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The most promising variation of the standard siren technique combines gravitational-wave (GW) data for binary neutron star (BNS) mergers with redshift measurements enabled by their electromagnetic (EM) counterparts, to constrain cosmological parameters such as $H_0$, $\Omega_m$, and $w_0$. Here we evaluate the near- and long-term prospects of multi-messenger cosmology in the era of future GW observatories: Advanced LIGO Plus (A+, 2025), Voyager-like detectors (2030s), and Cosmic Explorer-like detectors (CE, 2035 and beyond). We show that the BNS horizon distance of $\approx 700$ Mpc for A+ is well-matched to the sensitivity of the Vera C. Rubin Observatory (VRO) for kilonova detections. We find that one year of joint A+ and VRO observations will constrain the value of $H_0$ to percent-level precision, given a small investment of VRO time dedicated to target-of-opportunity GW follow-up. In the Voyager era, the BNS-kilonova observations begin to constrain $\Omega_m$ with an investment of a few percent of VRO time. With the larger BNS horizon distance in the Cosmic Explorer era, on-axis short gamma-ray bursts (SGRBs) and their afterglows (though accompanying only some of the GW-detected mergers) supplant kilonovae as the most promising counterparts for redshift identification. We show that five years of joint observations with Cosmic Explorer-like facilities and a next-generation gamma-ray satellite with localization capabilities similar to that presently possible with Swift could constrain both $\Omega_m$ and $w_0$ to $15-20\%$. We therefore advocate for a robust target-of-opportunity (ToO) program with VRO, and a wide-field gamma-ray satellite with improved sensitivity in the 2030s, to enable standard siren cosmology with next-generation gravitational wave facilities., Comment: The Astrophysical Journal Letters accepted version

We present nearly 500 days of observations of the tidal disruption event ASASSN-18pg, spanning from 54 days before peak light to 441 days after peak light. Our dataset includes X-ray, UV, and optical photometry, optical spectroscopy, radio observations, and the first published spectropolarimetric observations of a TDE. ASASSN-18pg was discovered on 2018 July 11 by the All-Sky Automated Survey for Supernovae (ASAS-SN) at a distance of $d=78.6$ Mpc, and with a peak UV magnitude of $m\simeq14$ it is both one of the nearest and brightest TDEs discovered to-date. The photometric data allow us to track both the rise to peak and the long-term evolution of the TDE. ASASSN-18pg peaked at a luminosity of $L\simeq2.2\times10^{44}$ erg s$^{-1}$, and its late-time evolution is shallower than a flux $\propto t^{-5/3}$ power-law model, similar to what has been seen in other TDEs. ASASSN-18pg exhibited Balmer lines and spectroscopic features consistent with Bowen fluorescence prior to peak which remained detectable for roughly 225 days after peak. Analysis of the two-component H$\alpha$ profile indicates that, if they are the result of reprocessing of emission from the accretion disk, the different spectroscopic lines may be coming from regions between $\sim10$ and $\sim60$ light-days from the black hole. No X-ray emission is detected from the TDE and there is no evidence of a jet or strong outflow detected in the radio. Our spectropolarimetric observations give no strong evidence for significant asphericity in the emission region, with the emission region having an axis ratio of at least $\sim0.65$., Comment: 22 pages, 11 figures, 5 tables. Submitted to ApJ. A machine-readable table containing the host-subtracted photometry presented in this manuscript is included as an ancillary file

AT 2018hyz (=ASASSN-18zj) is a tidal disruption event (TDE) located in the nucleus of a quiescent E+A galaxy at a redshift of $z = 0.04573$, first detected by the All-Sky Automated Survey for Supernovae (ASAS-SN). We present optical+UV photometry of the transient, as well as an X-ray spectrum and radio upper limits. The bolometric light curve of AT 2018hyz is comparable to other known TDEs and declines at a rate consistent with a $t^{-5/3}$ at early times, emitting a total radiated energy of $E = 9\times10^{50}$ erg. An excess bump appears in the UV light curve about 50 days after bolometric peak, followed by a flattening beyond 250 days. The light curve shows an excess bump in the UV about 50 days after bolometric peak lasting for at least 100 days, which may be related to an outflow. We detect a constant X-ray source present for at least 86 days. The X-ray spectrum shows a total unabsorbed flux of $\sim 4\times10^{-14}$ erg cm$^{-2}$ s$^{-1}$ and is best fit by a blackbody plus power-law model with a photon index of $\Gamma = 0.8$. A thermal X-ray model is unable to account for photons $> 1$ keV, while the radio non-detection favors inverse-Compton scattering rather than a jet for the non-thermal component. We model the optical and UV light curves using the Modular Open-Source Fitter for Transients (MOSFiT) and find a best fit for a black hole of $5.2\times10^6$ M$_\odot$ partially disrupting a $0.1$ M$_\odot$ star (stripping a mass of $\sim 0.01$ M$_\odot$ for the inferred impact parameter, $\beta=0.6$). The low optical depth implied by the small debris mass may explain how we are able to see hydrogen emission with disk-like line profiles in the spectra of AT 2018hyz (see our companion paper, Short et al.~2020)., Comment: 10 pages, 10 figures, published in MNRAS

Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos. In this Expert Recommendation, we review the key challenges of real-time observations of gravitational wave sources and their electromagnetic and astroparticle counterparts, and make a number of recommendations to maximize their potential for scientific discovery. These recommendations refer to the design of scalable and computationally efficient machine learning algorithms; the cyber-infrastructure to numerically simulate astrophysical sources, and to process and interpret multi-messenger astrophysics data; the management of gravitational wave detections to trigger real-time alerts for electromagnetic and astroparticle follow-ups; a vision to harness future developments of machine learning and cyber-infrastructure resources to cope with the big-data requirements; and the need to build a community of experts to realize the goals of multi-messenger astrophysics., Comment: Invited Expert Recommendation for Nature Reviews Physics. The art work produced by E. A. Huerta and Shawn Rosofsky for this article was used by Carl Conway to design the cover of the October 2019 issue of Nature Reviews Physics

Whether supernovae are a significant source of dust has been a long-standing debate. The large quantities of dust observed in high-redshift galaxies raise a fundamental question as to the origin of dust in the Universe since stars cannot have evolved to the AGB dust-producing phase in high-redshift galaxies. In contrast, supernovae occur within several millions of years after the onset of star formation. This white paper focuses on dust formation in supernova ejecta with US-Extremely Large Telescope (ELT) perspective during the era of JWST and LSST., Comment: Astro2020 Science White Paper: Dust Formation in Supernovae with US-ELT Perspective

We present optical photometry and spectroscopy of SN 2016iet, an unprecedented Type I supernova (SN) at $z=0.0676$ with no obvious analog in the existing literature. The peculiar light curve has two roughly equal brightness peaks ($\approx -19$ mag) separated by 100 days, and a subsequent slow decline by 5 mag in 650 rest-frame days. The spectra are dominated by emission lines of calcium and oxygen, with a width of only $3400$ km s$^{-1}$, superposed on a strong blue continuum in the first year, and with a large ratio of $L_{\rm [Ca\,II]}/L_{\rm [O\,I]}\approx 4$ at late times. There is no clear evidence for hydrogen or helium associated with the SN at any phase. We model the light curves with several potential energy sources: radioactive decay, central engine, and circumstellar medium (CSM) interaction. Regardless of the model, the inferred progenitor mass near the end of its life (i.e., CO core mass) is $\gtrsim 55$ M$_\odot$ and up to $120$ M$_\odot$, placing the event in the regime of pulsational pair instability supernovae (PPISNe) or pair instability supernovae (PISNe). The models of CSM interaction provide the most consistent explanation for the light curves and spectra, and require a CSM mass of $\approx 35$ M$_\odot$ ejected in the final decade before explosion. We further find that SN 2016iet is located at an unusually large offset ($16.5$ kpc) from its low metallicity dwarf host galaxy ($Z\approx 0.1$ Z$_\odot$, $M\approx 10^{8.5}$ M$_\odot$), supporting the PPISN/PISN interpretation. In the final spectrum, we detect narrow H$\alpha$ emission at the SN location, likely due to a dim underlying galaxy host or an H II region. Despite the overall consistency of the SN and its unusual environment with PPISNe and PISNe, we find that the inferred properties of SN\,2016iet challenge existing models of such events., Comment: 26 Pages, 17 Figures, Submitted to ApJ

The blossoming field of joint gravitational wave and electromagnetic (GW-EM) astronomy is one of the most promising in astronomy. The first, and only, joint GW-EM event GW170817 provided remarkable science returns that still continue to this day. Continued growth in this field requires increasing the sample size of joint GW-EM detections. In this white paper, we outline the case for using some percentage of LSST survey time for dedicated target-of-opportunity follow up of GW triggers in order to efficiently and rapidly identify optical counterparts. We show that the timeline for the LSST science survey is well matched to the planned improvements to ground based GW detectors in the next decade. LSST will become particularly crucial in the later half of the 2020s as more and more distant GW sources are detected. Lastly, we highlight some of the key science goals that can be addressed by a large sample of joint GW-EM detections., Comment: 8 pages, 2 figures. Submitted to the Astro 2020 call for white papers

