Search

Characterizing the host galaxies of astrophysical transients is important to many areas of astrophysics, including constraining the progenitor systems of core-collapse supernovae, correcting Type Ia supernova distances, and probabilistically classifying transients without photometric or spectroscopic data. Given the increasing transient discovery rate in the coming years, there is substantial utility in providing public, transparent, reproducible, and automatic characterization for large samples of transient host galaxies. Here we present Blast, a web application that ingests live streams of transient alerts, matches transients to their host galaxies, and performs photometry on coincident archival imaging data of the host galaxy. The photometry is then used to infer both global host-galaxy properties and galaxy properties within 2 kpc of the transient location by using the Prospector Bayesian inference framework, with an acceleration in evaluation speed achieved via simulation-based inference. Blast provides host-galaxy properties to users via a web browser or an application program interface. The software can be extended to support alternative photometric or SED-fitting algorithms, and can be scaled via an asynchronous worker queue across multiple compute nodes to handle the processing of large volumes of transient alerts for upcoming transient surveys. Blast has been ingesting newly discovered transients from the Transient Name Server since mid-2024, and has currently measured SED parameters for more than 6000 transients. The service is publicly available at https://blast.scimma.org/., Comment: submitted to PASP

We present multi-wavelength data of SN2020acct, a double-peaked stripped-envelope supernova (SN) in NGC2981 at ~150 Mpc. The two peaks are temporally distinct, with maxima separated by 58 rest-frame days, and a factor of 20 reduction in flux between. The first is luminous (M$_{r}$ = -18.00 $\pm$ 0.02 mag), blue (g - r = 0.27 $\pm$ 0.03 mag), and displays spectroscopic signatures of interaction with hydrogen-free circumstellar material. The second peak is fainter (M$_{r}$ = -17.29 $\pm$ 0.03 mag), and spectroscopically similar to an evolved stripped-envelope SNe, with strong blended forbidden [Ca II] and [O II] features. No other known double-peak SN exhibits a light curve similar to that of SN 2020acct. We find the likelihood of two individual SNe occurring in the same star-forming region within that time to be highly improbable, while an implausibly fine-tuned configuration would be required to produce two SNe from a single binary system. We find that the peculiar properties of SN2020acct match models of pulsational pair instability (PPI), in which the initial peak is produced by collisions of shells of ejected material, shortly followed by a terminal explosion. Pulsations from a star with a 72 M$_{\odot}$ helium core provide an excellent match to the double-peaked light curve. The local galactic environment has a metallicity of 0.4 Z$_{\odot}$, a level where massive single stars are not expected retain enough mass to encounter the PPI. However, late binary mergers or a low-metallicity pocket may allow the required core mass. We measure the rate of SN 2020acct-like events to be $<3.3\times10^{-8}$ Mpc$^{-3}$ yr$^{-1}$ at z = 0.07, or <0.1% of the total core-collapse SN rate., Comment: 31 pages, 14 figures. Submitted to ApJL, comments welcome

We present a comprehensive analysis of the photometric and spectroscopic evolution of SN~2021foa, unique among the class of transitional supernovae for repeatedly changing its spectroscopic appearance from hydrogen-to-helium-to-hydrogen-dominated (IIn-to-Ibn-to-IIn) within 50 days past peak brightness. The spectra exhibit multiple narrow ($\approx$ 300--600~km~s$^{-1}$) absorption lines of hydrogen, helium, calcium and iron together with broad helium emission lines with a full-width-at-half-maximum (FWHM) of $\sim 6000$~km~s$^{-1}$. For a steady, wind-mass loss regime, light curve modeling results in an ejecta mass of $\sim 8$ M$_{\odot}$ and CSM mass below 1 M$_{\odot}$, and an ejecta velocity consistent with the FWHM of the broad helium lines. We obtain a mass-loss rate of $\approx 2$ M$_{\odot} {\rm yr}^{-1}$. This mass-loss rate is three orders of magnitude larger than derived for normal Type II SNe. We estimate that the bulk of the CSM of SN~2021foa must have been expelled within half a year, about 15 years ago. Our analysis suggests that SN~2021foa had a helium rich ejecta which swept up a dense shell of hydrogen rich CSM shortly after explosion. At about 60 days past peak brightness, the photosphere recedes through the dense ejecta-CSM region, occulting much of the red-shifted emission of the hydrogen and helium lines, which results in observed blue-shift ($\sim -3000$~km~s$^{-1}$). Strong mass loss activity prior to explosion, such as those seen in SN~2009ip-like objects and SN~2021foa as precursor emission, are the likely origin of a complex, multiple-shell CSM close to the progenitor star., Comment: Revised. Accepted in ApJ

