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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. 

The construction of bounded-degree plane geometric spanners has been a focus of interest since 2002 when Bose, Gudmundsson, and Smid proposed the first algorithm to construct such spanners. To date, 11 algorithms have been designed with various tradeoffs in degree and stretch-factor. We have implemented these sophisticated spanner algorithms in C ++ using the CGAL library and experimented with them using large synthetic and real-world pointsets. Our experiments have revealed their practical behavior and real-world efficacy. We share the implementations via GitHub for broader uses and future research. We design and engineer EstimateStretchFactor , a simple practical algorithm, which can estimate stretch-factors (obtains lower bounds on the exact stretch-factors) of geometric spanners—a challenging problem for which no practical algorithm is known yet. In our experiments with bounded-degree plane geometric spanners, we found that EstimateStretchFactor estimated stretch-factors almost precisely. Further, it gave linear runtime performance in practice for the pointset distributions considered in this work, making it much faster than the naive Dijkstra-based algorithm for calculating stretch-factors. 

Non-equilibrium photocarriers in multilayer WSe₂injected by femtosecond laser pulses exhibit extraordinary nonlinear dynamics in the presence of intense THz fields. The THz absorption in optically excited WSe₂rises rapidly in the low THz field regime and gradually ramps up at high intensities. The strong THz pulses drive the photocarriers into sidebands of higher mobility and release trapped charge carriers, which consequently enhance the transient conductivity of WSe₂. The spectrally analyzed conductivity reveals distinctive features, indicating that the photocarriers undergo resonant interactions such as carrier-photon scattering.