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Abstract Quasars are bright active galactic nuclei powered by the accretion of matter around supermassive black holes at the center of galaxies. Their stochastic brightness variability depends on the physical properties of the accretion disk and black hole. The upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe tens of millions of quasars, so there is a need for efficient techniques like machine learning that can handle the large volume of data. Quasar variability is believed to be driven by an X-ray corona, which is reprocessed by the accretion disk and emitted as UV/optical variability. We are the first to introduce an auto-differentiable simulation of the accretion disk and reprocessing. We use the simulation as a direct component of our neural network to jointly model the driving variability and reprocessing, trained with supervised learning on simulated LSST-like 10 yr quasar light curves. We encode the light curves using a transformer encoder, and the driving variability is reconstructed using latent stochastic differential equations, a physically motivated generative deep learning method that can model continuous-time stochastic dynamics. By embedding the physical processes of the driving signal and reprocessing into our network, we achieve a model that is more robust and interpretable. We demonstrate that our model outperforms a Gaussian process regression baseline and can infer accretion disk parameters and time delays between wave bands, even for out-of-distribution driving signals. Our approach provides a powerful framework that can be adapted to solve other inverse problems in multivariate time series. 

Abstract Herein high-strength composites are prepared from elemental sulfur, sunflower oil, and wastewater sludge. Fats extracted from dissolved air flotation (DAF) solids were reacted with elemental sulfur to yield compositeDAFS(10 wt% DAF fats and 90 wt% sulfur). Additional composites were prepared from DAF fat, sunflower oil and sulfur to giveSunDAF_x(x = wt% sulfur, varied from 85–90%). The composites were characterized by spectroscopic, thermal, and mechanical methods. FT-IR spectra revealed a notable peak at 798 cm^–1indicating a C–S stretch inDAFS,SunDAF₉₀, andSunDAF₈₅indicating successful crosslinking of polymeric sulfur with olefin units. SEM/EDX analysis revealed homogenous distribution of carbon, oxygen, and sulfur inSunDAF₉₀andSunDAF₈₅. The percent crystallinity exhibited byDAFS(37%),SunDAF₉₀(39%), andSunDAF₈₅(45%) was observed to be slightly lower than that of previous composites prepared from elemental sulfur and fats and oils.DAFSandSunDAF_xdisplayed compressive strengths (26.4–38.7 MPa) of up to 227% above that required (17 MPa) of ordinary Portland cement for residential building foundations. The composite decomposition temperatures ranged from 211 to 219 °C, with glass transition temperatures of − 37 °C to − 39 °C. These composites thus provide a potential route to reclaim wastewater organics for use in value-added structural materials having mechanical properties competitive with those of commercial products. 

Abstract Tidal disruption events (TDEs) that are spatially offset from the nuclei of their host galaxies offer a new probe of massive black hole (MBH) wanderers, binaries, triples, and recoiling MBHs. Here we present AT2024tvd, the first off-nuclear TDE identified through optical sky surveys. High-resolution imaging with the Hubble Space Telescope shows that AT2024tvd is 0 $\stackrel{\text{″}}{.}$914 ± 0 $\stackrel{\text{″}}{.}$010 offset from the apparent center of its host galaxy, corresponding to a projected distance of 0.808 ± 0.009 kpc atz= 0.045. Chandra and Very Large Array observations support the same conclusion for the TDE’s X-ray and radio emission. AT2024tvd exhibits typical properties of nuclear TDEs, including a persistent hot UV/optical component that peaks atL_bb ∼ 6 × 10⁴³erg s⁻¹, broad hydrogen lines in its optical spectra, and delayed brightening of luminous (L_X,peak ∼ 3 × 10⁴³erg s⁻¹), highly variable soft X-ray emission. The MBH mass of AT2024tvd is 10^6±1M_⊙, at least 10 times lower than its host galaxy’s central black hole mass (≳10⁸M_⊙). The MBH in AT2024tvd has two possible origins: a wandering MBH from the lower-mass galaxy in a minor merger during the dynamical friction phase or a recoiling MBH ejected by triple interactions. Combining AT2024tvd with two previously known off-nuclear TDEs discovered in X-rays (3XMM J2150 and EP240222a), which likely involve intermediate-mass black holes in satellite galaxies, we find that the parent galaxies of all three events are very massive (∼10^10.9M_⊙). This result aligns with expectations from cosmological simulations that the number of offset MBHs scales linearly with the host halo mass. 