We present LAISS (Lightcurve Anomaly Identification and Similarity Search), an automated pipeline to detect anomalous astrophysical transients in real-time data streams. We deploy our anomaly detection model on the nightly ZTF Alert Stream via the ANTARES broker, identifying a manageable $\sim$1-5 candidates per night for expert vetting and coordinating follow-up observations. Our method leverages statistical light-curve and contextual host-galaxy features within a random forest classifier, tagging transients of rare classes (spectroscopic anomalies), of uncommon host-galaxy environments (contextual anomalies), and of peculiar or interaction-powered phenomena (behavioral anomalies). Moreover, we demonstrate the power of a low-latency ($\sim$ms) approximate similarity search method to find transient analogs with similar light-curve evolution and host-galaxy environments. We use analogs for data-driven discovery, characterization, (re-)classification, and imputation in retrospective and real-time searches. To date we have identified $\sim$50 previously known and previously missed rare transients from real-time and retrospective searches, including but not limited to: SLSNe, TDEs, SNe IIn, SNe IIb, SNe Ia-CSM, SNe Ia-91bg-like, SNe Ib, SNe Ic, SNe Ic-BL, and M31 novae. Lastly, we report the discovery of 325 total transients, all observed between 2018-2021 and absent from public catalogs ($\sim$1% of all ZTF Astronomical Transient reports to the Transient Name Server through 2021). These methods enable a systematic approach to finding the "needle in the haystack" in large-volume data streams. Because of its integration with the ANTARES broker, LAISS is built to detect exciting transients in Rubin data., Comment: 44 pages (68 pages with Appendix), 15 figures, accepted to ApJ

In this White Paper, we present recommendations for the scientific community and funding agencies to foster the infrastructure for a collaborative multi-messenger and time-domain astronomy (MMA/TDA) ecosystem. MMA/TDA is poised for breakthrough discoveries in the coming decade. In much the same way that expanding beyond the optical bandpass revealed entirely new and unexpected discoveries, cosmic messengers beyond light (i.e., gravitational waves, neutrinos, and cosmic rays) open entirely new windows to answer some of the most fundamental questions in (astro)physics: heavy element synthesis, equation of state of dense matter, particle acceleration, etc. This field was prioritized as a frontier scientific pursuit in the 2020 Decadal Survey on Astronomy and Astrophysics via its "New Windows on the Dynamic Universe" theme. MMA/TDA science presents technical challenges distinct from those experienced in other disciplines. Successful observations require coordination across myriad boundaries -- different cosmic messengers, ground vs. space, international borders, etc. -- all for sources that may not be well localized, and whose brightness may be changing rapidly with time. Add that all of this work is undertaken by real human beings, with distinct backgrounds, experiences, cultures, and expectations, that often conflict. To address these challenges and help MMA/TDA realize its full scientific potential in the coming decade (and beyond), the second in a series of community workshops sponsored by the U.S. National Science Foundation (NSF) and NASA titled "Windows on the Universe: Establishing the Infrastructure for a Collaborative Multi-Messenger Ecosystem" was held on October 16-18, 2023 in Tucson, AZ. Here we present the primary recommendations from this workshop focused on three key topics -- hardware, software, and people and policy. [abridged], Comment: Workshop white paper

The interactions between individuals play a pivotal role in shaping the structure and dynamics of social systems. Complex network models have proven invaluable in uncovering the underlying mechanisms that govern the formation and evolution of these systems. However, conventional network representations primarily emphasize pairwise interactions, represented as edges in the network. In reality, many social interactions occur within groups rather than individual pairs. To capture this crucial aspect, higher-order network representations come into play, especially to describe those complex systems that are inherently composed of agents interacting with group dynamics. Despite recent research advancements in exploring temporal higher-order networks in various systems, our understanding of collaboration networks remains limited. Specifically, there is a lack of knowledge regarding the patterns of group interactions within scientific collaborations. How do groups form and evolve in this context? In this study, we aim to delve into the temporal properties of groups within collaboration networks. Our investigation focuses on uncovering the mechanisms that govern the global, group, and individual-level dynamics, shedding light on how individuals collaborate and how groups form and disband over time. By studying these temporal patterns, we take a significant stride forward in comprehending the intricate dynamics of higher-order interactions within human collaboration systems.

The inclusion of inertia in the Kuramoto model has been long reported to change the nature of phase transition, providing a fertile ground to model the dynamical behaviors of interacting units. More recently, higher-order interactions have been realized as essential for the functioning of real-world complex systems ranging from the brain to disease spreading. Yet, analytical insights to decipher the role of inertia with higher-order interactions remain challenging. Here, we study the Kuramoto model with inertia on simplicial complexes, merging two research domains. We develop an analytical framework in a mean-field setting using self-consistent equations to describe the steady-state behavior, which reveals a prolonged hysteresis in the synchronization profile. Inertia and triadic interaction strength exhibit isolated influence on system dynamics by predominantly governing, respectively, the forward and backward transition points. This work sets a paradigm to deepen our understanding of real-world complex systems such as power grids modeled as the Kuramoto model with inertia., Comment: 5+ pages, 2 figures. Comments welcome

