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Machine learning methods are well established in the classification of quasars (QSOs). However, the advent of light curve observations adds a great amount of complexity to the problem. Our goal is to use the Zwicky Transient Facility (ZTF) to create a catalog of QSOs. We process the ZTF DR20 light curves with a transformer artificial neural network and combine the Pan-STARRS (PS), AllWISE, and Gaia surveys with extreme gradient boosting. Using ZTF g-band data with at least 100 observational epochs per light curve, we obtain 97% F1 score for QSOs. We find that with 3 day median cadence, a survey time span of at least 900 days is required to achieve 90% QSO F1 score. However, one can obtain the same score with a survey time span of 1800 days and the median cadence prolonged to 12 days. We find that ZTF classification is superior to the PS static bands, and on par with WISE and Gaia measurements. Additionally, we find that the light curves provide the most important features for QSO classification in the ZTF dataset. We robustly classify objects fainter than the $5\sigma$ SNR limit at $g=20.8$ by requiring $g < \mathrm{n_{obs}} / 80 + 20.375$. For this sample, we run inference with added WISE observations, and find 4,849,574 objects classified as QSOs. For 33% of QZO objects, with available WISE data, we publish redshifts with estimated error $\Delta z/(1 + z) = 0.14$., Comment: We will release the catalog upon acceptance in a journal. The code is available at https://github.com/snakoneczny/ztf-agn

Multi-messenger observations of gravitational waves and electromagnetic emission from compact object mergers offer unique insights into the structure of neutron stars, the formation of heavy elements, and the expansion rate of the Universe. With the LIGO-Virgo-KAGRA (LVK) gravitational-wave detectors currently in their fourth observing run (O4), it is an exciting time for detecting these mergers. However, assessing whether to follow up a candidate gravitational-wave event given limited telescope time and resources is challenging; the candidate can be a false alert due to detector glitches, or may not have any detectable electromagnetic counterpart even if it is real. GWSkyNet-Multi is a deep learning model developed to facilitate follow-up decisions by providing real-time classification of candidate events, using localization information released in LVK rapid public alerts. Here we introduce GWSkyNet-Multi II, an updated model targeted towards providing more robust and informative predictions during O4 and beyond. Specifically, the model now provides normalized probability scores and associated uncertainties for each of the four corresponding source categories released by the LVK: glitch, binary black hole, neutron star-black hole, and binary neutron star. Informed by explainability studies of the original model, the updated model architecture is also significantly simplified, including replacing input images with intuitive summary values, making it more interpretable. For significant O4 event alerts issued between May 2023 and December 2024, GWSkyNet-Multi II produces a prediction that is consistent with the updated LVK classification for 93% of events. The updated model can be used by the community to help make time-critical follow-up decisions., Comment: 19 pages, 6 figures, submitted to ApJ

The OpenUniverse2024 simulation suite is a cross-collaboration effort to produce matched simulated imaging for multiple surveys as they would observe a common simulated sky. Both the simulated data and associated tools used to produce it are intended to uniquely enable a wide range of studies to maximize the science potential of the next generation of cosmological surveys. We have produced simulated imaging for approximately 70 deg$^2$ of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Wide-Fast-Deep survey and the Nancy Grace Roman Space Telescope High-Latitude Wide-Area Survey, as well as overlapping versions of the ELAIS-S1 Deep-Drilling Field for LSST and the High-Latitude Time-Domain Survey for Roman. OpenUniverse2024 includes i) an early version of the updated extragalactic model called Diffsky, which substantially improves the realism of optical and infrared photometry of objects, compared to previous versions of these models; ii) updated transient models that extend through the wavelength range probed by Roman and Rubin; and iii) improved survey, telescope, and instrument realism based on up-to-date survey plans and known properties of the instruments. It is built on a new and updated suite of simulation tools that improves the ease of consistently simulating multiple observatories viewing the same sky. The approximately 400 TB of synthetic survey imaging and simulated universe catalogs are publicly available, and we preview some scientific uses of the simulations.

We present the discovery of 14 new (and recovery of 4 known) low accretion rate magnetic white dwarfs in post-common envelope binaries that emit strong cyclotron emission using the Zwicky Transient Facility (ZTF) light curves, doubling the known sample size. In addition, we discovered a candidate magnetic period bouncer and recovered three known ones. We confirmed the presence of cyclotron emission using low-resolution spectra in 19 objects. Using the ZTF light curves, follow-up spectra, and the spectral energy distribution, we measured the orbital period, magnetic field strength, and white dwarf temperature of each system. Although the phase-folded light curves have diverse shapes and show a much larger variability amplitude, we show that their intrinsic properties (e.g. period distribution, magnetic field strength) are similar to those of previously known systems. The diversity in light curve shapes can be explained by differences in the optical depth of the accretion spot and geometric differences, the inclination angle and the magnetic spot latitude. The evolutionary states of the longer period binaries are somewhat uncertain but are vary; we found systems consistent with being pre-polars, detached polars, or low-state polars. In addition, we discovered two new low-state polars that likely have brown dwarf companions and could be magnetic period bouncers.

Supernovae (SNe) come in various flavors and are classified into different types based on emission and absorption lines in their spectra. SN candidates are now abundant with the advent of large systematic dynamic sky surveys like the Zwicky Transient Facility (ZTF), however, the identification bottleneck lies in their spectroscopic confirmation and classification. Fully robotic telescopes with dedicated spectrographs optimized for SN follow-up have eased the burden of data acquisition. However, the task of classifying the spectra still largely rests with the astronomers. Automating this classification step reduces human effort, and can make the SN type available sooner to the public. For this purpose, we have developed a deep-learning based program for classifying core-collapse supernovae (CCSNe) with ultra-low resolution spectra obtained with the SED-Machine IFU spectrograph on the Palomar 60-inch telescope. The program consists of hierarchical classification task layers, with each layer composed of multiple binary classifiers which are run in parallel to produce a reliable classification. The binary classifiers utilize RNN and CNN architecture and are designed to take multiple inputs, to supplement spectra with g- and r-band photometry from ZTF. On non-host-contaminated and good quality SEDM spectra ("gold" test set), CCSNscore is ~94% accurate (correct classifications) in distinguishing between hydrogen-rich (Type II) and hydrogen-poor (Type Ibc) CCSNe. With the help of light curve input, CCSNscore classifies ~83% of the gold set with high confidence (score >= 0.8 and score-error < 0.05), with ~98% accuracy., Comment: Submitted to PASP

Motivated by the scarcity of proper labels in an astrophysical application, we have developed a novel technique, called Selfish Evolution, which allows for the detection and correction of corrupted labels in a weakly supervised fashion. Unlike methods based on early stopping, we let the model train on the noisy dataset. Only then do we intervene and allow the model to overfit to individual samples. The ``evolution'' of the model during this process reveals patterns with enough information about the noisiness of the label, as well as its correct version. We train a secondary network on these spatiotemporal ``evolution cubes'' to correct potentially corrupted labels. We incorporate the technique in a closed-loop fashion, allowing for automatic convergence towards a mostly clean dataset, without presumptions about the state of the network in which we intervene. We evaluate on the main task of the Supernova-hunting dataset but also demonstrate efficiency on the more standard MNIST dataset.

