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The distribution of streaming data often changes over time as conditions change, a phenomenon known as concept drift. Only a subset of previous experience, collected in similar conditions, is relevant to learning an accurate classifier for current data. Learning from irrelevant experience describing a different concept can degrade performance. A system learning from streaming data must identify which recent experience is irrelevant when conditions change and which past experience is relevant when concepts reoccur, \textit{e.g.,} when weather events or financial patterns repeat. Existing streaming approaches either do not consider experience to change in relevance over time and thus cannot handle concept drift, or only consider the recency of experience and thus cannot handle recurring concepts, or only sparsely evaluate relevance and thus fail when concept drift is missed. To enable learning in changing conditions, we propose SELeCT, a probabilistic method for continuously evaluating the relevance of past experience. SELeCT maintains a distinct internal state for each concept, representing relevant experience with a unique classifier. We propose a Bayesian algorithm for estimating state relevance, combining the likelihood of drawing recent observations from a given state with a transition pattern prior based on the system's current state.

Cataclysmic variables (CVs) are compact binary systems in which a white dwarf accretes matter from a Roche-lobe-filling companion star. In this study, we searched for new CVs in the Milky Way in the Chandra Source Catalog v2.0, cross-matched with Gaia Data Release 3 (DR3). We identified new CV candidates by combining X-ray and optical data in a color-color diagram called the ``X-ray Main Sequence". We used two different cuts in this diagram to compile pure and optically variable samples of CV candidates. We undertook optical spectroscopic follow-up observations with the Keck and Palomar Observatories to confirm the nature of these sources. We assembled a sample of 25,887 Galactic X-ray sources and found 14 new CV candidates. Seven objects show X-ray and/or optical variability. All sources show X-ray luminosity in the $\rm 10^{29}-10^{32}$ $\rm erg\ s^{-1}$ range, and their X-ray spectra can be approximated by a power-law model with photon indices in the $\rm \Gamma \sim 1-3$ range or an optically thin thermal emission model in the $\rm kT \sim 1-70$ keV range. We spectroscopically confirmed four CVs, discovering two new polars, one low accretion rate polar and a WZ~Sge-like low accretion rate CV. X-ray and optical properties of the other 9 objects suggest that they are also CVs (likely magnetic or dwarf novae), and one other object could be an eclipsing binary, but revealing their true nature requires further observations. These results show that a joint X-ray and optical analysis can be a powerful tool for finding new CVs in large X-ray and optical catalogs. X-ray observations such as those by Chandra are particularly efficient at discovering magnetic and low accretion rate CVs, which could be missed by purely optical surveys., Comment: 20 pages, 15 figures and 8 tables. Accepted for publication in Astronomy & Astrophysics

Direct imaging of exoplanets allows us to measure positions and chemical signatures of exoplanets. Given the limited resources for space observations where the atmosphere is absent, we want to make these measurements from the ground. However, it is difficult from the ground because it requires an adaptive optics system to provide an extremely well corrected wavefront to enable coronographic techniques. Currently only natural guide star AO systems have demonstrated the necessary wavefront correction for direct imaging of exoplanets. However, using a stellar source as the guide star for wavefront sensing limits the number of exoplanet systems we can directly image because it requires a relatively bright V~10 mag star. To increase the number of observable targets, we need to push the limit of natural guide stars to fainter magnitudes with high Strehl ratio correction. We propose to combine laser guide star (LGS) and natural guide star (NGS) wavefront sensing to achieve the high Strehl correction with fainter natural guide stars. We call this approach Hybrid Atmospheric Phase Analysis (HAPA); 'hapa' in Hawaiian means 'half' or 'of mixed ethnic heritage'. The relatively bright LGS is used for higher order correction, whereas the NGS is used for high accuracy lower order correction. We focus on demonstrating this approach using Robo-AO-2 at the UH 2.2m telescope on Maunakea with a UV Rayleigh laser at 355 nm. The laser focuses at 10 km altitude and has an equivalent magnitude of m_U~8. In this report specifically, we present simulated results of HAPA employed at Robo-AO-2, with the LGS system having a single configuration of 16x16 subaperture Shack-Hartmann wavefront sensor and the NGS system having 6 different configurations -- 16x16, 8x8, 5x5, 4x4, 2x2 and 1x1. We also discuss the on-sky experiments we plan to carry out with HAPA at the UH 2.2m telescope., Comment: 11 pages, 4 figures, 8 tables, SPIE Astronomical Telescopes + Instrumentation 2024