We present extensive optical photometry of the afterglow of GRB~221009A. Our data cover $0.9 - 59.9$\,days from the time of \textit{Swift} and \textit{Fermi} GRB detections. Photometry in $rizy$-band filters was collected primarily with Pan-STARRS and supplemented by multiple 1- to 4-meter imaging facilities. We analyzed the Swift X-ray data of the afterglow and found a single decline rate power-law $f(t) \propto t^{-1.556\pm0.002}$ best describes the light curve. In addition to the high foreground Milky Way dust extinction along this line of sight, the data favour additional extinction to consistently model the optical to X-ray flux with optically thin synchrotron emission. We fit the X-ray-derived power-law to the optical light curve and find good agreement with the measured data up to $5-6$\,days. Thereafter we find a flux excess in the $riy$ bands which peaks in the observer frame at $\sim20$\,days. This excess shares similar light curve profiles to the type Ic broad-lined supernovae SN~2016jca and SN~2017iuk once corrected for the GRB redshift of $z=0.151$ and arbitrarily scaled. This may be representative of a supernova emerging from the declining afterglow. We measure rest-frame absolute peak AB magnitudes of $M_g=-19.8\pm0.6$ and $M_r=-19.4\pm0.3$ and $M_z=-20.1\pm0.3$. If this is an SN component, then Bayesian modelling of the excess flux would imply explosion parameters of $M_{\rm ej}=7.1^{+2.4}_{-1.7}$ M$_{\odot}$, $M_{\rm Ni}=1.0^{+0.6}_{-0.4}$ M$_{\odot}$, and $v_{\rm ej}=33,900^{+5,900}_{-5,700} kms^{-1}$, for the ejecta mass, nickel mass and ejecta velocity respectively, inferring an explosion energy of $E_{\rm kin}\simeq 2.6-9.0\times10^{52}$ ergs., Comment: Submitted to ApJL on 23rd January 2023, for consideration for publication in the special issue on GRB 221009A. Accepted on 2nd March 2023. The results of this paper are under press embargo until 28th March 2023. 15 pages, 7 figures, 1 table

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multi-color Pan-STARRS1 (PS1) griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host-galaxy associations, redshifts, spectroscopic/photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z~0.5. We present relative SN rates from YSE's magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multi-survey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (~71%) SNe Ia, 339 (~23%) SNe II, and 96 (~6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time., Comment: Accepted to ApJS; 64 pages; 35 figures; 10 tables

There is growing evidence that Type Ia supernovae (SNe Ia) may originate from multiple explosion channels. Previous studies have indicated that the ejecta velocity of SNe Ia is one powerful tool to discriminate between different channels. In this work, we study ~400 confirmed SNe Ia discovered by the Pan-STARRS1 Medium Deep Survey (PS1-MDS), and obtain a sample of ~50 SNe Ia that have near-peak Si II 6355 velocity (Vsi) measurements. We investigate the relationships between Vsi and various parameters, including SN light-curve width, color, host-galaxy properties, and redshift. No significant trends are identified between Vsi and light-curve parameters. Regarding the host-galaxy properties, we see a significant trend that high-velocity (HV) SNe Ia (Vsi > 12000 km/s) tend to reside in more massive galaxies compared to normal-velocity (NV) SNe Ia (Vsi < 12000 km/s) when combining both the PS1-MDS dataset and those from previous low-z studies. While we do not see a significant trend between Vsi and redshift, HV SNe Ia appear to be more prevalent in low-z samples than in high-z samples. We discuss several possibilities that could potentially contribute to this trend. Furthermore, we investigate the potential bias on SN Ia distances and find no significant difference in Hubble residuals between HV and NV subgroups., Comment: 15 pages, 13 figures, 3 tables, accepted for publication in MNRAS

We verified for photometric stability a set of DA white dwarfs with Hubble Space Telescope magnitudes from the near-ultraviolet to the near-infrared and ground-based spectroscopy by using time-spaced observations from the Las Cumbres Observatory network of telescopes. The initial list of 38 stars was whittled to 32 final ones which comprise a high quality set of spectrophotometric standards. These stars are homogeneously distributed around the sky and are all fainter than r ~ 16.5 mag. Their distribution is such that at least two of them would be available to be observed from any observatory on the ground at any time at airmass less than two. Light curves and different variability indices from the Las Cumbres Observatory data were used to determine the stability of the candidate standards. When available, Pan-STARRS1, Zwicky Transient Facility and TESS data were also used to confirm the star classification. Our analysis showed that four DA white dwarfs may exhibit evidence of photometric variability, while a fifth is cooler than our established lower temperature limit, and a sixth star might be a binary. In some instances, due to the presence of faint nearby red sources, care should be used when observing a few of the spectrophotometric standards with ground-based telescopes. Light curves and finding charts for all the stars are provided., Comment: 48 pages, 50 figures, accepted for publication on ApJ

This paper considers the problem of Hierarchical Multi-Label Classification (HMC), where (i) several labels can be present for each example, and (ii) labels are related via a domain-specific hierarchy tree. Guided by the intuition that all mistakes are not equal, we present Comprehensive Hierarchy Aware Multi-label Predictions (CHAMP), a framework that penalizes a misprediction depending on its severity as per the hierarchy tree. While there have been works that apply such an idea to single-label classification, to the best of our knowledge, there are limited such works for multilabel classification focusing on the severity of mistakes. The key reason is that there is no clear way of quantifying the severity of a misprediction a priori in the multilabel setting. In this work, we propose a simple but effective metric to quantify the severity of a mistake in HMC, naturally leading to CHAMP. Extensive experiments on six public HMC datasets across modalities (image, audio, and text) demonstrate that incorporating hierarchical information leads to substantial gains as CHAMP improves both AUPRC (2.6% median percentage improvement) and hierarchical metrics (2.85% median percentage improvement), over stand-alone hierarchical or multilabel classification methods. Compared to standard multilabel baselines, CHAMP provides improved AUPRC in both robustness (8.87% mean percentage improvement ) and less data regimes. Further, our method provides a framework to enhance existing multilabel classification algorithms with better mistakes (18.1% mean percentage increment).