We report the discovery of three ultracompact binary white dwarf systems hosting accretion disks, with orbital periods of 7.95, 8.68, and 13.15 minutes. This significantly augments the population of mass-transferring binaries at the shortest periods, and provides the first evidence that accretors in ultracompacts can be dense enough to host accretion disks even below 10 minutes (where previously only direct-impact accretors were known). In the two shortest-period systems, we measured changes in the orbital periods driven by the combined effect of gravitational wave emission and mass transfer; we find $\dot{P}$ is negative in one case, and positive in the other. This is only the second system measured with a positive $\dot{P}$, and it the most compact binary known that has survived a period minimum. Using these systems as examples, we show how the measurement of $\dot{P}$ is a powerful tool in constraining the physical properties of binaries, e.g. the mass and mass-radius relation of the donor stars. We find that the chirp masses of ultracompact binaries at these periods seem to cluster around $\mathcal{M}_c \sim 0.3 M_\odot$, perhaps suggesting a common origin for these systems or a selection bias in electromagnetic discoveries. Our new systems are among the highest-amplitude known gravitational wave sources in the millihertz regime, providing exquisite opportunity for multi-messenger study with future space-based observatories such as \textit{LISA} and TianQin; we discuss how such systems provide fascinating laboratories to study the unique regime where the accretion process is mediated by gravitational waves., Comment: Accepted for publication in ApJ

Near-sun sky twilight observations allow for the detection of asteroid interior to the orbit of Venus (Aylos), the Earth (Atiras), and comets. We present the results of observations with the Palomar 48-inch telescope (P48)/Zwicky Transient Facility (ZTF) camera in 30 s r-band exposures taken during evening astronomical twilight from 2019 Sep 20 to 2022 March 7 and during morning astronomical twilight sky from 2019 Sep 21 to 2022 Sep 29. More than 46,000 exposures were taken in evening and morning astronomical twilight within 31 to 66 degrees from the Sun with an r-band limiting magnitude between 18.1 and 20.9. The twilight pointings show a slight seasonal dependence in limiting magnitude and ability to point closer towards the Sun, with limiting magnitude slightly improving during summer. In total, the one Aylo, (594913) 'Ayl\'o'chaxnim, and 4 Atiras, 2020 OV1, 2021 BS1, 2021 PB2, and 2021 VR3, were discovered in evening and morning twilight observations. Additional twilight survey discoveries also include 6 long-period comets: C/2020 T2, C/2020 V2, C/2021 D2, C/2021 E3, C/2022 E3, and C/2022 P3, and two short-period comets: P/2021 N1 and P/2022 P2 using deep learning comet detection pipelines. The P48/ZTF twilight survey also recovered 11 known Atiras, one Aylo, three short-period comes, two long-period comets, and one interstellar object. Lastly, the Vera Rubin Observatory will conduct a twilight survey starting in its first year of operations and will cover the sky within 45 degrees of the Sun. Twilight surveys such as those by ZTF and future surveys will provide opportunities for discovering asteroids inside the orbits of Earth and Venus., Comment: 26 pages, 13 figures, 4 tables, accepted for publication in Icarus

Electromagnetic follow-up observations of gravitational wave events offer critical insights and provide significant scientific gain from this new class of astrophysical transients. Accurate identification of gravitational wave candidates and rapid release of sky localization information are crucial for the success of these electromagnetic follow-up observations. However, searches for gravitational wave candidates in real time suffer a non-negligible false alarm rate. By leveraging the sky localization information and other metadata associated with gravitational wave candidates, GWSkyNet, a machine learning classifier developed by Cabero et al. (2020), demonstrated promising accuracy for the identification of the origin of event candidates. We improve the performance of the classifier for LIGO-Virgo-KAGRA's fourth observing run by reviewing and updating the architecture and features used as inputs by the algorithm. We also retrain and fine-tune the classifier with data from the third observing run. To improve the prospect of electromagnetic follow-up observations, we incorporate GWSkyNet into LIGO-Virgo-KAGRA's low-latency infrastructure as an automatic pipeline for the evaluation of gravitational wave alerts in real time. We test the readiness of the algorithm on a LIGO-Virgo-KAGRA mock data challenge campaign. The results show that by thresholding on the GWSkyNet score, noise masquerading as astrophysical sources can be rejected efficiently and the majority of true astrophysical signals correctly identified.

Owens Valley Radio Observatory (OVRO) observations of supermassive black hole binary (SMBHB) candidate PKS~2131$-$021 revealed, for the first time, six likely characteristics of the phenomenology exhibited by SMBHB in blazars, of which the most unexpected and critical is sinusoidal flux density variations. We have now identified a second blazar, PKS~J0805$-$0111, showing significant sinusoidal variations, with an observed period that translates to $1.422 \pm 0.005$ yr in the rest frame of the $z = 1.388$ object. We generate $10^6$ simulated light curves to reproduce the radio variability characteristics of PKS~J0805$-$0111, and show that the global probability, considering the \textit{look-elsewhere effect}, indicates that the observed periodicity can be attributed to the red noise tail of the power spectral density, with a $p_0$ value of $7.8 \times 10^{-5}$ (i.e. 3.78$\sigma$). PKS J0805$-$0111 displays all six characteristics observed in PKS 2131$-$021. Taking into account the well-defined OVRO sample size, the false positive probability $\sim 0.22$, but the rare behavior makes this a strong SMBHB candidate. The discovery of a second SMBHB candidate exhibiting these rare characteristics reveals that PKS~2131$-$021 is not a unique, isolated case. With these two strong cases we are clearly seeing only the tip of the iceberg. We estimate that the number of SMBHB candidates amongst blazars $\sim$ 1 in 100.