More than 3000 spectroscopically confirmed Type Ia supernovae (SNe Ia) are presented in the Zwicky Transient Facility SN Ia Data Release 2 (ZTF DR2). In this paper, we detail the spectral properties of 482 SNe Ia near maximum light, up to a redshift limit of $z$ $\leq$ 0.06. We measure the velocities and pseudo-equivalent widths (pEW) of key spectral features (Si II $\lambda$5972 and Si II $\lambda$6355) and investigate the relation between the properties of the spectral features and the photometric properties from the SALT2 light-curve parameters as a function of spectroscopic sub-class. We discuss the non-negligible impact of host galaxy contamination on SN Ia spectral classifications, as well as investigate the accuracy of spectral template matching of the ZTF DR2 sample. We define a new subclass of underluminous SNe Ia (`04gs-like') that lie spectroscopically between normal SNe Ia and transitional 86G-like SNe Ia (stronger Si II $\lambda$5972 than normal SNe Ia but significantly weaker Ti II features than `86G-like' SNe). We model these `04gs-like' SN Ia spectra using the radiative-transfer spectral synthesis code tardis and show that cooler temperatures alone are unable to explain their spectra; some changes in elemental abundances are also required. However, the broad continuity in spectral properties seen from bright (`91T-like') to faint normal SN Ia, including the transitional and 91bg-like SNe Ia, suggests that variations within a single explosion model may be able to explain their behaviour.

We installed the next-generation automated laser adaptive optics system, Robo-AO-2, on the University of Hawaii 2.2-m telescope on Maunakea in 2023. We engineered Robo-AO-2 to deliver robotic, diffraction-limited observations at visible and near-infrared wavelengths in unprecedented numbers. This new instrument takes advantage of upgraded components, manufacturing techniques and control; and includes a parallel reconfigurable natural guide star wavefront sensor with which to explore hybrid wavefront sensing techniques. We present the results of commissioning in 2023 and 2024., Comment: Proceedings of SPIE, 13097-15

The unprecedented statistics of detected Type Ia supernovae (SNe Ia) brought by the Zwicky Transient Facility enables us to probe the impact of the Large-Scale Structure on the properties of these objects. The goal of this paper is to explore the possible impact of the under-dense part of the large-scale structure on the intrinsic SALT2 light curve properties of SNe Ia and uncover possible biases in SN Ia analyses. With a volume-limited selection of ZTF-Cosmo-DR2 Type Ia supernovae overlapping with the SDSS-DR7 survey footprint, we investigate the distribution of their properties with regard to voids detected in the SDSS-DR7 galaxy sample. We further use Voronoi volumes as proxy for local density environments within the large-scale structure. We find a moderate dependency of the stretch toward the localisation around the void centre and none when considering colour. The local Voronoi volumes mostly affect the fraction of low/high stretch supernovae. With the current statistics available, we consider that the impact of high or low local density environment can be considered as a proxy for the colour of the host galaxy. Under-dense environments should not cause any biases in supernova analyses., Comment: 10 pages, 8 figures. Submitted to A&A

To get distances, Type Ia Supernovae magnitudes are corrected for their correlation with lightcurve width and colour. Here we investigate how this standardisation is affected by the SN environment, with the aim to reduce scatter and improve standardisation. We first study the SN Ia stretch distribution, as well as its dependence on environment, as characterised by local and global (g-z) colour and stellar mass. We then look at the standardisation parameter $\alpha$, which accounts for the correlation between residuals and stretch, along with its environment dependence and linearity. We finally compute magnitude offsets between SNe in different astrophysical environments after colour and stretch standardisation, aka steps. This analysis is made possible due to the unprecedented statistics of the ZTF SN Ia DR2 volume-limited sample. The stretch distribution exhibits a bimodal behaviour, as previously found in literature. However, we find the distribution means to decrease with host stellar mass at a 9.0$\sigma$ significance. We demonstrate, at the 14.3$\sigma$ level, that the stretch-magnitude relation is non-linear, challenging the usual linear stretch-residuals relation. Fitting for a broken-$\alpha$ model, we indeed find two different slopes between stretch regimes ($x_1<-0.49\pm0.06$): $\alpha_{low}=0.28\pm0.01$ and $\alpha_{high}=0.09\pm0.01$, a $\Delta_{\alpha}=-0.19\pm0.01$ difference. As the relative proportion of SNe Ia in the high-/low-stretch modes evolves with redshift and environment, this implies that a linear $\alpha$ also evolves with redshift and environment. Concerning the environmental magnitude offset $\gamma$, we find it to be greater than 0.14 mag regardless of the considered environmental tracer used (local or global colour and stellar mass), all measured at the $\geq 6\sigma$ level, increased to $\sim0.18\pm0.01$ mag when accounting for the stretch-non linearity., Comment: 15 pages, 9 figures, submitted to Astronomy and Astrophysics