We report the automatic detection of 11 transients (7 possible supernovae and 4 active galactic nuclei candidates) within the Zwicky Transient Facility fourth data release (ZTF DR4), all of them observed in 2018 and absent from public catalogs. Among these, three were not part of the ZTF alert stream. Our transient mining strategy employs 41 physically motivated features extracted from both real light curves and four simulated light curve models (SN Ia, SN II, TDE, SLSN-I). These features are input to a k-D tree algorithm, from which we calculate the 15 nearest neighbors. After pre-processing and selection cuts, our dataset contained approximately a million objects among which we visually inspected the 105 closest neighbors from seven of our brightest, most well-sampled simulations, comprising 89 unique ZTF DR4 sources. Our result illustrates the potential of coherently incorporating domain knowledge and automatic learning algorithms, which is one of the guiding principles directing the SNAD team. It also demonstrates that the ZTF DR is a suitable testing ground for data mining algorithms aiming to prepare for the next generation of astronomical data., Comment: 30 pages, 5 figures, 3 tables, preprint accepted to New Astronomy

The Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ${\sim}10^6$ 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 (DESC) Data Challenge (DC2) simulation for the Wide-Fast-Deep (WFD) 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 ${\sim}$15 deg$^2$ of DC2 over a 5-year time-span in which artificial point-sources from Type Ia Supernovae (SNIa) light curves have been overlaid onto the images. We measure the detection efficiency as a function of Signal-to-Noise Ratio (SNR) and find a $50\%$ efficiency at $\rm{SNR}=5.8$. The magnitude limits for each filter are: $u=23.66$, $g=24.69$, $r=24.06$, $i=23.45$, $z=22.54$, $y=21.62$ $\rm{mag}$. The artifact contamination is $\sim90\%$ of detections, corresponding to $\sim1000$ artifacts/deg$^2$ in $g$ band, and falling to 300 per 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 pipeline applied to 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 SNR, 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., Comment: Submitting to Astronomy & Astrophysics

SN 2017jgh is a type IIb supernova discovered by Pan-STARRS during the C16/C17 campaigns of the Kepler/K2 mission. Here we present the Kepler/K2 and ground based observations of SN 2017jgh, which captured the shock cooling of the progenitor shock breakout with an unprecedented cadence. This event presents a unique opportunity to investigate the progenitors of stripped envelope supernovae. By fitting analytical models to the SN 2017jgh lightcurve, we find that the progenitor of SN 2017jgh was likely a yellow supergiant with an envelope radius of $\sim50-290~R_{\odot}$, and an envelope mass of $\sim0-1.7~M_{\odot}$. SN 2017jgh likely had a shock velocity of $\sim7500-10300$ km s$^{-1}$. Additionally, we use the lightcurve of SN 2017jgh to investigate how early observations of the rise contribute to constraints on progenitor models. Fitting just the ground based observations, we find an envelope radius of $\sim50-330~R_{\odot}$, an envelope mass of $\sim0.3-1.7~M_{\odot}$ and a shock velocity of $\sim9,000-15,000$ km s$^{-1}$. Without the rise, the explosion time can not be well constrained which leads to a systematic offset in the velocity parameter and larger uncertainties in the mass and radius. Therefore, it is likely that progenitor property estimates through these models may have larger systematic uncertainties than previously calculated., Comment: 15 pages, 9 figures. Accepted to MNRAS

We review the needs of the supernova community for improvements in survey coordination and data sharing that would significantly boost the constraints on dark energy using samples of Type Ia supernovae from the Vera C. Rubin Observatories, the \textit{Nancy Grace Roman Space Telescope}, and the \textit{Euclid} Mission. We discuss improvements to both statistical and systematic precision that the combination of observations from these experiments will enable. For example, coordination will result in improved photometric calibration, redshift measurements, as well as supernova distances. We also discuss what teams and plans should be put in place now to start preparing for these combined data sets. Specifically, we request coordinated efforts in field selection and survey operations, photometric calibration, spectroscopic follow-up, pixel-level processing, and computing. These efforts will benefit not only experiments with Type Ia supernovae, but all time-domain studies, and cosmology with multi-messenger astrophysics., Comment: Response to the recent DOE/NASA Request for Information. Endorsed by the Roman Supernova Science Investigation Teams and the LSST DESC Supernova Working Group

Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition which aimed to catalyze the development of robust classifiers under LSST-like conditions of a non-representative training set for a large photometric test set of imbalanced classes. Over 1,000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between Sep 28, 2018 and Dec 17, 2018, ultimately identifying three winners in February 2019. Participants produced classifiers employing a diverse set of machine learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multi-layer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state-of-the-art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next generation PLAsTiCC data set., Comment: 20 pages, 14 figures

The commissioning team for the Vera C. Rubin observatory is planning a set of engineering and science verification observations with the Legacy Survey of Space and Time (LSST) commissioning camera and then the Rubin Observatory LSST Camera. The time frame for these observations is not yet fixed, and the commissioning team will have flexibility in selecting fields to observe. In this document, the Dark Energy Science Collaboration (DESC) Commissioning Working Group presents a prioritized list of target fields appropriate for testing various aspects of DESC-relevant science performance, grouped by season for visibility from Rubin Observatory at Cerro Pachon. Our recommended fields include Deep-Drilling fields (DDFs) to full LSST depth for photo-$z$ and shape calibration purposes, HST imaging fields to full depth for deblending studies, and an $\sim$200 square degree area to 1-year depth in several filters for higher-level validation of wide-area science cases for DESC. We also anticipate that commissioning observations will be needed for template building for transient science over a broad RA range. We include detailed descriptions of our recommended fields along with associated references. We are optimistic that this document will continue to be useful during LSST operations, as it provides a comprehensive list of overlapping data-sets and the references describing them., Comment: 37 pages, 4 figures. This DESC Note has also been shared with the Vera C. Rubin Observatory project and other Rubin Science Collaborations. The code, and data, along with the background references and research used to produce the tables and figures in this document can be found in an accompanying code supplement in the LSST DESC Zenodo community at http://doi.org/10.5281/zenodo.4148042

