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The rise of time-domain astronomy including electromagnetic counterparts to gravitational waves, gravitational microlensing, explosive phenomena, and even astrometry with Gaia, are showing the power and need for surveys with high-cadence, large area, and long time baselines to study the transient universe. A constellation of SmallSats or CubeSats providing wide, instantaneous sky coverage down to 21 Vega mag at optical wavelengths would be ideal for addressing this need. We are assembling CuRIOS-ED (CubeSats for Rapid Infrared and Optical Survey--Exploration Demo), an optical telescope payload which will act as a technology demonstrator for a larger constellation of several hundred 16U CubeSats known as CuRIOS. In preparation for CuRIOS, CuRIOS-ED will launch in late 2025 as part of the 12U Starspec InspireSat MVP payload. CuRIOS-ED will be used to demonstrate the StarSpec ADCS pointing capabilities to <1" and to space-qualify a commercial camera package for use on the full CuRIOS payload. The CuRIOS-ED camera system will utilize a Sony IMX455 CMOS detector delivered in an off-the-shelf Atik apx60 package which we modified to be compatible with operations in vacuum as well as the CubeSat form factor, power, and thermal constraints. By qualifying this commercial camera solution, the cost of each CuRIOS satellite will be greatly decreased (~100x) when compared with current space-qualified cameras with IMX455 detectors. We discuss the CuRIOS-ED mission design with an emphasis on the disassembly, repackaging, and testing of the Atik apx60 for space-based missions. Characterization of the apx60's read noise, dark current, patterned noise, and thermal behavior are reported for a range of temperatures (-35 C to 40 C) and exposure times (0.001s to 30 s). Additionally, we comment on preliminary environmental testing results from a successful thermal vacuum test., Comment: 17 pages, 10 figures, 1 table

Terrestrial planets born beyond 1-3 AU have been theorized to avoid being engulfed during the red-giant phases of their host stars. Nevertheless, only a few gas-giant planets have been observed around white dwarfs (WDs) -- the end product left behind by a red giant. Here we report on evidence that the lens system that produced the microlensing event KMT-2020-BLG-0414 is composed of a WD orbited by an Earth-mass planet and a brown dwarf (BD) companion, as shown by the non-detection of the lens flux using Keck Adaptive Optics (AO). From microlensing orbital motion constraints, we determine the planet to be a $1.9\pm0.2$ Earth-mass ($M_\oplus$) planet at a physical separation of $2.1\pm0.2$ au from the WD during the event. By considering the system evolutionary history, we determine the BD companion to have a projected separation of 22 au from the WD, and reject an alternative model that places the BD at 0.2 au. Given planetary orbital expansion during the final evolutionary stages of the host star, this Earth-mass planet may have existed in an initial orbit close to 1 au, thereby offering a glimpse into the possible survival of planet Earth in the distant future., Comment: Accepted. 25 pages, 7 figures, 4 tables

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

Even at modest amplification, the optical depth to gravitational lensing through the Galaxy is $<10^{-5}$. However, the large apparent isotropic-equivalent energy of GRB 221009A coupled with a path through low Galactic latitude suggests that the conditional probability that this particular GRB was lensed is greater than the very low a priori expectation. With the extreme brightness of the prompt emission, this Galactic lensing hypothesis can be constrained by autocorrelation analysis of Fermi photons on 0.1-1000 ms timescales. In relating lensing mass, magnification, and autocorrelation timescale, I show that a lensed-induced autocorrelation signature by stellar lenses falls below the minimal variability timescale (MVT) expected from a black hole central engine. However, lensing by Galactic dark matter MACHOs ($M_l > 10-1000\,M_\odot$) could be confirmed with this approach. Regardless, at a peak $\gamma$-ray photon rate of $>30$ ms$^{-1}$, GRB 221009A represents a prime opportunity to measure the smallest MVTs of GRBs., Comment: 4 pages, 1 figure. Published October 2022 in Research Notes of the AAS, Volume 6, Number 10

Modern surveys often deliver hundreds of thousands of stellar spectra at once, which are fit to spectral models to derive stellar parameters/labels. Therefore, the technique of Amortized Neural Posterior Estimation (ANPE) stands out as a suitable approach, which enables the inference of large number of targets as sub-linear/constant computational costs. Leveraging our new nbi software package, we train an ANPE model for the APOGEE survey and demonstrate its efficacy on both mock and real APOGEE stellar spectra. Unique to the nbi package is its out-of-the-box functionality on astronomical inverse problems with sequential data. As such, we have been able to acquire the trained model with minimal effort. We introduce an effective approach to handling the measurement noise properties inherent in spectral data, which utilizes the actual uncertainties in the observed data. This allows training data to resemble observed data, an aspect that is crucial for ANPE applications. Given the association of spectral data properties with the observing instrument, we discuss the utility of an ANPE "model zoo," where models are trained for specific instruments and distributed under the nbi framework to facilitate real-time stellar parameter inference., Comment: Accepted to ICML 2023 Workshop on Machine Learning for Astrophysics. 7 pages 3 figures

Despite the promise of Neural Posterior Estimation (NPE) methods in astronomy, the adaptation of NPE into the routine inference workflow has been slow. We identify three critical issues: the need for custom featurizer networks tailored to the observed data, the inference inexactness, and the under-specification of physical forward models. To address the first two issues, we introduce a new framework and open-source software nbi (Neural Bayesian Inference), which supports both amortized and sequential NPE. First, nbi provides built-in "featurizer" networks with demonstrated efficacy on sequential data, such as light curve and spectra, thus obviating the need for this customization on the user end. Second, we introduce a modified algorithm SNPE-IS, which facilities asymptotically exact inference by using the surrogate posterior under NPE only as a proposal distribution for importance sampling. These features allow nbi to be applied off-the-shelf to astronomical inference problems involving light curves and spectra. We discuss how nbi may serve as an effective alternative to existing methods such as Nested Sampling. Our package is at https://github.com/kmzzhang/nbi., Comment: Update references. Accepted to NeurIPS 2023 Workshop on Deep Learning and Inverse Problems. Initially appeared at ICML 2023 Workshop on Machine Learning for Astrophysics. Code at https://github.com/kmzzhang/nbi