Abstract We present an analysis of NuSTAR X-ray observations of three active galactic nuclei (AGN) that were identified as candidate subparsec binary supermassive black hole (SMBH) systems in the Catalina Real-Time Transient Survey based on apparent periodicity in their optical light curves. Simulations predict that close-separation accreting SMBH binaries will have different X-ray spectra than single accreting SMBHs. We previously observed these AGN with Chandra and found no differences between their low-energy X-ray properties and the larger AGN population. However, some models predict differences to be more prominent at energies higher than probed by Chandra. We find that even at the higher energies probed by NuSTAR, the spectra of these AGN are indistinguishable from the larger AGN population. This could rule out models predicting large differences in the X-ray spectra in the NuSTAR bands. Alternatively, it might mean that these three AGN are not binary SMBHs. 

Abstract Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling. 

Abstract We present Cryoscope, a new 50 deg²field-of-view, 1.2 m aperture,K_darksurvey telescope to be located at Dome C, Antarctica. Cryoscope has an innovative optical–thermal design wherein the entire telescope is cryogenically cooled. Cryoscope also explores new detector technology to cost-effectively tile the full focal plane. Leveraging the dark Antarctic sky and minimizing telescope thermal emission, Cryoscope achieves unprecedented deep, wide, fast, and red observations, matching and exceeding volumetric survey speeds from the Ultraviolet Explorer, Vera Rubin Observatory, Nancy Grace Roman Space Telescope, SPHEREx, and NEO Surveyor. By providing coverage beyond wavelengths of 2μm, we aim to create the most comprehensive dynamic movie of the most obscured reaches of the Universe. Cryoscope will be a dedicated discovery engine for electromagnetic emission from coalescing compact binaries, Earth-like exoplanets orbiting cold stars, and multiple facets of time-domain, stellar, and solar system science. In this paper, we describe the scientific drivers and technical innovations for this new discovery engine operating in theK_darkpassband, why we choose to deploy it in Antarctica, and the status of a fifth-scale prototype designed as a Pathfinder to retire technological risks prior to full-scale implementation. We plan to deploy the Cryoscope Pathfinder to Dome C in 2026 December and the full-scale telescope by 2030. 

Abstract About 3%–10% of Type I active galactic nuclei (AGNs) have double-peaked broad Balmer lines in their optical spectra originating from the motion of gas in their accretion disk. Double-peaked profiles arise not only in AGNs, but occasionally appear during optical flares from tidal disruption events and changing-state AGNs. In this paper, we identify 250 double-peaked emitters (DPEs) among a parent sample of optically variable broad-line AGNs in the Zwicky Transient Facility (ZTF) survey, corresponding to a DPE fraction of 19%. We model spectra of the broad Hαemission-line regions and provide a catalog of the fitted accretion disk properties for the 250 DPEs. Analysis of power spectra derived from the 5 yr ZTF light curves finds that DPE light curves have similar amplitudes and power-law indices to other broad-line AGNs. Follow-up spectroscopy of 12 DPEs reveals that ∼50% display significant changes in the relative strengths of their red and blue peaks over long 10–20 yr timescales, indicating that broad-line profile changes arising from spiral arm or hotspot rotation are common among optically variable DPEs. Analysis of the accretion disk parameters derived from spectroscopic modeling provides evidence that DPEs are not in a special accretion state, but are simply normal broad-line AGNs viewed under the right conditions for the accretion disk to be easily visible. We include inspiraling supermassive black hole binary candidate SDSSJ1430+2303 in our analysis, and discuss how its photometric and spectroscopic variability is consistent with the disk-emitting AGN population in the ZTF survey. 

Abstract We present the tidal disruption event (TDE) AT2022lri, hosted in a nearby (≈144 Mpc) quiescent galaxy with a low-mass massive black hole (10⁴M_⊙<M_BH< 10⁶M_⊙). 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 to 672 days after peak. The X-ray luminosity gradually declined from 1.5 × 10⁴⁴erg s⁻¹to 1.5 × 10⁴³erg s⁻¹and 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 a variability timescale of ≈0.5 hr–1 days and amplitude of ≈2–8. When fitted with simple continuum models, the X-ray spectrum is dominated by a thermal disk component with inner temperature going from ∼146 to ∼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 a scenario either 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 subrelativistic (0.1–0.3c) 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.