Time domain science has undergone a revolution over the past decade, with tens of thousands of new supernovae (SNe) discovered each year. However, several observational domains, including SNe within days or hours of explosion and faint, red transients, are just beginning to be explored. Here, we present the Young Supernova Experiment (YSE), a novel optical time-domain survey on the Pan-STARRS telescopes. Our survey is designed to obtain well-sampled $griz$ light curves for thousands of transient events up to $z \approx 0.2$. This large sample of transients with 4-band light curves will lay the foundation for the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope, providing a critical training set in similar filters and a well-calibrated low-redshift anchor of cosmologically useful SNe Ia to benefit dark energy science. As the name suggests, YSE complements and extends other ongoing time-domain surveys by discovering fast-rising SNe within a few hours to days of explosion. YSE is the only current four-band time-domain survey and is able to discover transients as faint $\sim$21.5 mag in $gri$ and $\sim$20.5 mag in $z$, depths that allow us to probe the earliest epochs of stellar explosions. YSE is currently observing approximately 750 square degrees of sky every three days and we plan to increase the area to 1500 square degrees in the near future. When operating at full capacity, survey simulations show that YSE will find $\sim$5000 new SNe per year and at least two SNe within three days of explosion per month. To date, YSE has discovered or observed 8.3% of the transient candidates reported to the International Astronomical Union in 2020. We present an overview of YSE, including science goals, survey characteristics and a summary of our transient discoveries to date., Comment: ApJ, in press; more information at https://yse.ucsc.edu/

While microlensing is very rare, occurring on average once per million stars observed, current and near-future surveys are coming online with the capability of providing photometry of almost the entire visible sky to depths up to R ~ 22 mag or fainter every few days, which will contribute to the detection of black holes and exoplanets through follow-up observations of microlensing events. Based on galactic models, we can expect microlensing events across a vastly wider region of the galaxy, although the cadence of these surveys (2-3 per day ) is lower than traditional microlensing surveys, making efficient detection a challenge. Rapid advances are being made in the utility of time-series data to detect and classify transient events in real-time using very high data-rate surveys, but limited work has been published regarding the detection of microlensing events, particularly for when the data streams are of relatively low-cadence. In this research, we explore the utility of a Random Forest algorithm for identifying microlensing signals using time-series data, with the goal of creating an efficient machine learning classifier that can be applied to search for microlensing in wide-field surveys even with low-cadence data. We have applied and optimized our classifier using the OGLE-II microlensing dataset, in addition to testing with PTF/iPTF survey data and the currently operating ZTF, which applies the same data handling infrastructure that is envisioned for the upcoming LSST.

CW photoinjectors operating at high accelerating gradients promise to revolutionize many areas of science and applications. They can establish the basis for a new generation of monochromatic X-ray free electron lasers, high brightness hadron beams, or a new generation of microchip production. In this letter we report on the record-performing superconducting RF electron gun with $\textrm{CsK}_{2}\textrm{Sb}$ photocathode. The gun is generating high charge electron bunches (up to 10 nC/bunch) and low transverse emittances, while operating for months with a single photocathode. This achievement opens a new era in generating high-power beams with a very high average brightness.

A Kavli foundation sponsored workshop on the theme \emph{Petabytes to Science} was held 12$^{th}$ to 14$^{th}$ of February 2019 in Las Vegas. The aim of the this workshop was to discuss important trends and technologies which may support astronomy. We also tackled how to better shape the workforce for the new trends and how we should approach education and public outreach. This document was coauthored during the workshop and edited in the weeks after. It comprises the discussions and highlights many recommendations which came out of the workshop. We shall distill parts of this document and formulate potential white papers for the decadal survey., Comment: 70 pages 2 figures - this contains a few fixes

We describe the simulated data sample for the "Photometric LSST Astronomical Time Series Classification Challenge" (PLAsTiCC), a publicly available challenge to classify transient and variable events that will be observed by the Large Synoptic Survey Telescope (LSST), a new facility expected to start in the early 2020s. The challenge was hosted by Kaggle, ran from 2018 September 28 to 2018 December 17, and included 1,094 teams competing for prizes. Here we provide details of the 18 transient and variable source models, which were not revealed until after the challenge, and release the model libraries at https://doi.org/10.5281/zenodo.2612896. We describe the LSST Operations Simulator used to predict realistic observing conditions, and we describe the publicly available SNANA simulation code used to transform the models into observed fluxes and uncertainties in the LSST passbands (ugrizy). Although PLAsTiCC has finished, the publicly available models and simulation tools are being used within the astronomy community to further improve classification, and to study contamination in photometrically identified samples of type Ia supernova used to measure properties of dark energy. Our simulation framework will continue serving as a platform to improve the PLAsTiCC models, and to develop new models.