During the first half of the fourth observing run (O4a) of the International Gravitational Wave Network (IGWN), the Zwicky Transient Facility (ZTF) conducted a systematic search for kilonova (KN) counterparts to binary neutron star (BNS) and neutron star-black hole (NSBH) merger candidates. Here, we present a comprehensive study of the five high-significance (FAR < 1 per year) BNS and NSBH candidates in O4a. Our follow-up campaigns relied on both target-of-opportunity observations (ToO) and re-weighting of the nominal survey schedule to maximize coverage. We describe the toolkit we have been developing, Fritz, an instance of SkyPortal, instrumental in coordinating and managing our telescope scheduling, candidate vetting, and follow-up observations through a user-friendly interface. ZTF covered a total of 2841 deg$^2$ within the skymaps of the high-significance GW events, reaching a median depth of g~20.2 mag. We circulated 15 candidates, but found no viable KN counterpart to any of the GW events. Based on the ZTF non-detections of the high-significance events in O4a, we used a Bayesian approach, nimbus, to quantify the posterior probability of KN model parameters that are consistent with our non-detections. Our analysis favors KNe with initial absolute magnitude fainter than -16 mag. The joint posterior probability of a GW170817-like KN associated with all our O4a follow-ups was 64%. Additionally, we use a survey simulation software, simsurvey, to determine that our combined filtered efficiency to detect a GW170817-like KN is 36%, when considering the 5 confirmed astrophysical events in O3 (1 BNS and 4 NSBH), along with our O4a follow-ups. Following Kasliwal et al. (2020), we derived joint constraints on the underlying KN luminosity function based on our O3 and O4a follow-ups, determining that no more than 76% of KNe fading at 1 mag/day can peak at a magnitude brighter than -17.5 mag., Comment: submitted

We present the tidal disruption event (TDE) AT2022lri, hosted in a nearby ($\approx\!144$ Mpc) quiescent galaxy with a low-mass massive black hole ($10^4\,M_\odot < M_{\rm BH} < 10^6\,M_\odot$). AT2022lri belongs to the TDE-H+He subtype. More than 1 Ms of X-ray data were collected with NICER, Swift, and XMM-Newton from 187 d to 672 d after peak. The X-ray luminosity gradually declined from $1.5\times 10^{44}\,{\rm erg\,s^{-1}}$ to $1.5\times 10^{43}\,{\rm erg\,s^{-1}}$ and remains much above the UV and optical luminosity, consistent with a super-Eddington accretion flow viewed face-on. Sporadic strong X-ray dips atop a long-term decline are observed, with variability timescale of $\approx\!0.5$ hr--1 d and amplitude of $\approx\!2$--8. When fitted with simple continuum models, the X-ray spectrum is dominated by a thermal disk component with inner temperature going from $\sim\! 146$ eV to $\sim\! 86$ eV. However, there are residual features that peak around 1 keV, which, in some cases, cannot be reproduced by a single broad emission line. We analyzed a subset of time-resolved spectra with two physically motivated models describing either a scenario where ionized absorbers contribute extra absorption and emission lines or where disk reflection plays an important role. Both models provide good and statistically comparable fits, show that the X-ray dips are correlated with drops in the inner disk temperature, and require the existence of sub-relativistic (0.1--0.3$c$) ionized outflows. We propose that the disk temperature fluctuation stems from episodic drops of the mass accretion rate triggered by magnetic instabilities or/and wobbling of the inner accretion disk along the black hole's spin axis., Comment: 35 pages, 20 figures, submitted

The rise of synoptic sky surveys has ushered in an era of big data in time-domain astronomy, making data science and machine learning essential tools for studying celestial objects. While tree-based models (e.g. Random Forests) and deep learning models dominate the field, we explore the use of different distance metrics to aid in the classification of astrophysical objects. We developed DistClassiPy, a new distance metric based classifier. The direct use of distance metrics is unexplored in time-domain astronomy, but distance-based methods can help make classification more interpretable and decrease computational costs. In particular, we applied DistClassiPy to classify light curves of variable stars, comparing the distances between objects of different classes. Using 18 distance metrics on a catalog of 6,000 variable stars across 10 classes, we demonstrate classification and dimensionality reduction. Our classifier meets state-of-the-art performance but has lower computational requirements and improved interpretability. Additionally, DistClassiPy can be tailored to specific objects by identifying the most effective distance metric for that classification. To facilitate broader applications within and beyond astronomy, we have made DistClassiPy open-source and available at https://pypi.org/project/distclassipy/., Comment: Accepted for publication in Astronomy and Computing (2024). 24 pages, 19 figures

We present SN 2023zaw $-$ a sub-luminous ($\mathrm{M_r} = -16.7$ mag) and rapidly-evolving supernova ($\mathrm{t_{1/2,r}} = 4.9$ days), with the lowest nickel mass ($\approx0.002$ $\mathrm{M_\odot}$) measured among all stripped-envelope supernovae discovered to date. The photospheric spectra are dominated by broad He I and Ca NIR emission lines with velocities of $\sim10\ 000 - 12\ 000$ $\mathrm{km\ s^{-1}}$. The late-time spectra show prominent narrow He I emission lines at $\sim$1000$\ \mathrm{km\ s^{-1}}$, indicative of interaction with He-rich circumstellar material. SN 2023zaw is located in the spiral arm of a star-forming galaxy. We perform radiation-hydrodynamical and analytical modeling of the lightcurve by fitting with a combination of shock-cooling emission and nickel decay. The progenitor has a best-fit envelope mass of $\approx0.2$ $\mathrm{M_\odot}$ and an envelope radius of $\approx50$ $\mathrm{R_\odot}$. The extremely low nickel mass and low ejecta mass ($\approx0.5$ $\mathrm{M_\odot}$) suggest an ultra-stripped SN, which originates from a mass-losing low mass He-star (ZAMS mass $<$ 10 $\mathrm{M_\odot}$) in a close binary system. This is a channel to form double neutron star systems, whose merger is detectable with LIGO. SN 2023zaw underscores the existence of a previously undiscovered population of extremely low nickel mass ($< 0.005$ $\mathrm{M_\odot}$) stripped-envelope supernovae, which can be explored with deep and high-cadence transient surveys., Comment: Accepted for publication in ApJL

Policy Brief on "Regional and Global Collaborations in Astronomy", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Astronomy brings together advanced scientific research, state-of-the-art technology, and educational initiatives, all while captivating and stimulating people of all ages. By doing so, it possesses the potential to serve as a powerful catalyst for sustainable global development and the resolution of global societal issues. It attracts a diverse range of scientists and experts from various fields, fostering collaboration and innovation. By leveraging their resources, influence, and diplomatic initiatives, S20 academies can foster an enabling environment for international collaborations in astronomy, facilitate knowledge exchange, and drive scientific advancements that benefit humanity. This policy brief explores the opportunities and challenges presented by regional and global collaborations in astronomy. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623., Comment: 6 pages. The panel videos including keynotes and the white papers are available on the S20 site at: https://s20india.org/science-policy-webinar-astroinformatics-for-sustainable-development/

Policy Brief on "Large Projects in Astronomy: An Indian Endeavour", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Cutting-edge astronomy initiatives often entail substantial investment and require a high level of expertise. Even the most technologically advanced nations recognize the value of establishing international partnerships to secure both financial resources and talent for these ambitious endeavours as they hold immense promise for catalysing transformative scientific discoveries, driving technological innovation, provide training opportunities for the next generation of scientists and engineers, and expanding our understanding of the cosmos that surrounds us. Crucially, large-scale multilateral collaborations serve as powerful agents for promoting unity and peace among the global population. Participants from various nations share a vested interest in the success of these projects and the wealth of knowledge they yield, fostering a sense of common purpose and shared goals. By utilizing astroinformatics capabilities, these initiatives are not merely enhancing our comprehension of the universe but are also actively contributing to the attainment of sustainable development objectives. In this discussion, we delve into the challenges faced, and prospects for substantial astronomical undertakings. Additionally, we present recommendations aimed at guaranteeing their effectiveness and optimizing their influence on both scientific advancement and society. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623., Comment: 4 pages. The panel videos including keynotes and the white papers are available on the S20 site at: https://s20india.org/science-policy-webinar-astroinformatics-for-sustainable-development/

