The Zwicky Transient Facility (ZTF) is a new optical time-domain survey that uses the Palomar 48 inch Schmidt telescope. A custom-built wide-field camera provides a 47 deg 2 field of view and 8 s readout time, yielding more than an order of magnitude improvement in survey speed relative to its predecessor survey, the Palomar Transient Factory. We describe the design and implementation of the camera and observing system. The ZTF data system at the Infrared Processing and Analysis Center provides near-real-time reduction to identify moving and varying objects. We outline the analysis pipelines, data products, and associated archive. Finally, we present on-sky performance analysis and first scientific results from commissioning and the early survey. ZTF's public alert stream will serve as a useful precursor for that of the Large Synoptic Survey Telescope.

The Zwicky Transient Facility (ZTF), a public–private enterprise, is a new time-domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope with a 47 deg2 field of view and an 8 second readout time. It is well positioned in the development of time-domain astronomy, offering operations at 10% of the scale and style of the Large Synoptic Survey Telescope (LSST) with a single 1-m class survey telescope. The public surveys will cover the observable northern sky every three nights in g and r filters and the visible Galactic plane every night in g and r. Alerts generated by these surveys are sent in real time to brokers. A consortium of universities that provided funding (“partnership”) are undertaking several boutique surveys. The combination of these surveys producing one million alerts per night allows for exploration of transient and variable astrophysical phenomena brighter than r ∼ 20.5 on timescales of minutes to years. We describe the primary science objectives driving ZTF, including the physics of supernovae and relativistic explosions, multi-messenger astrophysics, supernova cosmology, active galactic nuclei, and tidal disruption events, stellar variability, and solar system objects.

We present a catalog of 536 fast radio bursts (FRBs) detected by the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) Project between 400 and 800 MHz from 2018 July 25 to 2019 July 1, including 62 bursts from 18 previously reported repeating sources. The catalog represents the first large sample, including bursts from repeaters and nonrepeaters, observed in a single survey with uniform selection effects. This facilitates comparative and absolute studies of the FRB population. We show that repeaters and apparent nonrepeaters have sky locations and dispersion measures (DMs) that are consistent with being drawn from the same distribution. However, bursts from repeating sources differ from apparent nonrepeaters in intrinsic temporal width and spectral bandwidth. Through injection of simulated events into our detection pipeline, we perform an absolute calibration of selection effects to account for systematic biases. We find evidence for a population of FRBs—composing a large fraction of the overall population—with a scattering time at 600 MHz in excess of 10 ms, of which only a small fraction are observed by CHIME/FRB. We infer a power-law index for the cumulative fluence distribution of α = − 1.40 ± 0.11 ( stat. ) − 0.09 + 0.06 ( sys. ) , consistent with the −3/2 expectation for a nonevolving population in Euclidean space. We find that α is steeper for high-DM events and shallower for low-DM events, which is what would be expected when DM is correlated with distance. We infer a sky rate of [ 820 ± 60 ( stat. ) − 200 + 220 ( sys. ) ] / sky / day above a fluence of 5 Jy ms at 600 MHz, with a scattering time at 600 MHz under 10 ms and DM above 100 pc cm−3.

We present new mass estimates and cumulative mass profiles (CMPs) with Bayesian credible regions for the Milky Way (MW) Galaxy, given the kinematic data of globular clusters as provided by (1) the Gaia DR2 collaboration and the HSTPROMO team, and (2) the new catalog in Vasiliev (2019). We use globular clusters beyond 15kpc to estimate the CMP of the MW, assuming a total gravitational potential model Φ(r) = Φ • r −γ , which approximates an NFW-type potential at large distances when γ = 0.5. We compare the resulting CMPs given data sets (1) and (2), and find the results to be nearly identical. The median estimate for the total mass is M 200 = 0.70 × 10 12 M and the 50% Bayesian credible interval is (0.62, 0.81) × 10 12 M . However, because the Vasiliev catalog contains more complete data at large r, the MW total mass is slightly more constrained by these data. In this work, we also supply instructions for how to create a CMP for the MW with Bayesian credible regions, given a model for M (< r) and samples drawn from a posterior distribution. With the CMP, we can report median estimates and 50% Bayesian credible regions for the MW mass within any distance (e.g., M (r = 25 kpc) = 0.26 (0.20, 0.36) × 10 12 M , M (r = 50 kpc) = 0.37 (0.29, 0.51) × 10 12 M , M (r = 100 kpc) = 0.53 (0.41, 0.74) × 10 12 M , etc.), making it easy to compare our results directly to other studies.