Gravitationally lensed Type Ia supernovae (glSNe Ia) are unique astronomical tools for studying cosmological parameters, distributions of dark matter, the astrophysics of the supernovae and the intervening lensing galaxies themselves. Only a few highly magnified glSNe Ia have been discovered by ground-based telescopes, such as the Zwicky Transient Facility (ZTF), but simulations predict the existence of a fainter, undetected population. We present a systematic search in the ZTF archive of alerts from 1 June 2019 to 1 September 2022. Using the AMPEL platform, we developed a pipeline that distinguishes candidate glSNe Ia from other variable sources. Initial cuts were applied to the ZTF alert photometry before forced photometry was obtained for the remaining candidates. Additional cuts were applied to refine the candidates based on their light curve colours, lens galaxy colours, and the resulting parameters from fits to the SALT2 SN Ia template. Candidates were also cross-matched with the DESI spectroscopic catalogue. Seven transients passed all the cuts and had an associated galaxy DESI redshift, which we present as glSN Ia candidates. While superluminous supernovae (SLSNe) cannot be fully rejected, two events, ZTF19abpjicm and ZTF22aahmovu, are significantly different from typical SLSNe and their light curves can be modelled as two-image glSN Ia systems. From this two-image modelling, we estimate time delays of 22 $\pm$ 3 and 34 $\pm$ 1 days for the two events, respectively, which suggests that we have uncovered a population with longer time delays. The pipeline is efficient and sensitive enough to parse full alert streams. It is currently being applied to the live ZTF alert stream to identify and follow-up future candidates while active. This pipeline could be the foundation for glSNe Ia searches in future surveys, like the Vera C. Rubin Observatory's Legacy Survey of Space and Time., Comment: 21 pages, 15 figures

We have discovered that the Halpha emission line star Haro 5-2, located in the 3-6 Myr old Ori OB1b association, is a young quadruple system. The system has a 2+2 configuration with an outer separation of 2.6 arcseconds and with resolved subarcsecond inner binary components. The brightest component, Aa, dominates the A-binary, it is a weakline T Tauri star with spectral type M2.5pm1. The two stars of the B component are equally bright at J, but the Bb star is much redder. Optical spectroscopy of the combined B pair indicates a rich emission line spectrum with a M3pm1 spectral type. The spectrum is highly variable and switches back and forth between a classical and a weakline T Tauri star. In the near-infrared, the spectrum shows Paschen beta and Brackett gamma in emission, indicative of active accretion. A significant mid-infrared excess reveals the presence of circumstellar or circumbinary material in the system. Most multiple systems are likely formed during the protostellar phase, involving flybys of neighboring stars followed by an in-spiraling phase driven by accretion from circumbinary material and leading to compact sub-systems. However, Haro 5-2 stands out among young 2+2 quadruples as the two inner binaries are unusually wide relative to the separation of the A and B pair, allowing future studies of the individual components. Assuming the components are coeval, the system could potentially allow stringent tests of PMS evolutionary models., Comment: 21 pages, 10 figures. Accepted by The Astronomical Journal

Multi-peaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility (ZTF). Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (-17.4 mag) and long (~100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew's spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak's photospheric phase, before H$\alpha$ resurfaces again during the nebular phase. The nebular lines ([O I], [Ca II], Mg I], H$\alpha$) exhibit a double-peaked structure which hints towards a clumpy or non-spherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than normal SESNe as well as requiring a very high $^{56}$Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak which also powers the second peak of the light curve through SN-CSM interaction., Comment: 22 pages, 11 figures, 5 tables