Policy Brief on "Long Term Space Data and Informatics Needs", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Persistent space data gathering, retention, transmission, and analysis play a pivotal role in deepening our grasp of the Universe and fostering the achievement of global sustainable development goals. Long-term data storage and curation is crucial not only to make the wide range of burgeoning data sets available to the global science community, but also to stabilize those data sets, enabling new science in the future to analyse long-term trends over unprecedented time spans. In addition to this, over the long-term, the imperative to store all data on the ground should be ameliorated by use of space-based data stores --maintained and seen to be as reliable as any other data archive. This concept is sometimes referred to as Memory of the Sky. Storing the data must be accompanied by the ability to analyse them. Several concepts covered below acknowledge roots and inspiration based in the Virtual Observatory effort. Within this policy document, we delve into the complexities surrounding the long-term utilization of space data and informatics, shedding light on the challenges and opportunities inherent in this endeavour. Further, we present a series of pragmatic recommendations designed to address these challenges proactively. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623., Comment: 5 pages. The panel videos including keynotes and the white papers are available on the S20 site at: https://s20india.org/science-policy-webinar-astroinformatics-for-sustainable-development/

Policy Brief on "Workforce Development in Astronomy and Astroinformatics", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. The discipline of astronomy and astroinformatics is dynamically evolving thereby creating a compelling opportunity to foster a more inclusive, diverse, and proficient workforce. This is crucial for addressing multifaceted challenges that emerge as we progress and harness the potential therein. To realize this goal, it's imperative to cultivate strategies that promote inclusive practices in STEM education, encourage participation from historically excluded groups, provide training and mentorship, as well as provide active champions, especially for students and early career professionals from (historically) excluded groups. We provide an overview of the current status, resources available, and possible steps especially keeping in mind large international projects. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623., Comment: 6 pages. The panel videos including keynotes and the white papers are available on the S20 site at: https://s20india.org/science-policy-webinar-astroinformatics-for-sustainable-development/

Policy Brief on "Latest Developments and Opportunities in Sky Survey", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Sky surveys have been a crucial tool in advancing our understanding of the Universe. The last few decades have seen an explosion in the number and scope of sky surveys, both ground-based and space-based. This growth has led to a wealth of data that has enabled us to make significant advances in many areas of astronomy, and help understand the physics of the universe. They have helped us discover new astronomical objects, the origin of the elements, dark matter and dark energy, the accelerated expansion of the universe, and gravitational waves. They have helped us study the distribution of neutral and ionized matter in the Universe and test our theories about the origin and evolution of galaxies, stars, and planets. We explore recent advances and potential avenues in sky surveys, and examine how these developments may impact the field of international astronomical research. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623., Comment: 5 pages. The panel videos including keynotes and the white papers are available on the S20 site at: https://s20india.org/science-policy-webinar-astroinformatics-for-sustainable-development/

Policy Brief on "Global Data in Astronomy: Challenges and Opportunities", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Astronomy is increasingly becoming a data-driven science. Advances in our understanding of the physical mechanisms at work in the Universe require building ever-more sensitive telescopes to gather observations of the cosmos to test and advance our theoretical models of how the universe works. To confront the observed data with our theoretical models we require data hosting, archiving and storage and high-performance computing resources to run the theoretical calculations and compare our simulated and observed universe. We also require the sophisticated development of highly skilled human resources. Newer large projects are often run through international collaborations and partnerships, driving a need for 'open science' and collaborative structure across national boundaries. While astronomical data are useful scientifically, the data do not come with the same ethical/privacy-related restrictions as medical/biological data. Moreover, the ability to use data for new scientific analysis extends and expands the impact and reach of scientific surveys -- this is a strength that national funding agencies should capitalize on. We discuss the management and analysis of such large volumes of data and the corresponding significant challenges that require policy-level preparations. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623., Comment: 5 pages. The panel videos including keynotes and the white papers are available on the S20 site at: https://s20india.org/science-policy-webinar-astroinformatics-for-sustainable-development/

The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright ($m_\mathrm{peak}\,\leq\,18.5\,$mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection ("scanning") to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past $\sim5$ yr of ZTF operations. We present $\texttt{BTSbot}$, a multi-modal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. $\texttt{BTSbot}$ is able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. $\texttt{BTSbot}$ recovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, $\sim$1 hour quicker than scanners). We also find that $\texttt{BTSbot}$ is not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates. $\texttt{BTSbot}$ has been integrated into Fritz and $\texttt{Kowalski}$, ZTF's first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. During the month of October 2023, $\texttt{BTSbot}$ selected 296 sources in real-time, 93% of which were real extragalactic transients. With $\texttt{BTSbot}$ and other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human-time needed to scan. Future development has tremendous potential for creating similar models to identify and request follow-up observations for specific types of transients., Comment: 26 pages, 12 figures; to be submitted to ApJ; comments welcome

Policy Brief on "AstroInformatics, Recommendations for Global Collaboration", distilled from panel discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. The deliberations encompassed a wide array of topics, including broad astroinformatics, sky surveys, large-scale international initiatives, global data repositories, space-related data, regional and international collaborative efforts, as well as workforce development within the field. These discussions comprehensively addressed the current status, notable achievements, and the manifold challenges that the field of astroinformatics currently confronts. The G20 nations present a unique opportunity due to their abundant human and technological capabilities, coupled with their widespread geographical representation. Leveraging these strengths, significant strides can be made in various domains. These include, but are not limited to, the advancement of STEM education and workforce development, the promotion of equitable resource utilization, and contributions to fields such as Earth Science and Climate Science. We present a concise overview, followed by specific recommendations that pertain to both ground-based and space data initiatives. Our team remains readily available to furnish further elaboration on any of these proposals as required. Furthermore, we anticipate further engagement during the upcoming G20 presidencies in Brazil (2024) and South Africa (2025) to ensure the continued discussion and realization of these objectives. The policy webinar took place during the G20 presidency in India (2023). Notes based on the seven panels will be separately published., Comment: 7 pages

Context. Accreting ultracompact binaries contain a white dwarf that is accreting from a degenerate object and have orbital periods shorter than 65 minutes. Aims. The aims of this letter are to report the discovery and the orbital period of four new eclipsing accreting ultracompact binaries found using the Zwicky Transient Facility, and to discuss their photometric properties. Methods. We searched through a list of 4171 dwarf novae compiled using the Zwicky Transient Facility and used the Box Least Square method to search for periodic signals in the data. Results. We found four new eclipsing accreting ultracompact binaries with orbital periods between 25.9-56 minutes, one of which is previously published as an AM CVn, while the other three systems are new discoveries. The other two shorter period systems are likely also AM CVn systems, while the longest period system with a period of 56 minutes shows multiple super-outbursts observed in two years which is more consistent with it being a Helium-CV., Comment: Submitted to A&A