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

Binaries containing compact objects, if viewed close to edge on, can produce periodic brightening events under certain conditions on the masses, radii, and binary separation. Such flares are caused by one object gravitational lensing the other, in what is known as self-lensing flares. We present a simulation tool that efficiently reproduces the main features of self-lensing flares and facilitates a detection sensitivity analysis for various sky surveys. We estimate the detection prospects for a handful of representative surveys when searching for systems of either two white dwarfs, or a white dwarf with other compact objects, i.e., neutron stars and black holes. We find only a marginal ability to detect such systems in existing surveys. However, we estimate many such systems could be detectable by surveys in the near future, including the Vera Rubin observatory. We provide a quantitative analysis of the detectability of double-compact object self-lensing flares across the landscape of system parameters, and a qualitative discussion of survey and followup approaches to distinguish such flares from confounding events, such as stellar flares, satellite glints, and cosmic rays. We estimate 0.3, 3 and 247 double white dwarf systems could be detected by TESS, ZTF, and LSST, respectively. A similar number of systems with a neutron star or black hole companion could be detected, but we caution that the number densities of such binaries is model dependent and so our detection estimates. Such binaries can be used to constrain models of the end states of binary evolution.

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

We present analytical and numerical models of the bright long GRB 210822A at $z=1.736$. The intrinsic extreme brightness exhibited in the optical, which is very similar to other bright GRBs (e.g., GRBs 080319B, 130427A, 160625A 190114C, and 221009A), makes GRB 210822A an ideal case for studying the evolution of this particular kind of GRB. We use optical data from the RATIR instrument starting at $T+315.9$ s, with publicly available optical data from other ground-based observatories, as well as Swift/UVOT, and X-ray data from the Swift/XRT instrument. The temporal profiles and spectral properties during the late stages align consistently with the conventional forward shock model, complemented by a reverse shock element that dominates optical emissions during the initial phases ($T<300$ s). Furthermore, we observe a break at $T=80000$s that we interpreted as evidence of a jet break, which constrains the opening angle to be about $\theta_\mathrm{j}=(3-5)$ degrees. Finally, we apply a machine-learning technique to model the multi-wavelength light curve of GRB 210822A using the AFTERGLOWPY library. We estimate the angle of sight $\theta_{obs}=(6.4 \pm 0.1) \times 10^{-1}$ degrees, the energy $E_0=(7.9 \pm 1.6)\times 10^{53}$ ergs, the electron index $p=2.54 \pm 0.10$, the thermal energy fraction in electrons $\epsilon_\mathrm{e}=(4.63 \pm 0.91) \times 10^{-5}$ and in the magnetic field $\epsilon_\mathrm{B}= (8.66 \pm 1.01) \times 10^{-6}$, the efficiency $\chi = 0.89 \pm 0.01$, and the density of the surrounding medium $n_\mathrm{0} = 0.85 \pm 0.01 cm^{-3}$., Comment: Resubmitted to MNRAS after moderate revision, 12 pages, 6 figures

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 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

One of the open questions following the discovery of GW170817 is whether neutron star mergers are the only astrophysical sites capable of producing $r$-process elements. Simulations have shown that 0.01-0.1M$_\odot$ of $r$-process material could be generated in the outflows originating from the accretion disk surrounding the rapidly rotating black hole that forms as a remnant to both neutron star mergers and collapsing massive stars associated with long-duration gamma-ray bursts (collapsars). The hallmark signature of $r$-process nucleosynthesis in the binary neutron star merger GW170817 was its long-lasting near-infrared emission, thus motivating a systematic photometric study of the light curves of broadlined stripped-envelope (Ic-BL) supernovae (SNe) associated with collapsars. We present the first systematic study of 25 SNe Ic-BL -- including 18 observed with the Zwicky Transient Facility and 7 from the literature -- in the optical/near-infrared bands to determine what quantity of $r$-process material, if any, is synthesized in these explosions. Using semi-analytic models designed to account for $r$-process production in SNe Ic-BL, we perform light curve fitting to derive constraints on the $r$-process mass for these SNe. We also perform independent light curve fits to models without $r$-process. We find that the $r$-process-free models are a better fit to the light curves of the objects in our sample. Thus we find no compelling evidence of $r$-process enrichment in any of our objects. Further high-cadence infrared photometric studies and nebular spectroscopic analysis would be sensitive to smaller quantities of $r$-process ejecta mass or indicate whether all collapsars are completely devoid of $r$-process nucleosynthesis., Comment: 37 pages, 8 figures, 4 tables

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

Type Ia supernovae (SNe Ia) are thermonuclear explosions of degenerate white dwarf (WD) stars destabilized by mass accretion from a companion star, but the nature of their progenitors remains poorly understood. A way to discriminate between progenitor systems is through radio observations; a non-degenerate companion star is expected to lose material through winds or binary interaction prior to explosion, and the SN ejecta crashing into this nearby circumstellar material (CSM) should result in radio synchrotron emission. However, despite extensive efforts, no SN Ia has ever been detected at radio wavelengths, which suggests a clean environment and a companion star that is itself a degenerate WD star. Here we report on the study of SN 2020eyj, a SN Ia showing helium-rich CSM, as revealed by its spectral features, infrared emission and, for the first time in a SN Ia, a radio counterpart. Based on our modeling, we conclude the CSM likely originates from a single-degenerate (SD) binary system where a WD accretes material from a helium donor star, an often hypothesized formation channel for SNe Ia. We describe how comprehensive radio follow-up of SN 2020eyj-like SNe Ia can improve the constraints on their progenitor systems., Comment: 62 pages, 10 figures, 4 tables

We present the discovery and analysis of SN\,2022oqm, a Type Ic supernova (SN) detected $<1$\,day after explosion. The SN rises to a blue and short-lived (2\,days) initial peak. Early-time spectral observations of SN\,2022oqm show a hot (40,000\,K) continuum with high-ionization C and O absorption features at velocities of 4000\,km\,s$^{-1}$, while its photospheric radius expands at 20,000\,\kms, indicating a pre-existing distribution of expanding C/O material. After $\sim2.5$\,days, both the spectrum and light curves evolve into those of a typical SN Ic, with line velocities of $\sim10,000$\,km\,s$^{-1}$, in agreement with the photospheric radius evolution. The optical light curves reach a second peak at $t\approx15$\,days. By $t=60$\,days, the spectrum of \oqm\ becomes nearly nebular, displaying strong \ion{Ca}{2} and [\ion{Ca}{2}] emission with no detectable [\ion{O}{1}], marking this event as Ca-rich. The early behavior can be explained by $10^{-3}$\,\msun\ of optically thin circumstellar material (CSM) surrounding either (1) a massive compact progenitor such as a Wolf-Rayet star, (2) a massive stripped progenitor with an extended envelope, or (3) a binary system with a white dwarf. We propose that the early-time light curve is powered by both interaction of the ejecta with the optically thin CSM and shock cooling (in the massive-star scenario). The observations can be explained by CSM that is optically thick to X-ray photons, is optically thick in the lines as seen in the spectra, and is optically thin to visible-light continuum photons that come either from downscattered X-rays or from the shock-heated ejecta. Calculations show that this scenario is self-consistent., Comment: 36 pages, 23 figures. Comments are welcome ido.irani@weizmann.ac.il or idoirani@gmail.com. Accepted to ApJ