As of today, we have directly detected exactly one source in both gravitational waves (GWs) and electromagnetic (EM) radiation, the binary neutron star merger GW170817, its associated gamma-ray burst GRB170817A, and the subsequent kilonova SSS17a/AT 2017gfo. Within ten years, we will detect hundreds of events, including new classes of events such as neutron-star-black-hole mergers, core-collapse supernovae, and almost certainly something completely unexpected. As we build this sample, we will explore exotic astrophysical topics ranging from nucleosynthesis, stellar evolution, general relativity, high-energy astrophysics, nuclear matter, to cosmology. The discovery potential is extraordinary, and investments in this area will yield major scientific breakthroughs. Here we outline some of the most exciting scientific questions that can be answered by combining GW and EM observations., Comment: submitted to Astro2020

The discovery of the electromagnetic counterparts to the binary neutron star merger GW170817 has opened the era of GW+EM multi-messenger astronomy. Exploiting this breakthrough requires increasing samples to explore the diversity of kilonova behaviour and provide more stringent constraints on the Hubble constant, and tests of fundamental physics. LSST can play a key role in this field in the 2020s, when the gravitational wave detector network is expected to detect higher rates of merger events involving neutron stars ($\sim$10s per year) out to distances of several hundred Mpc. Here we propose comprehensive target-of-opportunity (ToOs) strategies for follow-up of gravitational-wave sources that will make LSST the premiere machine for discovery and early characterization for neutron star mergers and other gravitational-wave sources., Comment: White paper for LSST cadence optimization- ToOs

We present precise photometry and spectroscopy for 23 candidate spectrophotometric standard white dwarfs. The selected stars are distributed in the Northern hemisphere and around the celestial equators and are all fainter than r ~ 16.5 mag. This network of stars, when established as standards, together with the three Hubble Space Telescope primary CALSPEC white dwarfs, will provide a set of spectrophotometric standards to directly calibrate data products to better than 1%. These new faint standard white dwarfs will have enough signal-to-noise ratio in future deep photometric surveys and facilities to be measured accurately while still avoiding saturation in such surveys. They will also fall within the dynamic range of large telescopes and their instruments for the foreseeable future. This paper discusses the provenance of the observational data for our candidate standard stars. The comparison with models, reconciliation with reddening, and the consequent derivation of the full spectral energy density distributions for each of them is reserved for a subsequent paper., Comment: 31 pages, 17 figures, 10 tables, ApJ in press (accepted on December 23rd, 2018)

We present an exquisite, 30-min cadence Kepler (K2) light curve of the Type Ia supernova (SN Ia) 2018oh (ASASSN-18bt), starting weeks before explosion, covering the moment of explosion and the subsequent rise, and continuing past peak brightness. These data are supplemented by multi-color Pan-STARRS1 and CTIO 4-m DECam observations obtained within hours of explosion. The K2 light curve has an unusual two-component shape, where the flux rises with a steep linear gradient for the first few days, followed by a quadratic rise as seen for typical SNe Ia. This "flux excess" relative to canonical SN Ia behavior is confirmed in our $i$-band light curve, and furthermore, SN 2018oh is especially blue during the early epochs. The flux excess peaks 2.14$\pm0.04$ days after explosion, has a FWHM of 3.12$\pm0.04$ days, a blackbody temperature of $T=17,500^{+11,500}_{-9,000}$ K, a peak luminosity of $4.3\pm0.2\times10^{37}\,{\rm erg\,s^{-1}}$, and a total integrated energy of $1.27\pm0.01\times10^{43}\,{\rm erg}$. We compare SN 2018oh to several models that may provide additional heating at early times, including collision with a companion and a shallow concentration of radioactive nickel. While all of these models generally reproduce the early K2 light curve shape, we slightly favor a companion interaction, at a distance of $\sim$$2\times10^{12}\,{\rm cm}$ based on our early color measurements, although the exact distance depends on the uncertain viewing angle. Additional confirmation of a companion interaction in future modeling and observations of SN 2018oh would provide strong support for a single-degenerate progenitor system., Comment: 20 pages, 9 figures, 2 tables. Submitted to APJ Letters on 31 Jul 2018, Accepted for publication on 31 Aug 2018

Supernova (SN) 2018oh (ASASSN-18bt) is the first spectroscopically-confirmed type Ia supernova (SN Ia) observed in the $Kepler$ field. The $Kepler$ data revealed an excess emission in its early light curve, allowing to place interesting constraints on its progenitor system (Dimitriadis et al. 2018, Shappee et al. 2018b). Here, we present extensive optical, ultraviolet, and near-infrared photometry, as well as dense sampling of optical spectra, for this object. SN 2018oh is relatively normal in its photometric evolution, with a rise time of 18.3$\pm$0.3 days and $\Delta$m$_{15}(B)=0.96\pm$0.03 mag, but it seems to have bluer $B - V$ colors. We construct the "uvoir" bolometric light curve having peak luminosity as 1.49$\times$10$^{43}$erg s$^{-1}$, from which we derive a nickel mass as 0.55$\pm$0.04M$_{\odot}$ by fitting radiation diffusion models powered by centrally located $^{56}$Ni. Note that the moment when nickel-powered luminosity starts to emerge is +3.85 days after the first light in the Kepler data, suggesting other origins of the early-time emission, e.g., mixing of $^{56}$Ni to outer layers of the ejecta or interaction between the ejecta and nearby circumstellar material or a non-degenerate companion star. The spectral evolution of SN 2018oh is similar to that of a normal SN Ia, but is characterized by prominent and persistent carbon absorption features. The C II features can be detected from the early phases to about 3 weeks after the maximum light, representing the latest detection of carbon ever recorded in a SN Ia. This indicates that a considerable amount of unburned carbon exists in the ejecta of SN 2018oh and may mix into deeper layers., Comment: 48 pages, 23 figures. This paper is part of a coordinated effort between groups. Accepted for publication in ApJ