Gravitational lensing is proven to be one of the most efficient tools for studying the Universe. The spectral confirmation of such sources requires extensive calibration. This paper discusses the spectral extraction technique for the case of multiple source spectra being very near each other. Using the masking technique, we first detect high Signal-to-Noise (S/N) peaks in the CCD spectral image corresponding to the location of the source spectra. This technique computes the cumulative signal using a weighted sum, yielding a reliable approximation for the total counts contributed by each source spectrum. We then proceed with the subtraction of the contaminating spectra. Applying this method, we confirm the nature of 11 lensed quasar candidates., Comment: Accepted for publication in Bulletin de la Soci\'et\'e Royale des Sciences de Li\`ege (BSRSL)

The classification of variable objects provides insight into a wide variety of astrophysics ranging from stellar interiors to galactic nuclei. The Zwicky Transient Facility (ZTF) provides time series observations that record the variability of more than a billion sources. The scale of these data necessitates automated approaches to make a thorough analysis. Building on previous work, this paper reports the results of the ZTF Source Classification Project (SCoPe), which trains neural network and XGBoost machine learning (ML) algorithms to perform dichotomous classification of variable ZTF sources using a manually constructed training set containing 170,632 light curves. We find that several classifiers achieve high precision and recall scores, suggesting the reliability of their predictions for 209,991,147 light curves across 77 ZTF fields. We also identify the most important features for XGB classification and compare the performance of the two ML algorithms, finding a pattern of higher precision among XGB classifiers. The resulting classification catalog is available to the public, and the software developed for SCoPe is open-source and adaptable to future time-domain surveys., Comment: 23 pages, 12 figures, accepted to ApJS. Catalog available at https://zenodo.org/doi/10.5281/zenodo.8410825

Optical surveys have become increasingly adept at identifying candidate Tidal Disruption Events (TDEs) in large numbers, but classifying these generally requires extensive spectroscopic resources. Here we present $\texttt{tdescore}$, a simple binary photometric classifier that is trained using a systematic census of $\sim$3000 nuclear transients from the Zwicky Transient Facility (ZTF). The sample is highly imbalanced, with TDEs representing $\sim$2% of the total. $\texttt{tdescore}$ is nonetheless able to reject non-TDEs with 99.6% accuracy, yielding a sample of probable TDEs with recall of 77.5% for a precision of 80.2%. $\texttt{tdescore}$ is thus substantially better than any available TDE photometric classifier scheme in the literature, with performance not far from spectroscopy as a method for classifying ZTF nuclear transients, despite relying solely on ZTF data and multi-wavelength catalogue cross-matching. In a novel extension, we use `SHapley Additive exPlanations' ($\texttt{SHAP}$) to provide a human-readable justification for each individual $\texttt{tdescore}$ classification, enabling users to understand and form opinions about the underlying classifier reasoning. $\texttt{tdescore}$ can serve as a model for photometric identification of TDEs with time-domain surveys, such as the upcoming Rubin observatory., Comment: Accepted for publication, 16 pages, 7 figures, 2 tables

In recent years, certain luminous extragalactic optical transients have been observed to last only a few days. Their short observed duration implies a different powering mechanism from the most common luminous extragalactic transients (supernovae) whose timescale is weeks. Some short-duration transients, most notably AT2018cow, display blue optical colours and bright radio and X-ray emission. Several AT2018cow-like transients have shown hints of a long-lived embedded energy source, such as X-ray variability, prolonged ultraviolet emission, a tentative X-ray quasiperiodic oscillation, and large energies coupled to fast (but subrelativistic) radio-emitting ejecta. Here we report observations of minutes-duration optical flares in the aftermath of an AT2018cow-like transient, AT2022tsd (the "Tasmanian Devil"). The flares occur over a period of months, are highly energetic, and are likely nonthermal, implying that they arise from a near-relativistic outflow or jet. Our observations confirm that in some AT2018cow-like transients the embedded energy source is a compact object, either a magnetar or an accreting black hole., Comment: 79 pages, 3 figures (main text) + 7 figures (extended data) + 2 figures (supplementary information). Published online in Nature on 15 November 2023

We report observations of the optical counterpart of the long gamma-ray burst (LGRB) GRB 230812B, and its associated supernova (SN) SN 2023pel. The proximity ($z = 0.36$) and high energy ($E_{\gamma, \rm{iso}} \sim 10^{53}$ erg) make it an important event to study as a probe of the connection between massive star core-collapse and relativistic jet formation. With a phenomenological power-law model for the optical afterglow, we find a late-time flattening consistent with the presence of an associated SN. SN 2023pel has an absolute peak $r$-band magnitude of $M_r = -19.46 \pm 0.18$ mag (about as bright as SN 1998bw) and evolves on quicker timescales. Using a radioactive heating model, we derive a nickel mass powering the SN of $M_{\rm{Ni}} = 0.38 \pm 0.01$ $\rm{M_\odot}$, and a peak bolometric luminosity of $L_{\rm{bol}} \sim 1.3 \times 10^{43}$ $\rm{erg}$ $\rm{s^{-1}}$. We confirm SN 2023pel's classification as a broad-lined Type Ic SN with a spectrum taken 15.5 days after its peak in $r$ band, and derive a photospheric expansion velocity of $v_{\rm{ph}} = 11,300 \pm 1,600$ $\rm{km}$ $\rm{s^{-1}}$ at that phase. Extrapolating this velocity to the time of maximum light, we derive the ejecta mass $M_{\rm{ej}} = 1.0 \pm 0.6$ $\rm{M_\odot}$ and kinetic energy $E_{\rm{KE}} = 1.3^{+3.3}_{-1.2} \times10^{51}$ $\rm{erg}$. We find that GRB 230812B/SN 2023pel has SN properties that are mostly consistent with the overall GRB-SN population. The lack of correlations found in the GRB-SN population between SN brightness and $E_{\gamma, \rm{iso}}$ for their associated GRBs, across a broad range of 7 orders of magnitude, provides further evidence that the central engine powering the relativistic ejecta is not coupled to the SN powering mechanism in GRB-SN systems., Comment: 21 pages, 7 Figures, 1 Table, Accepted to ApJ Letters