We present X-ray, UV, optical, and radio observations of the nearby ($\approx78$ Mpc) tidal disruption event (TDE) AT2021ehb/ZTF21aanxhjv during its first 430 days of evolution. AT2021ehb occurs in the nucleus of a galaxy hosting a $\approx 10^{7}\,M_\odot$ black hole ($M_{\rm BH}$ inferred from host galaxy scaling relations). High-cadence Swift and NICER monitoring reveals a delayed X-ray brightening. The spectrum first undergoes a gradual ${\rm soft }\rightarrow{\rm hard}$ transition and then suddenly turns soft again within 3 days at $\delta t\approx 272$ days during which the X-ray flux drops by a factor of ten. In the joint NICER+NuSTAR observation ($\delta t =264$ days, harder state), we observe a prominent non-thermal component up to 30 keV and an extremely broad emission line in the iron K band. The bolometric luminosity of AT2021ehb reaches a maximum of $6.0^{+10.4}_{-3.8}\% L_{\rm Edd}$ when the X-ray spectrum is the hardest. During the dramatic X-ray evolution, no radio emission is detected, the UV/optical luminosity stays relatively constant, and the optical spectra are featureless. We propose the following interpretations: (i) the ${\rm soft }\rightarrow{\rm hard}$ transition may be caused by the gradual formation of a magnetically dominated corona; (ii) hard X-ray photons escape from the system along solid angles with low scattering optical depth ($\sim\,$a few) whereas the UV/optical emission is likely generated by reprocessing materials with much larger column density -- the system is highly aspherical; (iii) the abrupt X-ray flux drop may be triggered by the thermal-viscous instability in the inner accretion flow leading to a much thinner disk., Comment: 35 pages, 21 figures, accepted by ApJ

The Zwicky Transient Facility (ZTF) performs a systematic neutrino follow-up program, searching for optical counterparts to high-energy neutrinos with dedicated Target-of-Opportunity (ToO) observations. Since first light in March 2018, ZTF has taken prompt observations for 24 high-quality neutrino alerts from the IceCube Neutrino Observatory, with a median latency of 12.2 hours from initial neutrino detection. From two of these campaigns, we have already reported tidal disruption event (TDE) AT 2019dsg and likely TDE AT 2019fdr as probable counterparts, suggesting that TDEs contribute >7.8% of the astrophysical neutrino flux. We here present the full results of our program through to December 2021. No additional candidate neutrino sources were identified by our program, allowing us to place the first constraints on the underlying optical luminosity function of astrophysical neutrino sources. Transients with optical absolutes magnitudes brighter that $-21$ can contribute no more than 87% of the total, while transients brighter than $-22$ can contribute no more than 58% of the total, neglecting the effect of extinction and assuming they follow the star formation rate. These are the first observational constraints on the neutrino emission of bright populations such as superluminous supernovae. None of the neutrinos were coincident with bright optical AGN flares comparable to that observed for TXS 0506+056/IC170922A, with such optical blazar flares producing no more than 26% of the total neutrino flux. We highlight the outlook for electromagnetic neutrino follow-up programs, including the expected potential for the Rubin Observatory.

The Fermi Gamma-ray Burst Monitor (GBM) triggers on-board in response to $\sim$ 40 short gamma-ray bursts (SGRBs) per year; however, their large localization regions have made the search for optical counterparts a challenging endeavour. We have developed and executed an extensive program with the wide field of view of the Zwicky Transient Facility (ZTF) camera, mounted on the Palomar 48 inch Oschin telescope (P48), to perform target-of-opportunity (ToO) observations on 10 Fermi-GBM SGRBs during 2018 and 2020-2021. Bridging the large sky areas with small field of view optical telescopes in order to track the evolution of potential candidates, we look for the elusive SGRB afterglows and kilonovae (KNe) associated with these high-energy events. No counterpart has yet been found, even though more than 10 ground based telescopes, part of the Global Relay of Observatories Watching Transients Happen (GROWTH) network, have taken part in these efforts. The candidate selection procedure and the follow-up strategy have shown that ZTF is an efficient instrument for searching for poorly localized SGRBs, retrieving a reasonable number of candidates to follow-up and showing promising capabilities as the community approaches the multi-messenger era. Based on the median limiting magnitude of ZTF, our searches would have been able to retrieve a GW170817-like event up to $\sim$ 200 Mpc and SGRB afterglows to z = 0.16 or 0.4, depending on the assumed underlying energy model. Future ToOs will expand the horizon to z = 0.2 and 0.7 respectively.

Dirty fireballs are a hypothesized class of relativistic massive-star explosions with an initial Lorentz factor $\Gamma_\mathrm{init}$ below the $\Gamma_\mathrm{init}\sim100$ required to produce a long-duration gamma-ray burst (LGRB), but which could still produce optical emission resembling LGRB afterglows. Here we present the results of a search for on-axis optical afterglows using the Zwicky Transient Facility (ZTF). Our search yielded seven optical transients that resemble on-axis LGRB afterglows in terms of their red colors ($g-r>0$ mag), faint host galaxy ($r>23$ mag), and rapid fading ($dr/dt>1$ mag/day). Spectroscopy of the transient emission within a few days of discovery established cosmological distances ($z=0.876$ to $z=2.9$) for six events, tripling the number of afterglows with redshift measurements discovered by optical surveys without a $\gamma$-ray trigger. Upon a retrospective search, four events (ZTF20abbiixp/AT2020kym, ZTF21aagwbjr/AT2021buv, ZTF21aakruew/AT2021cwd, ZTF21abfmpwn/AT2021qbd) turned out to have a likely associated LGRB (GRB200524A, GRB210204A, GRB210212B, GRB210610B), while three did not (ZTF20aajnksq/AT2020blt, ZTF21aaeyldq/AT2021any, ZTF21aayokph/AT2021lfa). Our search revealed no definitive new class of events: the simplest explanation for the apparently "orphan" events is that they were regular LGRBs missed by high-energy satellites due to detector sensitivity and duty cycle, although it is possible that they were intrinsically faint in $\gamma$-rays or viewed slightly off-axis. We rule out a scenario in which dirty fireballs have a similar energy per solid angle to LGRBs and are an order of magnitude more common. In addition, we set the first direct constraint on the ratio of the opening angles of the material producing $\gamma$-rays and the material producing early optical afterglow emission, finding that they must be comparable., Comment: 37 pages, 12 figures. Accepted for publication in ApJ