Measurements of the dark energy equation-of-state parameter, $w$, have been limited by uncertainty in the selection effects and photometric calibration of $z<0.1$ Type Ia supernovae (SNe Ia). The Foundation Supernova Survey is designed to lower these uncertainties by creating a new sample of $z<0.1$ SNe Ia observed on the Pan-STARRS system. Here, we combine the Foundation sample with SNe from the Pan-STARRS Medium Deep Survey and measure cosmological parameters with 1,338 SNe from a single telescope and a single, well-calibrated photometric system. For the first time, both the low-$z$ and high-$z$ data are predominantly discovered by surveys that do not target pre-selected galaxies, reducing selection bias uncertainties. The $z>0.1$ data include 875 SNe without spectroscopic classifications and we show that we can robustly marginalize over CC SN contamination. We measure Foundation Hubble residuals to be fainter than the pre-existing low-$z$ Hubble residuals by $0.046 \pm 0.027$ mag (stat+sys). By combining the SN Ia data with cosmic microwave background constraints, we find $w=-0.938 \pm 0.053$, consistent with $\Lambda$CDM. With 463 spectroscopically classified SNe Ia alone, we measure $w=-0.933\pm0.061$. Using the more homogeneous and better-characterized Foundation sample gives a 55% reduction in the systematic uncertainty attributed to SN Ia sample selection biases. Although use of just a single photometric system at low and high redshift increases the impact of photometric calibration uncertainties in this analysis, previous low-$z$ samples may have correlated calibration uncertainties that were neglected in past studies. The full Foundation sample will observe up to 800 SNe to anchor the LSST and WFIRST Hubble diagrams., Comment: 30 pages, 17 figures, accepted by ApJ

Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of their underlying physical processes. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional labeling procedures are inappropriate. Probabilistic classification is more appropriate for the data but are incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations intend to use these classification probabilities for diverse science objectives, indicating a need for a metric that balances a variety of goals. We describe the process used to develop an optimal performance metric for an open classification challenge that seeks probabilistic classifications and must serve many scientific interests. The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC) is an open competition aiming to identify promising techniques for obtaining classification probabilities of transient and variable objects by engaging a broader community both within and outside astronomy. Using mock classification probability submissions emulating archetypes of those anticipated of PLAsTiCC, we compare the sensitivity of metrics of classification probabilities under various weighting schemes, finding that they yield qualitatively consistent results. We choose as a metric for PLAsTiCC a weighted modification of the cross-entropy because it can be meaningfully interpreted. Finally, we propose extensions of our methodology to ever more complex challenge goals and suggest some guiding principles for approaching the choice of a metric of probabilistic classifications.

Empirical models of supernova (SN) spectral energy distributions (SEDs) are widely used for SN survey simulations and photometric classifications. The existing library of SED models has excellent optical templates but limited, poorly constrained coverage of ultraviolet (UV) and infrared (IR) wavelengths. However, both regimes are critical for the design and operation of future SN surveys, particularly at IR wavelengths that will be accessible with the James Webb Space Telescope (JWST) and the Wide-Field Infrared Survey Telescope (WFIRST). We create a public repository of improved empirical SED templates using a sampling of Type Ia and core-collapse (CC) photometric light curves to extend the Type Ia parameterized SALT2 model and a set of SN Ib, SN Ic, and SN II SED templates into the UV and near-IR. We apply this new repository of extrapolated SN SED models to examine how future surveys can discriminate between CC and Type Ia SNe at UV and IR wavelengths, and present an open-source software package written in Python, SNSEDextend, that enables a user to generate their own extrapolated SEDs.

On 2018 Feb. 4.41, the All-Sky Automated Survey for SuperNovae (ASAS-SN) discovered ASASSN-18bt in the K2 Campaign 16 field. With a redshift of z=0.01098 and a peak apparent magnitude of B_{max}=14.31, ASASSN-18bt is the nearest and brightest SNe Ia yet observed by the Kepler spacecraft. Here we present the discovery of ASASSN-18bt, the K2 light curve, and pre-discovery data from ASAS-SN and the Asteroid Terrestrial-impact Last Alert System (ATLAS). The K2 early-time light curve has an unprecedented 30-minute cadence and photometric precision for an SN~Ia light curve, and it unambiguously shows a ~4 day nearly linear phase followed by a steeper rise. Thus, ASASSN-18bt joins a growing list of SNe Ia whose early light curves are not well described by a single power law. We show that a double-power-law model fits the data reasonably well, hinting that two physical processes must be responsible for the observed rise. However, we find that current models of the interaction with a non-degenerate companion predict an abrupt rise and cannot adequately explain the initial, slower linear phase. Instead, we find that existing, published models with shallow 56Ni are able to span the observed behavior and, with tuning, may be able to reproduce the ASASSN-18bt light curve. Regardless, more theoretical work is needed to satisfactorily model this and other early-time SNe~Ia light curves. Finally, we use Swift X-ray non-detections to constrain the presence of circumstellar material (CSM) at much larger distances and lower densities than possible with the optical light curve. For a constant density CSM these non-detections constrain rho<4.5 * 10^5 cm^-3 at a radius of 4 *10^15 cm from the progenitor star. Assuming a wind-like environment, we place mass-loss limits of Mdot< 8 * 10^-6 M_sun yr^-1 for v_w=100 km s^-1, ruling out some symbiotic progenitor systems., Comment: 17 pages, 8 figures, 3 Tables. Accepted to ApJ. This work is part of a number of papers analyzing ASASSN-18bt, with coordinated papers from Dimitriadis et al. (2018) and Li et al. (2018)