Long-period comets are planetesimal remnants constraining the environment and volatiles of the protoplanetary disc. We report the discovery of hyperbolic long-period comet C/2022 E3 (ZTF), which has a perihelion $\sim$1.11 au, an eccentricity $\gtrsim$1 and an inclination $\sim$109$^{\circ}$, from images taken with the Palomar 48-inch telescope during morning twilight on 2022 Mar 2. Additionally, we report the characterization of C/2022 E3 (ZTF) from observations taken with the Palomar 200-inch, the Palomar 60-inch, and the NASA Infrared Telescope Facility in early 2023 February to 2023 March when the comet passed within $\sim$0.28 au of the Earth and reached a visible magnitude of $\sim$5. We measure g-r = 0.70$\pm$0.01, r-i = 0.20$\pm$0.01, i-z = 0.06$\pm$0.01, z-J = 0.90$\pm$0.01, J-H = 0.38$\pm$0.01 and H-K = 0.15$\pm$0.01 colours for the comet from observations. We measure the A(0$^\circ$)f$\rho$ (0.8~$\mu$m) in a 6500~km radius from the nucleus of 1483$\pm$40~cm, and CN, C$_3$, and C$_2$ production of 5.43$\pm0.11\times$10$^{25}$~mol/s, 2.01$\pm0.04\times$10$^{24}$, and 3.08$\pm0.5\times$10$^{25}$~mol/s, similar to other long period comets. We additionally observe the appearance of jet-like structures at a scale of $\sim$4,000 km in wide-field g-band images, which may be caused by the presence of CN gas in the near-nucleus coma., Comment: Accepted for publication in MNRAS:L, 9 pages, 6 figures, 2 tables

Humanity has wondered whether we are alone for millennia. The discovery of life elsewhere in the Universe, particularly intelligent life, would have profound effects, comparable to those of recognizing that the Earth is not the center of the Universe and that humans evolved from previous species. There has been rapid growth in the fields of extrasolar planets and data-driven astronomy. In a relatively short interval, we have seen a change from knowing of no extrasolar planets to now knowing more potentially habitable extrasolar planets than there are planets in the Solar System. In approximately the same interval, astronomy has transitioned to a field in which sky surveys can generate 1 PB or more of data. The Data-Driven Approaches to Searches for the Technosignatures of Advanced Civilizations_ study at the W. M. Keck Institute for Space Studies was intended to revisit searches for evidence of alien technologies in light of these developments. Data-driven searches, being able to process volumes of data much greater than a human could, and in a reproducible manner, can identify *anomalies* that could be clues to the presence of technosignatures. A key outcome of this workshop was that technosignature searches should be conducted in a manner consistent with Freeman Dyson's "First Law of SETI Investigations," namely "every search for alien civilizations should be planned to give interesting results even when no aliens are discovered." This approach to technosignatures is commensurate with NASA's approach to biosignatures in that no single observation or measurement can be taken as providing full certainty for the detection of life. Areas of particular promise identified during the workshop were (*) Data Mining of Large Sky Surveys, (*) All-Sky Survey at Far-Infrared Wavelengths, (*) Surveys with Radio Astronomical Interferometers, and (*) Artifacts in the Solar System., Comment: Final Report prepared for the W. M. Keck Institute for Space Studies (KISS), http://kiss.caltech.edu/workshops/technosignatures/technosignatures.html ; eds. Lazio, Djorgovski, Howard, & Cutler; The study leads gratefully acknowledge the outstanding support of Michele Judd, KISS Executive Director, and her dedicated staff, who made the study experience invigorating and enormously productive

In this paper, we propose first a mmWave channel tracking algorithm based on multidimensional orthogonal matching pursuit algorithm (MOMP) using reduced sparsifying dictionaries, which exploits information from channel estimates in previous frames. Then, we present an algorithm to obtain the vehicle's initial location for the current frame by solving a system of geometric equations that leverage the estimated path parameters. Next, we design an attention network that analyzes the series of channel estimates, the vehicle's trajectory, and the initial estimate of the position associated with the current frame, to generate a refined, high accuracy position estimate. The proposed system is evaluated through numerical experiments using realistic mmWave channel series generated by ray-tracing. The experimental results show that our system provides a 2D position tracking error below 20 cm, significantly outperforming previous work based on Bayesian filtering.

GWSkyNet-Multi is a machine learning model developed for classification of candidate gravitational-wave events detected by the LIGO and Virgo observatories. The model uses limited information released in the low-latency Open Public Alerts to produce prediction scores indicating whether an event is a merger of two black holes, a merger involving a neutron star, or a non-astrophysical glitch. This facilitates time sensitive decisions about whether to perform electromagnetic follow-up of candidate events during LIGO-Virgo-KAGRA (LVK) observing runs. However, it is not well understood how the model is leveraging the limited information available to make its predictions. As a deep learning neural network, the inner workings of the model can be difficult to interpret, impacting our trust in its validity and robustness. We tackle this issue by systematically perturbing the model and its inputs to explain what underlying features and correlations it has learned for distinguishing the sources. We show that the localization area of the 2D sky maps and the computed coherence versus incoherence Bayes factors are used as strong predictors for distinguishing between real events and glitches. The estimated distance to the source is further used to discriminate between binary black hole mergers and mergers involving neutron stars. We leverage these findings to show that events misclassified by GWSkyNet-Multi in LVK's third observing run have distinct sky area, coherence factor, and distance values that influence the predictions and explain these misclassifications. The results help identify the model's limitations and inform potential avenues for further optimization., Comment: 22 pages, 11 figures, submitted to ApJ

Binary neutron star mergers and neutron star-black hole mergers are multi-messenger sources that can be detected in gravitational waves and in electromagnetic radiation. The low electron fraction of neutron star merger ejecta favors the production of heavy elements such as lanthanides and actinides via rapid neutron capture (r-process). The decay of these unstable nuclei powers an infrared-bright transient called a "kilonova". The discovery of a population of kilonovae will allow us to determine if neutron star mergers are the dominant sites for r-process element nucleosynthesis, constrain the equation of state of nuclear matter, and make independent measurements of the Hubble constant. The Nancy Grace Roman Space Telescope (Roman) will have a unique combination of depth, near-infrared sensitivity, and wide field of view. These characteristics will enable Roman's discovery of GW counterparts that will be missed by optical telescopes, such as kilonova that are associated with large distances, high lanthanide fractions, high binary mass-ratios, large dust extinction in the line of sight, or that are observed from equatorial viewing angles. Our analysis suggests to (i) make available a rapid (about 1 week) Target of Opportunity mode for GW follow-up; (ii) include observations of the High Latitude Time-Domain survey footprint in at least two filters (preferably the F158 and F213 filters) with a cadence of < 8 days; (iii) operate in synergy with Rubin Observatory. Following these recommendations, we expect that 1-6 kilonovae can be identified by Roman via ToO observations of well localized (A < 10 sq. deg., 90% C.I.) neutron star mergers during 1.5 years of the LIGO-Virgo-KAGRA fifth (or about 4-21 in during the sixth) observing run. A sample of 5-40 serendipitously discovered kilonovae can be collected in a 5-year high latitude survey., Comment: accepted for publication in Astroparticle Physics

Optical polarimeters are typically calibrated using measurements of stars with known and stable polarization parameters. However, there is a lack of such stars available across the sky. Many of the currently available standards are not suitable for medium and large telescopes due to their high brightness. Moreover, as we find, some of the used polarimetric standards are in fact variable or have polarization parameters that differ from their cataloged values. Our goal is to establish a sample of stable standards suitable for calibrating linear optical polarimeters with an accuracy down to $10^{-3}$ in fractional polarization. For five years, we have been running a monitoring campaign of a sample of standard candidates comprised of 107 stars distributed across the northern sky. We analyzed the variability of the linear polarization of these stars, taking into account the non-Gaussian nature of fractional polarization measurements. For a subsample of nine stars, we also performed multiband polarization measurements. We created a new catalog of 65 stars (see Table 2) that are stable, have small uncertainties of measured polarimetric parameters, and can be used as calibrators of polarimeters at medium- and large-size telescopes.