Efficient searches for electromagnetic counterparts to gravitational wave, high-energy neutrino, and gamma-ray burst events demand rapid processing of image arithmetic and geometry set operations in a database to cross-match galaxy catalogs, observation footprints, and all-sky images. Here we introduce HEALPix Alchemy, an open-source, pure Python implementation of a set of methods that enables rapid all-sky geometry calculations. HEALPix Alchemy is built upon HEALPix, a spatial indexing strategy that is widely used in astronomical databases as well as the native format of LIGO-Virgo-KAGRA gravitational-wave sky localization maps. Our approach leverages new multirange types built into the PostgreSQL 14 database engine. This enables fast all-sky queries against probabilistic multimessenger event localizations and telescope survey footprints. Questions such as "What are the galaxies contained within the 90% credible region of an event?" and "What is the rank-ordered list of the fields within an observing footprint with the highest probability of containing the event?" can be performed in less than a few seconds on commodity hardware using off-the-shelf cloud-managed database implementations without server-side database extensions. Common queries scale roughly linearly with the number of telescope pointings. As the number of fields grows into the hundreds or thousands, HEALPix Alchemy is orders of magnitude faster than other implementations. HEALPix Alchemy is now used as the spatial geometry engine within SkyPortal, which forms the basis of the Zwicky Transient Facility transient marshal, called Fritz., Comment: For source code, see https://github.com/skyportal/healpix-alchemy

UVEX is a proposed medium class Explorer mission designed to provide crucial missing capabilities that will address objectives central to a broad range of modern astrophysics. The UVEX design has two co-aligned wide-field imagers operating in the FUV and NUV and a powerful broadband medium resolution spectrometer. In its two-year baseline mission, UVEX will perform a multi-cadence synoptic all-sky survey 50/100 times deeper than GALEX in the NUV/FUV, cadenced surveys of the Large and Small Magellanic Clouds, rapid target of opportunity followup, as well as spectroscopic followup of samples of stars and galaxies. The science program is built around three pillars. First, UVEX will explore the low-mass, low-metallicity galaxy frontier through imaging and spectroscopic surveys that will probe key aspects of the evolution of galaxies by understanding how star formation and stellar evolution at low metallicities affect the growth and evolution of low-metallicity, low-mass galaxies in the local universe. Such galaxies contain half the mass in the local universe, and are analogs for the first galaxies, but observed at distances that make them accessible to detailed study. Second, UVEX will explore the dynamic universe through time-domain surveys and prompt spectroscopic followup capability will probe the environments, energetics, and emission processes in the early aftermaths of gravitational wave-discovered compact object mergers, discover hot, fast UV transients, and diagnose the early stages of stellar explosions. Finally, UVEX will become a key community resource by leaving a large all-sky legacy data set, enabling a wide range of scientific studies and filling a gap in the new generation of wide-field, sensitive optical and infrared surveys provided by the Rubin, Euclid, and Roman observatories. This paper discusses the scientific potential of UVEX, and the broad scientific program., Comment: 69 pages, 43 figures

While gravitational microlensing by planetary systems provides unique vistas on the properties of exoplanets, observations of a given 2-body microlensing event can often be interpreted with multiple distinct physical configurations. Such ambiguities are typically attributed to the close-wide and inner-outer types of degeneracies that arise from transformation invariances and symmetries of microlensing caustics. However, there remain unexplained inconsistencies between aforementioned theories and observations. Here, leveraging a fast machine learning inference framework, we present the discovery of the offset degeneracy, which concerns a magnification-matching behaviour on the lens-axis and is formulated independent of caustics. This offset degeneracy unifies the close-wide and inner-outer degeneracies, generalises to resonant topologies, and upon reanalysis, not only appears ubiquitous in previously published planetary events with 2-fold degenerate solutions, but also resolves prior inconsistencies. Our analysis demonstrates that degenerate caustics do not strictly result in degenerate magnifications and that the commonly invoked close-wide degeneracy essentially never arises in actual events. Moreover, it is shown that parameters in offset degenerate configurations are related by a simple expression. This suggests the existence of a deeper symmetry in the equations governing 2-body lenses than previously recognised., Comment: 21 pages, 8 figures, submitted

The discovery of the electromagnetic counterpart to the binary neutron star merger GW170817 has opened the era of gravitational-wave multi-messenger astronomy. Rapid identification of the optical/infrared kilonova enabled a precise localization of the source, which paved the way to deep multi-wavelength follow-up and its myriad of related science results. Fully exploiting this new territory of exploration requires the acquisition of electromagnetic data from samples of neutron star mergers and other gravitational wave sources. After GW170817, the frontier is now to map the diversity of kilonova properties and provide more stringent constraints on the Hubble constant, and enable new tests of fundamental physics. The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) can play a key role in this field in the 2020s, when an improved network of gravitational-wave detectors is expected to reach a sensitivity that will enable the discovery of a high rate of merger events involving neutron stars (about tens per year) out to distances of several hundred Mpc. We design comprehensive target-of-opportunity observing strategies for follow-up of gravitational-wave triggers that will make the Rubin Observatory the premier instrument for discovery and early characterization of neutron star and other compact object mergers, and yet unknown classes of gravitational wave events., Comment: Accepted for publication in ApJS. arXiv admin note: text overlap with arXiv:1812.04051