Classical gamma-ray bursts (GRBs) have two distinct emission episodes: prompt emission from ultra-relativistic ejecta and afterglow from shocked circumstellar material. While both components are extremely luminous in known GRBs, a variety of scenarios predict the existence of luminous afterglow emission with little or no associated high-energy prompt emission. We present AT 2019pim, the first secure example of this phenomenon to be identified. Serendipitously discovered during follow-up observations of a gravitational-wave trigger and located in a contemporaneous TESS sector, it is hallmarked by a fast-rising (t ~ 2 hr), luminous (M_UV,peak ~ -24.4 mag) optical transient with accompanying luminous X-ray and radio emission. No gamma-ray emission consistent with the time and location of the transient was detected by Fermi-GBM or by Konus, placing strong limits on an accompanying GRB. We investigate several independent observational aspects of the afterglow in the context of constraints on relativistic motion and find all of them are consistent with an initial Lorentz factor of Gamma_0 ~ 30-50, significantly lower than in any well-observed GRB and consistent with the theoretically-predicted "dirty fireball" scenario in which the high-energy prompt emission is stifled by pair production. However, we cannot rule out a structured jet model in which only the line-of-sight material was ejected at low-Gamma, off-axis from a classical high-Gamma jet core. This event represents a milestone in orphan afterglow searches, demonstrating that luminous afterglows with weak or no detectable gamma-ray radiation exist in nature and can be discovered by high-cadence optical surveys., Comment: Submitted to MNRAS

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

Cataclysmic variables (CVs) that have evolved past the period minimum during their lifetimes are predicted to be systems with a brown dwarf donor. While population synthesis models predict that around $\approx 40-70\%$ of the Galactic CVs are post-period minimum systems referred to as "period bouncers", only a few dozen confirmed systems are known. We report the study and characterisation of a new eclipsing CV, SRGeJ041130.3+685350 (SRGeJ0411), discovered from a joint SRG/eROSITA and ZTF program. The optical spectrum of SRGeJ0411 shows prominent hydrogen and helium emission lines, typical for CVs. We obtained optical high-speed photometry to confirm the eclipse of SRGeJ0411 and determine the orbital period to be $P_\textrm{orb} \approx 97.530$ minutes. The spectral energy distribution suggests that the donor has an effective temperature of $\lesssim 1,800$ K. We constrain the donor mass with the period--density relationship for Roche-lobe-filling stars and find that $M_\textrm{donor} \lesssim 0.04\ M_\odot$. The binary parameters are consistent with evolutionary models for post-period minimum CVs, suggesting that SRGeJ0411 is a new period bouncer. The optical emission lines of SRGeJ0411 are single-peaked despite the system being eclipsing, which is typically only seen due to stream-fed accretion in polars. X-ray spectroscopy hints that the white dwarf in SRGeJ0411 could be magnetic, but verifying the magnetic nature of SRGeJ0411 requires further investigation. The lack of optical outbursts has made SRGeJ0411 elusive in previous surveys, and joint X-ray and optical surveys highlight the potential for discovering similar systems in the near future., Comment: 17 pages, 16 figures, accepted to MNRAS

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

With the advancement in robotics, it is becoming increasingly common for large factories and warehouses to incorporate visual SLAM (vSLAM) enabled automated robots that operate closely next to humans. This makes any adversarial attacks on vSLAM components potentially detrimental to humans working alongside them. Loop Closure Detection (LCD) is a crucial component in vSLAM that minimizes the accumulation of drift in mapping, since even a small drift can accumulate into a significant drift over time. A prior work by Kim et al., SymbioLCD2, unified visual features and semantic objects into a single graph structure for finding loop closure candidates. While this provided a performance improvement over visual feature-based LCD, it also created a single point of vulnerability for potential graph-based adversarial attacks. Unlike previously reported visual-patch based attacks, small graph perturbations are far more challenging to detect, making them a more significant threat. In this paper, we present Adversarial-LCD, a novel black-box evasion attack framework that employs an eigencentrality-based perturbation method and an SVM-RBF surrogate model with a Weisfeiler-Lehman feature extractor for attacking graph-based LCD. Our evaluation shows that the attack performance of Adversarial-LCD with the SVM-RBF surrogate model was superior to that of other machine learning surrogate algorithms, including SVM-linear, SVM-polynomial, and Bayesian classifier, demonstrating the effectiveness of our attack framework. Furthermore, we show that our eigencentrality-based perturbation method outperforms other algorithms, such as Random-walk and Shortest-path, highlighting the efficiency of Adversarial-LCD's perturbation selection method., Comment: Accepted at VISIGRAPP 2024, 8 pages