SkyPortal is an open-source software package designed to efficiently discover interesting transients, manage follow-up, perform characterization, and visualize the results. By enabling fast access to archival and catalog data, cross-matching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, a SkyPortal-based platform has been operating at scale for 2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences (UX) across common frontend workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented API system. From backend and frontend software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the re-use and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large-language models (LLMs) to automatically generate and surface source-level human-readable summaries. With the imminent re-start of the next-generation of gravitational wave detectors, SkyPortal now also includes dedicated multi-messenger features addressing the requirements of rapid multi-messenger follow-up: multi-telescope management, team/group organizing interfaces, and cross-matching of multi-messenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for the newcomers to the field. (abridged), Comment: Accepted to ApJS

We report on our study of supernova (SN) 2022xxf based on observations obtained during the first four months of its evolution. The light curves (LCs) display two humps of similar maximum brightness separated by 75 days, unprecedented for a broad-lined (BL) Type Ic supernova (SN IcBL). SN 2022xxf is the most nearby SN IcBL to date (in NGC 3705, $z = 0.0037$, at a distance of about 20 Mpc). Optical and near-infrared photometry and spectroscopy are used to identify the energy source powering the LC. Nearly 50 epochs of high signal-to-noise-ratio spectroscopy were obtained within 130 days, comprising an unparalleled dataset for a SN IcBL, and one of the best-sampled SN datasets to date. The global spectral appearance and evolution of SN 2022xxf points to typical SN Ic/IcBL, with broad features (up to $\sim14000$ km s$^{-1}$) and a gradual transition from the photospheric to the nebular phase. However, narrow emission lines (corresponding to $\sim1000-2500$ km s$^{-1}$) are present in the spectra from the time of the second rise, suggesting slower-moving circumstellar material (CSM). These lines are subtle, in comparison to the typical strong narrow lines of CSM-interacting SNe, for example, Type IIn, Ibn, and Icn, but some are readily noticeable at late times such as in Mg I $\lambda$5170 and [O I] $\lambda$5577. Unusually, the near-infrared spectra show narrow line peaks in a number of features formed by ions of O and Mg. We infer the presence of CSM that is free of H and He. We propose that the radiative energy from the ejecta-CSM interaction is a plausible explanation for the second LC hump. This interaction scenario is supported by the color evolution, which progresses to the blue as the light curve evolves along the second hump, and the slow second rise and subsequent rapid LC drop. (Abstract abridged), Comment: Accepted version

We conduct a systematic tidal disruption event (TDE) demographics analysis using the largest sample of optically selected TDEs. A flux-limited, spectroscopically complete sample of 33 TDEs is constructed using the Zwicky Transient Facility over three years (from October 2018 to September 2021). We infer the black hole (BH) mass ($M_{\rm BH}$) with host galaxy scaling relations, showing that the sample $M_{\rm BH}$ ranges from $10^{5.1}\,M_\odot$ to $10^{8.2}\,M_\odot$. We developed a survey efficiency corrected maximum volume method to infer the rates. The rest-frame $g$-band luminosity function (LF) can be well described by a broken power-law of $\phi (L_g)\propto [(L_g / L_{\rm bk})^{0.3} + (L_g / L_{\rm bk})^{2.6}]^{-1}$, with $L_{\rm bk}=10^{43.1}\,{\rm erg\,s^{-1}}$. In the BH mass regime of $10^{5.3}\lesssim (M_{\rm BH}/M_\odot) \lesssim 10^{7.3}$, the TDE mass function follows $\phi(M_{\rm BH})\propto M_{\rm BH}^{-0.25}$, which favors a flat local BH mass function ($dn_{\rm BH}/d{\rm log}M_{\rm BH}\approx{\rm constant}$). We confirm the significant rate suppression at the high-mass end ($M_{\rm BH}\gtrsim 10^{7.5}\,M_\odot$), which is consistent with theoretical predictions considering direct capture of hydrogen-burning stars by the event horizon. At a host galaxy mass of $M_{\rm gal}\sim 10^{10}\,M_\odot$, the average optical TDE rate is $\approx 3.2\times 10^{-5}\,{\rm galaxy^{-1}\,yr^{-1}}$. We constrain the optical TDE rate to be [3.7, 7.4, and 1.6$]\times 10^{-5}\,{\rm galaxy^{-1}\,yr^{-1}}$ in galaxies with red, green, and blue colors., Comment: Replaced following peer-review process. 38 pages, 23 figures. Accepted for publication in ApJL

Creating a taxonomy of interests is expensive and human-effort intensive: not only do we need to identify nodes and interconnect them, in order to use the taxonomy, we must also connect the nodes to relevant entities such as users, pins, and queries. Connecting to entities is challenging because of ambiguities inherent to language but also because individual interests are dynamic and evolve. Here, we offer an alternative approach that begins with bottom-up discovery of $\mu$-topics called pincepts. The discovery process itself connects these $\mu$-topics dynamically with relevant queries, pins, and users at high precision, automatically adapting to shifting interests. Pincepts cover all areas of user interest and automatically adjust to the specificity of user interests and are thus suitable for the creation of various kinds of taxonomies. Human experts associate taxonomy nodes with $\mu$-topics (on average, 3 $\mu$-topics per node), and the $\mu$-topics offer a high-level data layer that allows quick definition, immediate inspection, and easy modification. Even more powerfully, $\mu$-topics allow easy exploration of nearby semantic space, enabling curators to spot and fill gaps. Curators' domain knowledge is heavily leveraged and we thus don't need untrained mechanical Turks, allowing further cost reduction. These $\mu$-topics thus offer a satisfactory "symbolic" stratum over which to define taxonomies. We have successfully applied this technique for very rapidly iterating on and launching the home decor and fashion styles taxonomy for style-based personalization, prominently featured at the top of Pinterest search results, at 94% precision, improving search success rate by 34.8% as well as boosting long clicks and pin saves.