We present optical follow-up imaging obtained with the Katzman Automatic Imaging Telescope, Las Cumbres Observatory Global Telescope Network, Nickel Telescope, Swope Telescope, and Thacher Telescope of the LIGO/Virgo gravitational wave (GW) signal from the neutron star-black hole (NSBH) merger GW190814. We searched the GW190814 localization region (19 deg$^{2}$ for the 90th percentile best localization), covering a total of 51 deg$^{2}$ and 94.6% of the two-dimensional localization region. Analyzing the properties of 189 transients that we consider as candidate counterparts to the NSBH merger, including their localizations, discovery times from merger, optical spectra, likely host-galaxy redshifts, and photometric evolution, we conclude that none of these objects are likely to be associated with GW190814. Based on this finding, we consider the likely optical properties of an electromagnetic counterpart to GW190814, including possible kilonovae and short gamma-ray burst afterglows. Using the joint limits from our follow-up imaging, we conclude that a counterpart with an $r$-band decline rate of 0.68 mag day$^{-1}$, similar to the kilonova AT 2017gfo, could peak at an absolute magnitude of at most $-17.8$ mag (50% confidence). Our data are not constraining for ''red'' kilonovae and rule out ''blue'' kilonovae with $M>0.5 M_{\odot}$ (30% confidence). We strongly rule out all known types of short gamma-ray burst afterglows with viewing angles $<$17$^{\circ}$ assuming an initial jet opening angle of $\sim$$5.2^{\circ}$ and explosion energies and circumburst densities similar to afterglows explored in the literature. Finally, we explore the possibility that GW190814 merged in the disk of an active galactic nucleus, of which we find four in the localization region, but we do not find any candidate counterparts among these sources., Comment: 86 pages, 9 figures

Fast and automated inference of binary-lens, single-source (2L1S) microlensing events with sampling-based Bayesian algorithms (e.g., Markov Chain Monte Carlo; MCMC) is challenged on two fronts: high computational cost of likelihood evaluations with microlensing simulation codes, and a pathological parameter space where the negative-log-likelihood surface can contain a multitude of local minima that are narrow and deep. Analysis of 2L1S events usually involves grid searches over some parameters to locate approximate solutions as a prerequisite to posterior sampling, an expensive process that often requires human-in-the-loop domain expertise. As the next-generation, space-based microlensing survey with the Roman Space Telescope is expected to yield thousands of binary microlensing events, a new fast and automated method is desirable. Here, we present a likelihood-free inference (LFI) approach named amortized neural posterior estimation, where a neural density estimator (NDE) learns a surrogate posterior $\hat{p}(\theta|x)$ as an observation-parametrized conditional probability distribution, from pre-computed simulations over the full prior space. Trained on 291,012 simulated Roman-like 2L1S simulations, the NDE produces accurate and precise posteriors within seconds for any observation within the prior support without requiring a domain expert in the loop, thus allowing for real-time and automated inference. We show that the NDE also captures expected posterior degeneracies. The NDE posterior could then be refined into the exact posterior with a downstream MCMC sampler with minimal burn-in steps., Comment: 15 pages, 8 figures, 3 tables. Accepted for publication in the Astronomical Journal. This article supersedes arXiv:2010.04156

Short-period cataclysmic variables (spCVs), with orbital periods below the period gap ($P_{orb}$ < 2 hr), offer insight into the evolutionary models of CVs and can serve as strong emitters of gravitational waves (GWs). To identify new spCV candidates, we crossmatch a catalog of known CVs to sources with robust parallaxes in the Gaia second data release (DR2). We uncover and fit an apparently monotonic relationship between the color--absolute-magnitude diagram (CMD) position and $P_{orb}$ of these CVs, revealed in DR2. To supplement this relation, we develop a method for identifying sources with large photometric variability, a characteristic trait of spCVs. Using all available Gaia light curves, we construct a machine-learned regression model to predict variability metrics for sources in the CMD locus of known spCVs based solely on time-averaged covariates present in DR2. Using this approach we identify 3,253 candidate spCVs, of which $\sim$95% are previously unknown. Inspection of archival SDSS spectra of these candidates suggests that $>$82% are likely to be spCVs: a noticeably higher recovery rate than previous light curve searches, which bias toward active systems. We obtain optical spectra of 9 new systems at Lick Observatory and confirm that all objects are CV systems. We measure $P_{orb}$ for 7 systems using archival Gaia and Palomar Transient Factory light curves, 3 of which do not have previous $P_{orb}$ measurements. We use the CMD-$P_{orb}$ relation to infer the detectability of these systems to the upcoming LISA mission, and find that six sources may be coherent LISA verification binaries, with an estimated SNR > 5 in the 4 yr mission. This paper demonstrates that the time-averaged Gaia catalog is a powerful tool in the methodical discovery and characterization of time-varying objects, making it complementary to missions like ZTF, TESS, and the Vera Rubin LSST., Comment: 35 pages, 24 figures. Submitted to AAS Journals

Neural networks (NNs) have been shown to be competitive against state-of-the-art feature engineering and random forest (RF) classification of periodic variable stars. Although previous work utilising NNs has made use of periodicity by period folding multiple-cycle time-series into a single cycle -- from time-space to phase-space -- no approach to date has taken advantage of the fact that network predictions should be invariant to the initial phase of the period-folded sequence. Initial phase is exogenous to the physical origin of the variability and should thus be factored out. Here, we present cyclic-permutation invariant networks, a novel class of NNs for which invariance to phase shifts is guaranteed through polar coordinate convolutions, which we implement by means of "Symmetry Padding." Across three different datasets of variable star light curves, we show that two implementations of the cyclic-permutation invariant network: the iTCN and the iResNet, consistently outperform non-invariant baselines and reduce overall error rates by between 4% to 22%. Over a 10-class OGLE-III sample, the iTCN/iResNet achieves an average per-class accuracy of 93.4%/93.3%, compared to RNN/RF accuracies of 70.5%/89.5% in a recent study using the same data. Finding improvement on a non-astronomy benchmark, we suggest that the methodology introduced here should also be applicable to a wide range of science domains where periodic data abounds due to physical symmetries., Comment: Accepted to MNRAS. Extended abstract accepted to NeurIPS 2020: Machine Learning for the Physical Sciences. Initially appeared in ICLR 2020: Fundamental Science in the Era of AI. Open source implementation at https://github.com/kmzzhang/periodicnetwork. 8 pages, 4 figures