We present new deep photometry of the rich globular cluster (GC) systems around the Brightest Cluster Galaxies UGC 9799 (Abell 2052) and UGC 10143 (Abell 2147), obtained with the Hubble Space Telescope (HST) ACS and WFC3 cameras. For comparison, we also present new reductions of similar HST/ACS data for the Coma supergiants NGC 4874 and 4889. All four of these galaxies have huge cluster populations (to the radial limits of our data, comprising from 12,000 to 23,000 clusters per galaxy). The metallicity distribution functions (MDFs) of the GCs can still be matched by a bimodal-Gaussian form where the metal-rich and metalpoor modes are separated by 0.8 dex, but the internal dispersions of each mode are so large that the total MDF becomes very broad and nearly continuous from [Fe/H];−2.4 to solar. There are, however, significant differences between galaxies in the relative numbers of metal-rich clusters, suggesting that they underwent significantly different histories of mergers with massive gas-rich halos. Last, the proportion of metal-poor GCs rises especially rapidly outside projected radii  R R 4 eff , suggesting the importance of accreted dwarf satellites in the outer halo. Comprehensive models for the formation of GCs as part of the hierarchical formation of their parent galaxies will be needed to trace the systematic change in structure of the MDF with galaxy mass, from the distinctly bimodal form in smaller galaxies up to the broad continuum that we see in the very largest systems.

We present mass and mass profile estimates for the Milky Way (MW) Galaxy using the Bayesian analysis developed by Eadie et al. and using globular clusters (GCs) as tracers of the Galactic potential. The dark matter and GCs are assumed to follow different spatial distributions; we assume power-law model profiles and use the model distribution functions described in Evans et al. and Deason et al. We explore the relationships between assumptions about model parameters and how these assumptions affect mass profile estimates. We also explore how using subsamples of the GC population beyond certain radii affect mass estimates. After exploring the posterior distributions of different parameter assumption scenarios, we conclude that a conservative estimate of the Galaxy's mass within 125 kpcis5.22 10 11  M , with a 50% probability region of4. ). If we consider only the GCs beyond 10 kpc, then the virial mass iś 9.02 5.69, 10.86 10 11 ( )vir 24 19 kpc). We also arrive at an estimate of the velocity anisotropy parameter β of the GC population, which is b = 0.28 with a 50% credible region (0.21, 0.35). Interestingly, the mass estimates are sensitive to both the dark matter halo potential and visible matter tracer parameters, but are not very sensitive to the anisotropy parameter.

A powerful method to measure the mass profile of a galaxy is through the velocities of tracer particles distributed through its halo. Transforming this kind of data accurately to a mass profile M (r), however, is not a trivial problem. In particular, limited or incomplete data may substantially affect the analysis. In this paper we develop a Bayesian method to deal with incomplete data effectively; we have a hybrid-Gibbs sampler that treats the unknown velocity components of tracers as parameters in the model. We explore the effectiveness of our model using simulated data, and then apply our method to the Milky Way using velocity and position data from globular clusters and dwarf galaxies. We find that in general, missing velocity components have little effect on the total mass estimate. However, the results are quite sensitive to the outer globular cluster Pal 3. Using a basic Hernquist model with an isotropic velocity dispersion, we obtain credible regions for the cumulative mass profile M (r) of the Milky Way, and provide estimates for the model parameters with 95% Bayesian credible intervals. The mass contained within 260kpc is 1.37×10 12 M , with a 95% credible interval of (1.27, 1.51)×10 12 M . The Hernquist parameters for the total mass and scale radius are 1.55 +0.18 −0.13 ×10 12 M and 16.9 +4.8 −4.1 kpc, where the uncertainties span the 95% credible intervals. The code we developed for this work, Galactic Mass Estimator (GME), will be available as an open source package in the R Project for Statistical Computing.

We present a hierarchical Bayesian method for estimating the total mass and mass profile of the Milky Way Galaxy. The new hierarchical Bayesian approach further improves the framework presented by Eadie et al. (2015b); Eadie & Harris (2016) and builds upon the preliminary reports by Eadie et al. (2015a,c). The method uses a distribution function f (E, L) to model the galaxy and kinematic data from satellite objects such as globular clusters (GCs) to trace the Galaxy's gravitational potential. A major advantage of the method is that it not only includes complete and incomplete data simultaneously in the analysis, but also incorporates measurement uncertainties in a coherent and meaningful way. We first test the hierarchical Bayesian framework, which includes measurement uncertainties, using the same data and power-law model assumed in Eadie & Harris (2016), and find the results are similar but more strongly constrained. Next, we take advantage of the new statistical framework and incorporate all possible GC data, finding a cumulative mass profile with Bayesian credible regions. This profile implies a mass within 125kpc of 4.8 × 1011 M with a 95% Bayesian credible region of (4.0 − 5.8) × 10 11 M . Our results also provide estimates of the true specific energies of all the GCs. By comparing these estimated energies to the measured energies of GCs with complete velocity measurements, we observe that (the few) remote tracers with complete measurements may play a large role in determining a total mass estimate of the Galaxy. Thus, our study stresses the need for more remote tracers with complete velocity measurements.