The field of time-domain astrophysics has entered the era of Multi-messenger Astronomy (MMA). One key science goal for the next decade (and beyond) will be to characterize gravitational wave (GW) and neutrino sources using the next generation of Extremely Large Telescopes (ELTs). These studies will have a broad impact across astrophysics, informing our knowledge of the production and enrichment history of the heaviest chemical elements, constrain the dense matter equation of state, provide independent constraints on cosmology, increase our understanding of particle acceleration in shocks and jets, and study the lives of black holes in the universe. Future GW detectors will greatly improve their sensitivity during the coming decade, as will near-infrared telescopes capable of independently finding kilonovae from neutron star mergers. However, the electromagnetic counterparts to high-frequency (LIGO/Virgo band) GW sources will be distant and faint and thus demand ELT capabilities for characterization. ELTs will be important and necessary contributors to an advanced and complete multi-messenger network., Comment: White paper submitted to the Astro2020 Decadal Survey

This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrophysics, with a particular emphasis on real-time discovery campaigns. Acknowledging the transdisciplinary nature of Multi-Messenger Astrophysics, this document has been prepared by members of the physics, astronomy, computer science, data science, software and cyberinfrastructure communities who attended the NSF-, DOE- and NVIDIA-funded "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at the National Center for Supercomputing Applications, October 17-19, 2018. Highlights of this report include unanimous agreement that it is critical to accelerate the development and deployment of novel, signal-processing algorithms that use the synergy between artificial intelligence (AI) and high performance computing to maximize the potential for scientific discovery with Multi-Messenger Astrophysics. We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics; (ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data; (iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups; (iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era; (v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics., Comment: 15 pages, no figures. White paper based on the "Deep Learning for Multi-Messenger Astrophysics: Real-time Discovery at Scale" workshop, hosted at NCSA, October 17-19, 2018 http://www.ncsa.illinois.edu/Conferences/DeepLearningLSST/

astroquery is a collection of tools for requesting data from databases hosted on remote servers with interfaces exposed on the internet, including those with web pages but without formal application program interfaces (APIs). These tools are built on the Python requests package, which is used to make HTTP requests, and astropy, which provides most of the data parsing functionality. astroquery modules generally attempt to replicate the web page interface provided by a given service as closely as possible, making the transition from browser-based to command-line interaction easy. astroquery has received significant contributions from throughout the astronomical community, including several significant contributions from telescope archives. astroquery enables the creation of fully reproducible workflows from data acquisition through publication. This paper describes the philosophy, basic structure, and development model of the astroquery package. The complete documentation for astroquery can be found at http://astroquery.readthedocs.io/., Comment: Accepted to AJ. The documentation is at http://astroquery.readthedocs.io/ and the repository is at https://github.com/astropy/astroquery/

We announce the public release of the application program interface (API) for the Open Astronomy Catalogs (OACs), the OACAPI. The OACs serve near-complete collections of supernova, tidal disruption, kilonova, and fast stars data (including photometry, spectra, radio, and X-ray observations) via a user-friendly web interface that displays the data interactively and offers full data downloads. The OACAPI, by contrast, enables users to specifically download particular pieces of the OAC dataset via a flexible programmatic syntax, either via URL GET requests, or via a module within the astroquery Python package., Comment: Published in RNAAS. A living description of the API is available at https://github.com/astrocatalogs/OACAPI

We present the first effort to aggregate, homogenize, and uniformly model the combined ultraviolet, optical, and near-infrared dataset for the electromagnetic counterpart of the binary neutron star merger GW170817. By assembling all of the available data from 18 different papers and 46 different instruments, we are able to identify and mitigate systematic offsets between individual datasets, and to identify clear outlying measurements, with the resulting pruned and adjusted dataset offering an opportunity to expand the study of the kilonova. The unified dataset includes 647 individual flux measurements, spanning 0.45 to 29.4 days post-merger, and thus has greater constraining power for physical models than any single dataset. We test a number of semi-analytical models and find that the data are well modeled with a three-component kilonova model: a "blue" lanthanide-poor component with Mej~0.020 Msol and vej~0.27c; an intermediate opacity "purple" component with Mej~0.047 Msol and vej~0.15c; and a "red" lanthanide-rich component with Mej~0.011 Msol and vej~0.14c. We further explore the possibility of ejecta asymmetry and its impact on the estimated parameters. From the inferred parameters we draw conclusions about the physical mechanisms responsible for the various ejecta components, the properties of the neutron stars, and, combined with an up-to-date merger rate, the implications for r-process enrichment via this channel. To facilitate future studies of this keystone event we make the unified dataset and our modeling code public., Comment: 35 pages; 5 figures; 3 tables. Significant changes made to Table 3. Accepted to ApJL