Automated inference of binary microlensing events with traditional sampling-based algorithms such as MCMC has been hampered by the slowness of the physical forward model and the pathological likelihood surface. Current analysis of such events requires both expert knowledge and large-scale grid searches to locate the approximate solution as a prerequisite to MCMC posterior sampling. As the next generation, space-based microlensing survey with the Roman Space Observatory is expected to yield thousands of binary microlensing events, a new scalable and automated approach is desired. Here, we present an automated inference method based on neural density estimation (NDE). We show that the NDE trained on simulated Roman data not only produces fast, accurate, and precise posteriors but also captures expected posterior degeneracies. A hybrid NDE-MCMC framework can further be applied to produce the exact posterior., Comment: 7 pages, 1 figure. This article is superseded by arXiv:2102.05673. Accepted to the ML4PS workshop at NeurIPS 2020

The transition from prompt to the afterglow emission is one of the most exciting and least understood phases in gamma-ray bursts (GRBs). Correlations among optical, X-ray and gamma-ray emission in GRBs have been explored, to attempt to answer whether the earliest optical emission comes from internal and/or external shocks. We present optical photometric observations of GRB 180325A collected with the TAROT and RATIR ground-based telescopes. These observations show two strong optical flashes with separate peaks at $\sim50\;$s and $\sim120\;$s, followed by a temporally extended optical emission. We also present X-rays and gamma-ray observations of GRB 180325A, detected by the Burst Alert Telescope (BAT) and X-ray Telescope (XRT), on the Neil Gehrels Swift observatory, which both observed a narrow flash at $\sim80\;$s. We show that the prompt gamma- and X-ray early emission shares similar temporal and spectral features consistent with internal dissipation within the relativistic outflow (e.g. by internal shocks or magnetic reconnection), while the early optical flashes are likely generated by the reverse shock that decelerates the ejecta as it sweeps up the external medium., Comment: Accepted for publication in ApJ

Several thousand core-collapse supernovae (CCSNe) of different flavors have been discovered so far. However, identifying their progenitors has remained an outstanding open question in astrophysics. Studies of SN host galaxies have proven to be powerful in providing constraints on the progenitor populations. In this paper, we present all CCSNe detected between 2009 and 2017 by the Palomar Transient Factory. This sample includes 888 SNe of 12 distinct classes out to redshift $z\approx1$. We present the photometric properties of their host galaxies from the far-ultraviolet to the mid-infrared and model the host-galaxy spectral energy distributions to derive physical properties. The galaxy mass functions of Type Ic, Ib, IIb, II, and IIn SNe ranges from $10^{5}$ to $10^{11.5}~M_\odot$, probing the entire mass range of star-forming galaxies down to the least-massive star-forming galaxies known. Moreover, the galaxy mass distributions are consistent with models of star-formation-weighted mass functions. Regular CCSNe are hence direct tracers of star formation. Small but notable differences exist between some of the SN classes. Type Ib/c SNe prefer galaxies with slightly higher masses (i.e., higher metallicities) and star-formation rates than Type IIb and II SNe. These differences are less pronounced than previously thought. H-poor SLSNe and SNe~Ic-BL are scarce in galaxies above $10^{10}~M_\odot$. Their progenitors require environments with metallicities of $<0.4$ and $<1$ solar, respectively. In addition, the hosts of H-poor SLSNe are dominated by a younger stellar population than all other classes of CCSNe. Our findings corroborate the notion that low-metallicity \textit{and} young age play an important role in the formation of SLSN progenitors., Comment: 24 pages main text, 14 figures, 9 Tables, catalogue available at http://www.github.com/steveschulze/PTF

We present a systematic search for optical counterparts to 13 gravitational wave (GW) triggers involving at least one neutron star during LIGO/Virgo's third observing run. We searched binary neutron star (BNS) and neutron star black hole (NSBH) merger localizations with the Zwicky Transient Facility (ZTF) and undertook follow-up with the Global Relay of Observatories Watching Transients Happen (GROWTH) collaboration. The GW triggers had a median localization of 4480 deg^2, median distance of 267 Mpc and false alarm rates ranging from 1.5 to 1e-25 per yr. The ZTF coverage had a median enclosed probability of 39%, median depth of 20.8mag, and median response time of 1.5 hr. The O3 follow-up by the GROWTH team comprised 340 UVOIR photometric points, 64 OIR spectra, and 3 radio. We find no promising kilonova (radioactivity-powered counterpart) and we convert the upper limits to constrain the underlying kilonova luminosity function. Assuming that all kilonovae are at least as luminous as GW170817 at discovery (-16.1mag), we calculate our joint probability of detecting zero kilonovae is only 4.2%. If we assume that all kilonovae are brighter than -16.6mag (extrapolated peak magnitude of GW170817) and fade at 1 mag/day (similar to GW170817), the joint probability of zero detections is 7%. If we separate the NSBH and BNS populations, the joint probability of zero detections, assuming all kilonovae are brighter than -16.6mag, is 9.7% for NSBH and 7.9% for BNS mergers. Moreover, <57% (<89%) of putative kilonovae could be brighter than -16.6mag assuming flat (fading) evolution, at 90% confidence. If we further account for the online terrestrial probability for each GW trigger, we find that <68% of putative kilonovae could be brighter than -16.6mag. Comparing to model grids, we find that some kilonovae must have Mej < 0.03 Msun or Xlan>1e-4 or phi>30deg to be consistent with our limits. (Abridged), Comment: Submitted to ApJ

We present {\tt deepSIP} (deep learning of Supernova Ia Parameters), a software package for measuring the phase and -- for the first time using deep learning -- the light-curve shape of a Type Ia supernova (SN~Ia) from an optical spectrum. At its core, {\tt deepSIP} consists of three convolutional neural networks trained on a substantial fraction of all publicly-available low-redshift SN~Ia optical spectra, onto which we have carefully coupled photometrically-derived quantities. We describe the accumulation of our spectroscopic and photometric datasets, the cuts taken to ensure quality, and our standardised technique for fitting light curves. These considerations yield a compilation of 2754 spectra with photometrically characterised phases and light-curve shapes. Though such a sample is significant in the SN community, it is small by deep-learning standards where networks routinely have millions or even billions of free parameters. We therefore introduce a data-augmentation strategy that meaningfully increases the size of the subset we allocate for training while prioritising model robustness and telescope agnosticism. We demonstrate the effectiveness of our models by deploying them on a sample unseen during training and hyperparameter selection, finding that Model~I identifies spectra that have a phase between $-10$ and 18\,d and light-curve shape, parameterised by $\Delta m_{15}$, between 0.85 and 1.55\,mag with an accuracy of 94.6\%. For those spectra that do fall within the aforementioned region in phase--$\Delta m_{15}$ space, Model~II predicts phases with a root-mean-square error (RMSE) of 1.00\,d and Model~III predicts $\Delta m_{15}$ values with an RMSE of 0.068\,mag., Comment: 20 pages, 11 figures, accepted for publication in MNRAS

