidal pulsations at twice the radio period with a semi-amplitude of 27\pm5%. The properties of PSR J0726-2612 strongly resemble those of the INSs, except for its much shorter characteristic age of 200 kyr (instead of several Myr). We conclude that PSR J0726-2612 is indeed an example of a young INS, one that started with a magnetic field strength on the low end of those inferred for the INSs, and that, therefore, decayed by a relatively small amount. Our results suggest that the long-period, strong-field pulsars and the INSs are members of the same class, and open up new opportunities to understand the puzzling X-ray and optical emission of the INSs through radio observations of PSR J0726-2612., Comment: ApJ, in press. 7 pages, 3 figures, using emulateapj. Old version had wrong source files

The spectroscopic and photometric signals of the star-to-star abundance variations found in globular clusters seem to be correlated with global parameters like the cluster's metallicity, mass and age. Understanding this behaviour could bring us closer to the origin of these intriguing abundance spreads. In this work we use deep HST photometry to look for evidence of abundance variations in the main sequence of a young massive cluster NGC 419 ($\sim10^5$ M$_{\odot}$, $\sim1.4$ Gyr). Unlike previous studies, here we focus on stars in the same mass range found in old globulars ($\sim0.75-1$ M$_{\odot}$), where light elements variations are detected. We find no evidence for N abundance variations among these stars in the $Un-B$ and $U-B$ CMD of NGC 419. This is at odds with the N-variations found in old globulars like 47 Tuc, NGC 6352 and NGC 6637 with similar metallicity to NGC 419. Although the signature of the abundance variations characteristic of old globulars appears to be significantly smaller or absent in this young cluster, we cannot conclude if this effect is mainly driven by its age or its mass., Comment: 9 pages, 8 figures, accepted for publication in MNRAS