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

Binary systems containing a compact object may exhibit periodic brightening episodes due to gravitational lensing as the compact object transits the companion star. Such ``self-lensing'' signatures have been detected before for white dwarf binaries. We attempt to use these signatures to identify detached stellar-mass neutron star and black hole binaries using data from the Zwicky Transient Facility (ZTF). We present a systematic search for self-lensing signals in Galactic binaries from a subset of high-cadence ZTF data taken in 2018. We identify 12 plausible candidates from the search, although because each candidate is observed to only brighten once, other origins such as stellar flares are more likely. We discuss prospects for more comprehensive future searches of the ZTF data., Comment: 12 pages. Accepted to the Open Journal of Astrophysics

A distinction is often drawn between a model's ability to predict a label for an evaluation sample that is directly memorised from highly similar training samples versus an ability to predict the label via some method of generalisation. In the context of using Language Models for question-answering, discussion continues to occur as to the extent to which questions are answered through memorisation. We consider this issue for questions that would ideally be answered through reasoning over an associated context. We propose a method of identifying evaluation samples for which it is very unlikely our model would have memorised the answers. Our method is based on semantic similarity of input tokens and label tokens between training and evaluation samples. We show that our method offers advantages upon some prior approaches in that it is able to surface evaluation-train pairs that have overlap in either contiguous or discontiguous sequences of tokens. We use this method to identify unmemorisable subsets of our evaluation datasets. We train two Language Models in a multitask fashion whereby the second model differs from the first only in that it has two additional datasets added to the training regime that are designed to impart simple numerical reasoning strategies of a sort known to improve performance on some of our evaluation datasets but not on others. We then show that there is performance improvement between the two models on the unmemorisable subsets of the evaluation datasets that were expected to benefit from the additional training datasets. Specifically, performance on unmemorisable subsets of two of our evaluation datasets, DROP and ROPES significantly improves by 9.0%, and 25.7% respectively while other evaluation datasets have no significant change in performance.

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 present a sample of 34 normal SNe II detected with the Zwicky Transient Facility, with multi-band UV light-curves starting at $t \leq 4$ days after explosion, as well as X-ray detections and upper limits. We characterize the early UV-optical colors and provide prescriptions for empirical host-extinction corrections. We show that the $t > 2\,$days UV-optical colors and the blackbody evolution of the sample are consistent with the predictions of spherical phase shock-cooling (SC), independently of the presence of `flash ionization" features. We present a framework for fitting SC models which can reproduce the parameters of a set of multi-group simulations without a significant bias up to 20% in radius and velocity. Observations of about half of the SNe II in the sample are well-fit by models with breakout radii $<10^{14}\,$cm. The other half are typically more luminous, with observations from day 1 onward that are better fit by a model with a large $>10^{14}\,$cm breakout radius. However, these fits predict an early rise during the first day that is too slow. We suggest these large-breakout events are explosions of stars with an inflated envelope or a confined CSM with a steep density profile, at which breakout occurs. Using the X-ray data, we derive constraints on the extended ($\sim10^{15}$ cm) CSM density independent of spectral modeling, and find most SNe II progenitors lose $<10^{-4} M_{\odot}\, \rm yr^{-1}$ a few years before explosion. This provides independent evidence the CSM around many SNe II progenitors is confined. We show that the overall observed breakout radius distribution is skewed to higher radii due to a luminosity bias. We argue that the $66^{+11}_{-22}\%$ of red supergiants (RSG) explode as SNe II with breakout radii consistent with the observed distribution of field RSG, with a tail extending to large radii, likely due to the presence of CSM., Comment: Submitted to ApJ. Comments are welcome at ido.irani@weizmann.ac.il or idoirani@gmail.com. Accepted version