The ability to generate physically plausible ensembles of variable sources is critical to the optimization of time-domain survey cadences and the training of classification models on datasets with few to no labels. Traditional data augmentation techniques expand training sets by reenvisioning observed exemplars, seeking to simulate observations of specific training sources under different (exogenous) conditions. Unlike fully theory-driven models, these approaches do not typically allow principled interpolation nor extrapolation. Moreover, the principal drawback of theory-driven models lies in the prohibitive computational cost of simulating source observables from {\it ab initio} parameters. In this work, we propose a computationally tractable machine learning approach to generate realistic light curves of periodic variables capable of integrating physical parameters and variability classes as inputs. Our deep generative model, inspired by the Transparent Latent Space Generative Adversarial Networks (TL-GANs), uses a Variational Autoencoder (VAE) architecture with Temporal Convolutional Network (TCN) layers, trained using the \hbox{OGLE-III} optical light curves and physical characteristics (e.g., effective temperature and absolute magnitude) from Gaia DR2. A test using the temperature-shape relationship of RR\,Lyrae demonstrates the efficacy of our generative "Physics-Enhanced Latent Space VAE" (PELS-VAE) model. Such deep generative models, serving as non-linear non-parametric emulators, present a novel tool for astronomers to create synthetic time series over arbitrary cadences., Comment: 19 pages, 9 figures, 4 tables

Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse datasets has thus far hampered a direct intercomparison of different approaches. Here we perform the first comprehensive study of variants of NN-based learning and inference for astronomical time-series, aiming to provide the community with an overview on relative performance and, hopefully, a set of best-in-class choices for practical implementations. In both supervised and self-supervised contexts, we study the effects of different time-series-compatible layer choices, namely the dilated temporal convolutional neural network (dTCNs), Long-Short Term Memory (LSTM) NNs, Gated Recurrent Units (GRUs) and temporal convolutional NNs (tCNNs). We also study the efficacy and performance of encoder-decoder (i.e., autoencoder) networks compared to direct classification networks, different pathways to include auxiliary (non-time-series) metadata, and different approaches to incorporate multi-passband data (i.e., multiple time-series per source). Performance---applied to a sample of 17,604 variable stars from the MACHO survey across 10 imbalanced classes---is measured in training convergence time, classification accuracy, reconstruction error, and generated latent variables. We find that networks with Recurrent NN (RNNs) generally outperform dTCNs and, in many scenarios, yield to similar accuracy as tCNNs. In learning time and memory requirements, convolution-based layers are more performant. We conclude by discussing the advantages and limitations of deep architectures for variable star classification, with a particular eye towards next-generation surveys such as LSST, WFIRST and ZTF2., Comment: Submitted to ApJS

Synoptic searches for the optical counterpart to a binary neutron star (BNS) or neutron star-black hole (NSBH) merger can pose significant challenges towards the discovery of kilonovae and performing multi-messenger science. In this work, we describe the advantage of a global multi-telescope network towards this end, with a particular focus on the key and complementary role the Dark Energy Camera (DECam) plays in multi-facility follow-up. We describe the Global Relay of Observatories Watching Transients Happen (GROWTH) Target-of-Opportunity (ToO) Marshal, a common web application we built to ingest events, plan observations, search for transient candidates, and retrieve performance summary statistics for all of the telescopes in our network. Our infrastructure enabled us to conduct observations of two events during O3a, S190426c and S190510g. Furthermore, our analysis of deep DECam observations of S190814bv conducted by the DESGW team, and access to a variety of global follow-up facilities allowed us to place meaningful constraints on the parameters of the kilonova and the merging binary. We emphasize the importance of a global telescope network in conjunction with a power telescope like DECam in performing searches for the counterparts to gravitational-wave sources., Comment: 9 pages, 4 figures, submitted to Rev. Mex. A. A. (AstroRob 2019 conference proceedings)

On 2019 August 14, the Advanced LIGO and Virgo interferometers detected the high-significance gravitational wave (GW) signal S190814bv. The GW data indicated that the event resulted from a neutron star--black hole (NSBH) merger, or potentially a low-mass binary black hole merger. Due to the low false alarm rate and the precise localization (23 deg$^2$ at 90\%), S190814bv presented the community with the best opportunity yet to directly observe an optical/near-infrared counterpart to a NSBH merger. To search for potential counterparts, the GROWTH collaboration performed real-time image subtraction on 6 nights of public Dark Energy Camera (DECam) images acquired in the three weeks following the merger, covering $>$98\% of the localization probability. Using a worldwide network of follow-up facilities, we systematically undertook spectroscopy and imaging of optical counterpart candidates. Combining these data with a photometric redshift catalog, we ruled out each candidate as the counterpart to S190814bv and we placed deep, uniform limits on the optical emission associated with S190814bv. For the nearest consistent GW distance, radiative transfer simulations of NSBH mergers constrain the ejecta mass of S190814bv to be $M_\mathrm{ej} < 0.04$~$M_{\odot}$ at polar viewing angles, or $M_\mathrm{ej} < 0.03$~$M_{\odot}$ if the opacity is $\kappa < 2$~cm$^2$g$^{-1}$. Assuming a tidal deformability for the neutron star at the high end of the range compatible with GW170817 results, our limits would constrain the BH spin component aligned with the orbital momentum to be $ \chi < 0.7$ for mass ratios $Q < 6$, with weaker constraints for more compact neutron stars. We publicly release the photometry from this campaign at http://www.astro.caltech.edu/~danny/static/s190814bv., Comment: Accepted to ApJ with no major changes