We provide a brief, and inevitably incomplete overview of the use of Machine Learning (ML) and other AI methods in astronomy, astrophysics, and cosmology. Astronomy entered the big data era with the first digital sky surveys in the early 1990s and the resulting Terascale data sets, which required automating of many data processing and analysis tasks, for example the star-galaxy separation, with billions of feature vectors in hundreds of dimensions. The exponential data growth continued, with the rise of synoptic sky surveys and the Time Domain Astronomy, with the resulting Petascale data streams and the need for a real-time processing, classification, and decision making. A broad variety of classification and clustering methods have been applied for these tasks, and this remains a very active area of research. Over the past decade we have seen an exponential growth of the astronomical literature involving a variety of ML/AI applications of an ever increasing complexity and sophistication. ML and AI are now a standard part of the astronomical toolkit. As the data complexity continues to increase, we anticipate further advances leading towards a collaborative human-AI discovery., Comment: 12 pages, 1 figure, an invited review chapter, to appear in: Artificial Intelligence for Science, eds. A. Choudhary, G. Fox and T. Hey, Singapore: World Scientific, in press (2023)

Tidal disruption events (TDEs) are bursts of electromagnetic energy released when supermassive black holes (SMBHs) at the centers of galaxies violently disrupt a star that passes too close. TDEs provide a new window to study accretion onto SMBHs; in some rare cases, this accretion leads to launching of a relativistic jet, but the necessary conditions are not fully understood. The best studied jetted TDE to date is Swift J1644+57, which was discovered in gamma-rays, but was too obscured by dust to be seen at optical wavelengths. Here we report the optical discovery of AT2022cmc, a rapidly fading source at cosmological distance (redshift z=1.19325) whose unique lightcurve transitioned into a luminous plateau within days. Observations of a bright counterpart at other wavelengths, including X-rays, sub-millimeter, and radio, supports the interpretation of AT2022cmc as a jetted TDE containing a synchrotron "afterglow", likely launched by a SMBH with spin $a \gtrsim 0.3$. Using 4 years of Zwicky Transient Facility (ZTF) survey data, we calculate a rate of $0.02 ^{+ 0.04 }_{- 0.01 }$ Gpc$^{-3}$ yr$^{-1}$ for on-axis jetted TDEs based on the luminous, fast-fading red component, thus providing a measurement complementary to the rates derived from X-ray and radio observations. Correcting for the beaming angle effects, this rate confirms that about 1% of TDEs have relativistic jets. Optical surveys can use AT2022cmc as a prototype to unveil a population of jetted TDEs., Comment: Accepted for publication in Nature

The accretion disks of active galactic nuclei (AGN) are promising locations for the merger of compact objects detected by gravitational wave (GW) observatories. Embedded within a baryon-rich, high density environment, mergers within AGN are the only GW channel where an electromagnetic (EM) counterpart must occur (whether detectable or not). Considering AGN with unusual flaring activity observed by the Zwicky Transient Facility (ZTF), we describe a search for candidate EM counterparts to binary black hole (BBH) mergers detected by LIGO/Virgo in O3. After removing probable false positives, we find nine candidate counterparts to BBH mergers mergers during O3 (seven in O3a, two in O3b) with a $p$-value of 0.019. Based on ZTF sky coverage, AGN geometry, and merger geometry, we expect $\approx 3(N_{\rm BBH}/83)(f_{\rm AGN}/0.5)$ potentially detectable EM counterparts from O3, where $N_{\rm BBH}$ is the total number of observed BBH mergers and $f_{\rm AGN}$ is the fraction originating in AGN. Further modeling of breakout and flaring phenomena in AGN disks is required to reduce our false positive rate. Two of the events are also associated with mergers with total masses $> 100M_\odot$, which is the expected rate for O3 if hierarchical (large mass) mergers occur in the AGN channel. Candidate EM counterparts in future GW observing runs can be better constrained by coverage of the Southern sky as well as spectral monitoring of unusual AGN flaring events in LIGO/Virgo alert volumes. A future set of reliable AGN EM counterparts to BBH mergers will yield an independent means of measuring cosmic expansion ($H_0$) as a function of redshift., Comment: 24 pages, 6 figures, submitted to ApJ

With a rapidly rising number of transients detected in astronomy, classification methods based on machine learning are increasingly being employed. Their goals are typically to obtain a definitive classification of transients, and for good performance they usually require the presence of a large set of observations. However, well-designed, targeted models can reach their classification goals with fewer computing resources. This paper presents SNGuess, a model designed to find young extragalactic nearby transients with high purity. SNGuess works with a set of features that can be efficiently calculated from astronomical alert data. Some of these features are static and associated with the alert metadata, while others must be calculated from the photometric observations contained in the alert. Most of the features are simple enough to be obtained or to be calculated already at the early stages in the lifetime of a transient after its detection. We calculate these features for a set of labeled public alert data obtained over a time span of 15 months from the Zwicky Transient Facility (ZTF). The core model of SNGuess consists of an ensemble of decision trees, which are trained via gradient boosting. Approximately 88% of the candidates suggested by SNGuess from a set of alerts from ZTF spanning from April 2020 to August 2021 were found to be true relevant supernovae (SNe). For alerts with bright detections, this number ranges between 92% and 98%. Since April 2020, transients identified by SNGuess as potential young SNe in the ZTF alert stream are being published to the Transient Name Server (TNS) under the AMPEL_ZTF_NEW group identifier. SNGuess scores for any transient observed by ZTF can be accessed via a web service. The source code of SNGuess is publicly available., Comment: 14 pages, 10 figures, Astronomy & Astrophysics (A&A), Forthcoming article, source code https://github.com/nmiranda/SNGuess

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science., Comment: White paper from "From Data to Software to Science with the Rubin Observatory LSST" workshop

We present a sample of 14 hydrogen-rich superluminous supernovae (SLSNe II) from the Zwicky Transient Facility (ZTF) between 2018 and 2020. We include all classified SLSNe with peaks $M_{g}<-20$ mag and with observed \emph{broad} but not narrow Balmer emission, corresponding to roughly 20 per cent of all hydrogen-rich SLSNe in ZTF phase I. We examine the light curves and spectra of SLSNe II and attempt to constrain their power source using light-curve models. The brightest events are photometrically and spectroscopically similar to the prototypical SN 2008es, while others are found spectroscopically more reminiscent of non-superluminous SNe II, especially SNe II-L. $^{56}$Ni decay as the primary power source is ruled out. Light-curve models generally cannot distinguish between circumstellar interaction (CSI) and a magnetar central engine, but an excess of ultraviolet (UV) emission signifying CSI is seen in most of the SNe with UV data, at a wide range of photometric properties. Simultaneously, the broad H$\alpha$ profiles of the brightest SLSNe II can be explained through electron scattering in a symmetric circumstellar medium (CSM). In other SLSNe II without narrow lines, the CSM may be confined and wholly overrun by the ejecta. CSI, possibly involving mass lost in recent eruptions, is implied to be the dominant power source in most SLSNe II, and the diversity in properties is likely the result of different mass loss histories. Based on their radiated energy, an additional power source may be required for the brightest SLSNe II, however -- possibly a central engine combined with CSI., Comment: 27 pages including appendices; 14 figures. Revised version, resubmitted to MNRAS after the referee's comments