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Abstract Multiyear observations from the Sloan Digital Sky Survey (SDSS) Reverberation Mapping ​(RM) project have significantly increased the number of quasars with reliable RM lag measurements. We statistically analyze target properties, light-curve characteristics, and survey design choices to identify factors crucial for successful and efficient RM surveys. Analyzing 172 high-confidence (“gold”) lag measurements from SDSS-RM for the Hβ, Mgii, and Civemission lines, we find that the Durbin–Watson statistic (a statistical test for residual correlation) is the most significant predictor of light curves suitable for lag detection. The variability signal-to-noise ratio and emission-line placement on the detector also correlate with successful lag measurements. We further investigate the impact of the observing cadence on the survey design by analyzing the effect of reducing observations in the first year of SDSS-RM. Our results demonstrate that a modest reduction in the observing cadence to ∼1.5 weeks between observations can retain approximately 90% of the lag measurements compared to twice-weekly observations in the initial year. Provided similar and uniform sampling in subsequent years, this adjustment has a minimal effect on the overall recovery of lags across all emission lines. These results provide valuable inputs for optimizing future RM surveys. 

Abstract Over three decades of reverberation mapping (RM) studies on local broad-line active galactic nuclei (AGNs) have measured reliable black hole (BH) masses for >100 AGNs. These RM measurements reveal a significant correlation between the Balmer broad-line region (BLR) size and AGN optical luminosity (theR–Lrelation). Recent RM studies for AGN samples with more diverse BH parameters (e.g., mass and Eddington ratio) reveal a substantial intrinsic dispersion around the averageR–Lrelation, suggesting that variations in the broadband spectrum, driven by accretion parameters and other factors such as the cloud distribution and inclination, significantly influence the measuredR–Lrelation. Here we perform a detailed photoionization investigation of expected broad-line properties as functions of accretion parameters using AGN continuum models fromqsosed. We compare theoretical predictions with observations of a sample of 67z ≲ 0.5 reverberation-mapped AGNs with rest-frame optical and UV spectra in the moderate-accretion regime (Eddington ratioλ_Edd ≡ L/L_Edd < 0.5). The UV/optical line strengths and their dependences on accretion parameters are reasonably well reproduced by the locally optimally emitting cloud photoionization models. We provide quantitative recipes using optical/UV line flux ratios to infer the unobservable ionizing continuum. Additionally, photoionization models with universal values of ionization parameter ( $\log U_{\mathrm{H}}=-2$) and hydrogen density ( $\log n\left(\mathrm{H}\right)=12$) can qualitatively reproduce the observed globalR–Lrelation for the current RM AGN sample. However, such models fail to reproduce the observed decrease in BLR size with increasingL/L_Eddat fixed optical luminosity, implying that gas density or BLR structure may systematically change with accretion rate. 

Abstract We present dynamical modeling of the broad-line region (BLR) of the highly variable active galactic nucleus (AGN) SDSS J141041.25+531849.0 (z= 0.359) using photometric and spectroscopic monitoring data from the Sloan Digital Sky Survey (SDSS) Reverberation Mapping project and the current fifth-generation SDSS Black Hole Mapper program, spanning from early 2013 to early 2023. We model the geometry and kinematics of the BLR in the Hβ, Hα, and Mgiiemission lines for three different time periods to measure the potential change of structure within the BLR across time and line species. We find a moderately face-on $(i_{\mathrm{full}-\mathrm{state}}=29.{68}_{-3.62}^{+4.74}\mathrm{deg})$thick-disk $({\theta }_{\mathrm{opn},\mathrm{full}-\mathrm{state}}=42.{04}_{-3.96}^{+4.32}\mathrm{deg})$geometry for most BLRs, with a joint estimate for the mass of the supermassive black hole for each of three time periods, yielding ${\log }_{10}(M_{\mathrm{BH}}/M_{\odot })=8.10_{-0.03}^{+0.03}$when using the full data set. The inferred individual virial factorf∼ 1.6 is moderately smaller than the average factor for a local sample of dynamically modeled AGNs. There is strong evidence for nonvirial motion, with over 70% of clouds on inflowing/outflowing orbits. We analyze the change in model parameters across emission lines, finding the radii of BLRs for the emission lines are consistent with the following relative sizesR_Hβ ≲ R_MgII ≲ R_Hα. Comparing results across time, we findR_low-state ≲ R_high-state, with the change in BLR size for Hβbeing more significant than for the other two lines. The data also reveal complex, time-evolving, and potentially transient dynamics of the BLR gas over a decade-long timescale, encouraging for future dynamical modeling of fine-scale BLR kinematics. 