The early optical emission of gamma-ray bursts gives an opportunity to understand the central engine and first stages of these events. About 30\% of GRBs present flares whose origin is still a subject of discussion. We present optical photometry of GRB 180620A with the COATLI telescope and RATIR instrument. COATLI started to observe from the end of prompt emission at $T+39.3$~s and RATIR from $T+121.4$~s. We supplement the optical data with the X-ray light curve from \emph{Swift}/XRT. %The optical and X-ray light curves show very unusual behavior with features clearly beyond the standard fireball model. We observe an optical flare from $T+110$ to $T+550$~s, with a temporal index decay $\alpha_\mathrm{O,decay}=1.32\pm 0.01$, and a $\Delta t/t=1.63$, which we interpret as the signature of a reverse shock component. After the initial normal decay the light curves show a long plateau from $T+500$ to $T+7800$~s both in X-rays and the optical before decaying again after an achromatic jet break at $T+7800$~s. Fluctuations are seen during the plateau phase in the optical. Adding to the complexity of GRB afterglows, the plateau phase (typically associated with the coasting phase of the jet) is seen in this object after the ``normal'' decay phase (emitted during the deceleration phase of the jet) and the jet break phase occurs directly after the plateau. We suggest that this sequence of events can be explained by a rapid deceleration of the jet with $t_d\lesssim 40$ s due to the high density of the environment ($\approx 100$ cm$^{-3}$) followed by reactivation of the central engine which causes the flare and powers the plateau phase., Comment: 13 pages, 2 figures, 2 tables, submitted to ApJ

The LIGO/Virgo gravitational wave events S190828j and S190828l were detected only 21 minutes apart, from nearby regions of sky, and with the same source classifications (binary black hole mergers). It is therefore natural to speculate that the two signals are actually strongly lensed images of the same merger. However, an estimate of the separation of the (unknown) positions of the two events requires them to be >10 deg apart, much wider than the arcsecond-scale separations that usually arise in extragalactic lensing. The large separation is much more consistent with two independent, unrelated events that occurred close in time by chance. We quantify the overlap between simulated pairs of lensed events, and use frequentist hypothesis testing to reject S190828j/l as a lensed pair at 99.8% confidence., Comment: 8 pages, 4 figures, submitted to ApJL

The third observing run by LVC has brought the discovery of many compact binary coalescences. Following the detection of the first binary neutron star merger in this run (LIGO/Virgo S190425z), we performed a dedicated follow-up campaign with the Zwicky Transient Facility (ZTF) and Palomar Gattini-IR telescopes. The initial skymap of this single-detector gravitational wave (GW) trigger spanned most of the sky observable from Palomar Observatory. Covering 8000 deg$^2$ of the initial skymap over the next two nights, corresponding to 46\% integrated probability, ZTF system achieved a depth of $\approx$\,21 $m_\textrm{AB}$ in $g$- and $r$-bands. Palomar Gattini-IR covered 2200 square degrees in $J$-band to a depth of 15.5\,mag, including 32\% integrated probability based on the initial sky map. The revised skymap issued the following day reduced these numbers to 21\% for the Zwicky Transient Facility and 19\% for Palomar Gattini-IR. We narrowed 338,646 ZTF transient "alerts" over the first two nights of observations to 15 candidate counterparts. Two candidates, ZTF19aarykkb and ZTF19aarzaod, were particularly compelling given that their location, distance, and age were consistent with the GW event, and their early optical lightcurves were photometrically consistent with that of kilonovae. These two candidates were spectroscopically classified as young core-collapse supernovae. The remaining candidates were ruled-out as supernovae. Palomar Gattini-IR did not identify any viable candidates with multiple detections only after merger time. We demonstrate that even with single-detector GW events localized to thousands of square degrees, systematic kilonova discovery is feasible.

Cosmic ray (CR) identification and replacement are critical components of imaging and spectroscopic reduction pipelines involving solid-state detectors. We present deepCR, a deep learning based framework for CR identification and subsequent image inpainting based on the predicted CR mask. To demonstrate the effectiveness of this framework, we train and evaluate models on Hubble Space Telescope ACS/WFC images of sparse extragalactic fields, globular clusters, and resolved galaxies. We demonstrate that at a false positive rate of 0.5%, deepCR achieves close to 100% detection rates in both extragalactic and globular cluster fields, and 91% in resolved galaxy fields, which is a significant improvement over the current state-of-the-art method LACosmic. Compared to a multicore CPU implementation of LACosmic, deepCR CR mask predictions run up to 6.5 times faster on CPU and 90 times faster on a single GPU. For image inpainting, the mean squared errors of deepCR predictions are 20 times lower in globular cluster fields, 5 times lower in resolved galaxy fields, and 2.5 times lower in extragalactic fields, compared to the best performing non-neural technique tested. We present our framework and the trained models as an open-source Python project, with a simple-to-use API. To facilitate reproducibility of the results we also provide a benchmarking codebase., Comment: Accepted for publication in ApJ. 12 pages, 6 figures. An open-source Python package, deepCR, which implements the approach in this paper is at https://github.com/profjsb/deepCR. Figures and benchmarks can be reproduced at https://github.com/kmzzhang/deepCR-paper. Blog post describing this work is at https://medium.com/@kemingzhang/deepcr-2fa610655655

The first two months of the third Advanced LIGO and Virgo observing run (2019 April-May) showed that distant gravitational wave (GW) events can now be readily detected. Three candidate mergers containing neutron stars (NS) were reported in a span of 15 days, all likely located more than 100 Mpc away. However, distant events such as the three new NS mergers are likely to be coarsely localized, which highlights the importance of facilities and scheduling systems that enable deep observations over hundreds to thousands of square degrees to detect the electromagnetic counterparts. On 2019-05-10 02:59:39.292 UT the GW candidate S190510g was discovered and initially classified as a BNS merger with 98% probability. The GW event was localized within an area of 3462 deg2, later refined to 1166 deg2 (90%) at a distance of 227 +- 92 Mpc. We triggered Target of Opportunity observations with the Dark Energy Camera (DECam), a wide-field optical imager mounted at the prime focus of the 4m Blanco Telescope at CTIO in Chile. This Letter describes our DECam observations and our real-time analysis results, focusing in particular on the design and implementation of the observing strategy. Within 24 hours of the merger time, we observed 65% of the total enclosed probability of the final skymap with an observing efficiency of 94%. We identified and publicly announced 13 candidate counterparts. S190510g was re-classified 1.7 days after the merger, after our observations were completed, with a "binary neutron star merger" probability reduced from 98% to 42% in favor of a "terrestrial" classification., Comment: 4 figures, 3 tables, accepted for publication in ApJL