Observing a supernova explosion shortly after it occurs can reveal important information about the physics of stellar explosions and the nature of the progenitor stars of supernovae (SNe). When a star with a well-defined edge explodes in vacuum, the first photons to escape from its surface appear as a brief shock-breakout flare. The duration of this flare can extend to at most a few hours even for nonspherical breakouts from supergiant stars, after which the explosion ejecta should expand and cool. Alternatively, for stars exploding within a distribution of sufficiently dense optically thick circumstellar material, the first photons escape from the material beyond the stellar edge, and the duration of the initial flare can extend to several days, during which the escaping emission indicates photospheric heating. The difficulty in detecting SN explosions promptly after the event has so far limited data regarding supergiant stellar explosions mostly to serendipitous observations that, owing to the lack of ultraviolet (UV) data, were unable to determine whether the early emission is heating or cooling, and hence the nature of the early explosion event. Here, we report observations of SN 2023ixf in the nearby galaxy M101, covering the early days of the event. Using UV spectroscopy from the Hubble Space Telescope (HST) as well as a comprehensive set of additional multiwavelength observations, we trace the photometric and spectroscopic evolution of the event and are able to temporally resolve the emergence and evolution of the SN emission.

Neutron stars and stellar-mass black holes are the remnants of massive star explosions. Most massive stars reside in close binary systems, and the interplay between the companion star and the newly formed compact object has been theoretically explored, but signatures for binarity or evidence for the formation of a compact object during a supernova explosion are still lacking. Here we report a stripped-envelope supernova, SN 2022jli, which shows 12.4-day periodic undulations during the declining light curve. Narrow H$\alpha$ emission is detected in late-time spectra with concordant periodic velocity shifts, likely arising from hydrogen gas stripped from a companion and accreted onto the compact remnant. A new Fermi/LAT $\gamma$-ray source is temporally and positionally consistent with SN 2022jli. The observed properties of SN 2022jli, including periodic undulations in the optical light curve, coherent H$\alpha$ emission shifting, and evidence for association with a $\gamma$-ray source, point to the explosion of a massive star in a binary system leaving behind a bound compact remnant. Mass accretion from the companion star onto the compact object powers the light curve of the supernova and generates the $\gamma$-ray emission., Comment: Accepted for publication in Nature

Tidal disruption events (TDEs) occur when a star enters the tidal radius of a supermassive black hole (SMBH). If the star only grazes the tidal radius, a fraction of the stellar mass will be accreted in a partial TDE (pTDE). The remainder can continue orbiting and may re-disrupted at pericenter, causing a repeating pTDE. pTDEs may be as or more common than full TDEs (fTDEs), yet few are known. In this work, we present the discovery of the first repeating pTDE from a systematically-selected sample, AT\,2020vdq. AT\,2020vdq was originally identified as an optically- and radio-flaring TDE. Around $3$ years after its discovery, it rebrightened dramatically and rapidly in the optical. The optical flare was remarkably fast and luminous compared to previous TDEs. It was accompanied by extremely broad (${\sim}0.1c$) optical/UV spectral features and faint X-ray emission ($L_X \sim 3\times10^{41}$\,erg\,s$^{-1}$), but no new radio-emitting component. Based on the transient optical/UV spectral features and the broadband light curve, we show that AT\,2020vdq is a repeating pTDE. We then use it to constrain TDE models; in particular, we favor a star originally in a very tight binary system that is tidally broken apart by the Hills mechanism. We also constrain the repeating pTDE rate to be $10^{-6}$ to $10^{-5}$ yr$^{-1}$ galaxy$^{-1}$, with uncertainties dominated by the unknown distribution of pTDE repeat timescales. In the Hills framework, this means the binary fraction in the galactic nucleus is of the order few percent., Comment: 24 pages, 13 figures, submitted to ApJ

ATLASv2 is based on a previously generated dataset included in "ATLAS: A Sequence-based Learning Approach for Attack Investigation." The original ATLAS dataset is comprised of Windows Security Auditing system logs, Firefox logs, and DNS logs via WireShark. In ATLASv2, we aim to enrich the ATLAS dataset with higher quality background noise and additional logging vantage points. This work replicates the ten attack scenarios described in ATLAS, but extends the logging to include Sysmon logs and events tracked through VMware Carbon Black Cloud. The main contribution of ATLASv2 is to improve the quality of the benign system activity and the integration of the attack scenarios. Instead of relying on automated scripts to generate activity, we had two researchers use the victim machines as their primary work stations throughout the course of the engagement. This allowed us to capture system logs on actual user behavior. Additionally, the researchers conducted the attacks in a lab setup allowing the integration of the attack into the work flow of the victim user. This allows the ATLASv2 dataset to provide realistic system logs that mirror the system log activity generated in real-world attacks.