As hyperscalers such as Google, Microsoft, and Amazon play an increasingly important role in today's Internet, they are also capable of manipulating probe packets that traverse their privately owned and operated backbones. As a result, standard traceroute-based measurement techniques are no longer a reliable means for assessing network connectivity in these global-scale cloud provider infrastructures. In response to these developments, we present a new empirical approach for elucidating connectivity in these private backbone networks. Our approach relies on using only lightweight (i.e., simple, easily interpretable, and readily available) measurements, but requires applying heavyweight mathematical techniques for analyzing these measurements. In particular, we describe a new method that uses network latency measurements and relies on concepts from Riemannian geometry (i.e., Ricci curvature) to assess the characteristics of the connectivity fabric of a given network infrastructure. We complement this method with a visualization tool that generates a novel manifold view of a network's delay space. We demonstrate our approach by utilizing latency measurements from available vantage points and virtual machines running in datacenters of three large cloud providers to study different aspects of connectivity in their private backbones and show how our generated manifold views enable us to expose and visualize critical aspects of this connectivity. 

Extremely variable quasars can also show strong changes in broad-line emission strength and are known as changing-look quasars (CLQs). To study the CLQ transition mechanism, we present a pilot sample of CLQs with X-ray observations in both the bright and faint states. From a sample of quasars with bright-state archival SDSS spectra and (Chandra or XMM-Newton) X-ray data, we identified five new CLQs via optical spectroscopic follow-up and then obtained new target-of-opportunity X-ray observations with Chandra. No strong absorption is detected in either the bright- or the faint-state X-ray spectra. The intrinsic X-ray flux generally changes along with the optical variability, and the X-ray power-law slope becomes harder in the faint state. Large-amplitude mid-infrared variability is detected in all five CLQs, and it echoes the variability in the optical with a time lag expected from the light-crossing time of the dusty torus for CLQs with robust lag measurements. The changing-obscuration model is not consistent with the observed X-ray spectra and spectral energy distribution changes seen in these CLQs. It is highly likely that the observed changes are due to the changing accretion rate of the supermassive black hole, so the multiwavelength emission varies accordingly, with promising analogies to the accretion states of X-ray binaries. 

The main premise of this work is that since large cloud providers can and do manipulate probe packets that traverse their privately owned and operated backbones, standard traceroute-based measurement techniques are no longer a reliable means for assessing network connectivity in large cloud provider infrastructures. In response to these developments, we present a new empirical approach for elucidating private connectivity in today's Internet. Our approach relies on using only "light-weight" ( i.e., simple, easily-interpretable, and readily available) measurements, but requires applying a "heavy-weight" or advanced mathematical analysis. In particular, we describe a new method for assessing the characteristics of network path connectivity that is based on concepts from Riemannian geometry ( i.e., Ricci curvature) and also relies on an array of carefully crafted visualizations ( e.g., a novel manifold view of a network's delay space). We demonstrate our method by utilizing latency measurements from RIPE Atlas anchors and virtual machines running in data centers of three large cloud providers to (i) study different aspects of connectivity in their private backbones and (ii) show how our manifold-based view enables us to expose and visualize critical aspects of this connectivity over different geographic scales. 

Which galaxies in the general population turn into active galactic nuclei (AGNs) is a keystone of galaxy formation and evolution. Thanks to SRG/eROSITA’s contiguous 140 square degree pilot survey field, we constructed a large, complete, and unbiased soft X-ray flux-limited ( F X  > 6.5 × 10 −15 erg s −1 cm −2 ) AGN sample at low redshift, 0.05 <  z  < 0.55. Two summary statistics, the clustering using spectra from SDSS-V and galaxy-galaxy lensing with imaging from HSC, are measured and interpreted with halo occupation distribution and abundance matching models. Both models successfully account for the observations. We obtain an exceptionally complete view of the AGN halo occupation distribution. The population of AGNs is broadly distributed among halos with a mean mass of 3.9 −2.4 +2.0  × 10 12   M ⊙ . This corresponds to a large-scale halo bias of b ( z  = 0.34) = 0.99 −0.10 +0.08 . The central occupation has a large transition parameter, σ log 10 ( M )  = 1.28 ± 0.2. The satellite occupation distribution is characterized by a shallow slope, α sat  = 0.73 ± 0.38. We find that AGNs in satellites are rare, with f sat  < 20%. Most soft X-ray-selected AGNs are hosted by central galaxies in their dark matter halo. A weak correlation between soft X-ray luminosity and large-scale halo bias is confirmed (3.3 σ ). We discuss the implications of environmental-dependent AGN triggering. This study paves the way toward fully charting, in the coming decade, the coevolution of X-ray AGNs, their host galaxies, and dark matter halos by combining eROSITA with SDSS-V, 4MOST, DESI, LSST, and Euclid data.