Superconducting RF (SRF) photo-injectors are one of the most promising devices for generating continuous wave (CW) electron beams with record high brightness. Ultra-high vacuum of SRF guns provides for long lifetime of the high quantum efficiency (QE) photocathodes, while SRF technology provides for high accelerating gradients exceeding 10 MV/m. It is especially true for low frequency SRF guns where electrons are generated at photocathodes at the crest of accelerating voltage. Two main physics challenges of SRF guns are their compatibility with high QE photocathodes and multipacting. The first is related to a possibility of deposition of photocathode materials (such as Cs) on the walls of the SRF cavity, which can result in increased dark current via reduction of the bulk Nb work function and in enhancing of a secondary electron emission yield (SEY). SEY plays critical role in multipacting, which could both spoil the gun vacuum and speed up the deposition of the cathode material on the walls of the SRF cavity. In short, the multipactor behavior in superconducting accelerating units must be well understood for successful operation of an SRF photo-injector. In this paper we present our studies of 1.2 MV 113 MHz quarter-wave SRF photo-injector serving as a source of electron beam for the Coherent electron Cooling experiment (CeC) at BNL. During three years of operating our SRF gun we encountered a number of multipacting zones. We also observed that presence of $\textrm{CsK}_{2}\textrm{Sb}$ photocathode in the gun could create additional multipacting barriers. We had conducted a comprehensive numerical and experimental study of the multipactor discharge in our SRF gun, and had developed a process of crossing the multipacting barriers from zero to the operational voltage without affecting the lifetime of our photocathode and enhancing the strength of multipacting barriers.

In this paper, we obtain Lyapunov type inequality for discrete fractional boundary value problem., Comment: Main result of this paper requires major correction

In present paper, Hartman-Wintner-type inequality is established for a nonlocal fractional boundary value problem involving k-Prabhakar fractional derivative., Comment: Some major corrections I want Revise

We present optical light curves, redshifts, and classifications for 365 spectroscopically confirmed Type Ia supernovae (SNe Ia) discovered by the Pan-STARRS1 (PS1) Medium Deep Survey. We detail improvements to the PS1 SN photometry, astrometry and calibration that reduce the systematic uncertainties in the PS1 SN Ia distances. We combine the subset of 279 PS1 SN Ia ($0.03 < z < 0.68$) with useful distance estimates of SN Ia from SDSS, SNLS, various low-z and HST samples to form the largest combined sample of SN Ia consisting of a total of 1048 SN Ia ranging from $0.01 < z < 2.3$, which we call the `Pantheon Sample'. When combining Planck 2015 CMB measurements with the Pantheon SN sample, we find $\Omega_m=0.307\pm0.012$ and $w = -1.026\pm0.041$ for the wCDM model. When the SN and CMB constraints are combined with constraints from BAO and local H0 measurements, the analysis yields the most precise measurement of dark energy to date: $w0 = -1.007\pm 0.089$ and $wa = -0.222 \pm0.407$ for the w0waCDM model. Tension with a cosmological constant previously seen in an analysis of PS1 and low-z SNe has diminished after an increase of $2\times$ in the statistics of the PS1 sample, improved calibration and photometry, and stricter light-curve quality cuts. We find the systematic uncertainties in our measurements of dark energy are almost as large as the statistical uncertainties, primarily due to limitations of modeling the low-redshift sample. This must be addressed for future progress in using SN Ia to measure dark energy., Comment: Accepted by ApJ. Data can be found here: http://dx.DOI.org/10.17909/T95Q4X

In this paper, we consider a nonlocal fractional boundary value problem with Prabhakar derivative and obtained a Hartman-Wintner type inequality for it.

We present light curves and classification spectra of 17 hydrogen-poor superluminous supernovae (SLSNe) from the Pan-STARRS1 Medium Deep Survey (PS1 MDS). Our sample contains all objects from the PS1 MDS sample with spectroscopic classification that are similar to either of the prototypes SN2005ap or SN2007bi, without an explicit limit on luminosity. With a redshift range $0.3 < z < 1.6$, PS1MDS is the first SLSN sample primarily probing the high-redshift population; our multi-filter PS1 light curves probe the rest-frame UV emission, and hence the peak of the spectral energy distribution. We measure the temperature evolution and construct bolometric light curves, and find peak luminosities of $(0.5-5) \times 10^{44}$ erg s$^{-1}$ and lower limits on the total radiated energies of $(0.3-2) \times 10^{51}$ erg. The light curve shapes are diverse, with both rise- and decline times spanning a factor of $\sim 5$, and several examples of double-peaked light curves. When correcting for the flux-limited nature of our survey, we find a median peak luminosity at 4000 {\AA} of $M_{\rm 4000} = -21.1$ mag, and a spread of $\sigma = 0.7$ mag., Comment: Matches published version. Minor changes following referee comments; conclusions unchanged

In this paper, Lyapunov type inequality is establish for fractional boundary value problem involving the k-Prabhakar fractional derivative., Comment: 11 Pages