White dwarfs, the extremely dense remnants left behind by most stars after their death, are characterised by a mass comparable to that of the Sun compressed into the size of an Earth-like planet. In the resulting strong gravity, heavy elements sink toward the centre and the upper layer of the atmosphere contains only the lightest element present, usually hydrogen or helium. Several mechanisms compete with gravitational settling to change a white dwarf's surface composition as it cools, and the fraction of white dwarfs with helium atmospheres is known to increase by a factor ~2.5 below a temperature of about 30,000 K; therefore, some white dwarfs that appear to have hydrogen-dominated atmospheres above 30,000 K are bound to transition to be helium-dominated as they cool below it. Here we report observations of ZTF J203349.8+322901.1, a transitioning white dwarf with two faces: one side of its atmosphere is dominated by hydrogen and the other one by helium. This peculiar nature is likely caused by the presence of a small magnetic field, which creates an inhomogeneity in temperature, pressure or mixing strength over the surface. ZTF J203349.8+322901.1 might be the most extreme member of a class of magnetic, transitioning white dwarfs -- together with GD 323, a white dwarf that shows similar but much more subtle variations. This new class could help shed light on the physical mechanisms behind white dwarf spectral evolution., Comment: 45 pages, 11 figures

When provided with sufficient explanatory context, smaller Language Models have been shown to exhibit strong reasoning ability on challenging short-answer question-answering tasks where the questions are unseen in training. We evaluate two methods for further improvement in this setting. Both methods focus on combining rationales generated by a larger Language Model with longer contexts created from a multi-hop dense retrieval system. The first method ($\textit{RR}$) involves training a Rationale Ranking model to score both generated rationales and retrieved contexts with respect to relevance and truthfulness. We then use the scores to derive combined contexts from both knowledge sources using a number of combinatory strategies. For the second method ($\textit{RATD}$) we utilise retrieval-augmented training datasets developed by Hartill et al. 2023 to train a smaller Reasoning model such that it becomes proficient at utilising relevant information from longer text sequences that may be only partially evidential and frequently contain many irrelevant sentences. We find that both methods significantly improve results. Our single best Reasoning model materially improves upon strong comparable prior baselines for unseen evaluation datasets (StrategyQA 58.9 $\rightarrow$ 61.7 acc., CommonsenseQA 63.6 $\rightarrow$ 72.7 acc., ARC-DA 31.6 $\rightarrow$ 52.1 F1, IIRC 25.5 $\rightarrow$ 27.3 F1) and a version utilising our prior knowledge of each type of question in selecting a context combination strategy does even better. Our proposed models also generally outperform direct prompts against much larger models (BLOOM 175B and StableVicuna 13B) in both few-shot chain-of-thought and standard few-shot settings.

We equip a smaller Language Model to generalise to answering challenging compositional questions that have not been seen in training. To do so we propose a combination of multitask supervised pretraining on up to 93 tasks designed to instill diverse reasoning abilities, and a dense retrieval system that aims to retrieve a set of evidential paragraph fragments. Recent progress in question-answering has been achieved either through prompting methods against very large pretrained Language Models in zero or few-shot fashion, or by fine-tuning smaller models, sometimes in conjunction with information retrieval. We focus on the less explored question of the extent to which zero-shot generalisation can be enabled in smaller models with retrieval against a corpus within which sufficient information to answer a particular question may not exist. We establish strong baselines in this setting for diverse evaluation datasets (StrategyQA, CommonsenseQA, IIRC, DROP, Musique and ARC-DA), and show that performance can be significantly improved by adding retrieval-augmented training datasets which are designed to expose our models to a variety of heuristic reasoning strategies such as weighing partial evidence or ignoring an irrelevant context.