Gordon T Richards

Contemporary large-scale surveys such as the and Euclid present an unprecedented discovery potential for studying at the population level in the big data era. However, one major challenge is the accurate identification and classification of from optical and near-infrared photometry or variability data alone. To optimize selection, classification, and systematics as well as to test different data analysis tools, we present ( ), an end-to-end simulation software. Developed as part of the INAF in-kind contribution, is capable of simulating the anticipated AGN population in and Euclid. LSST AGN AGN AGN AGILE AGILE LSST LSST AGILE LSST We based on existing simulations of galaxies and stars, while we developed an recipe based on empirical relations. populates complete galaxy samples with according to the observed AGILE AGN AGILE AGN AGN accretion rate distribution, and each is assigned an optical/UV spectral energy distribution. Optical variability is added using a damped random walk model connected to the physical parameters. Finally, creates both -like images and related data products. AGN AGN AGN AGILE LSST Using , we built a 24, ^2 complete mock truth catalog of , galaxies, and stars with 0.2 < z < 5.5, łogMstar > 8.5 ( and galaxies), and r < 27.5, (stars). We also performed a pilot simulation ( DR1) consisting of 1, ^2 of operations in the COSMOS field observed up to three years in accordance with the survey strategy. We used DR1 to quantify the accuracy of the LSST Science Pipelines in recovering the true fluxes of , galaxies, and stars. We quantified the completeness and purity in recovering using typical color-color and variability selections. We share the DR1 dataset, as it represents an ideal test bench for further scientific exploitation and forecasts in the context of AGILE deg AGN AGN mag AGILE deg LSST AGILE AGN LSST AGN AGILE LSST AGN .

The Legacy Survey of Space and Time (LSST), being conducted by the Vera C. Rubin Observatory, is a wide-field multiband survey that will revolutionize our understanding of extragalactic sources through its unprecedented combination of area and depth. While the LSST survey strategy is still being finalized, the Rubin Observatory team has generated a series of survey simulations using the LSST Operations Simulator to explore the optimal survey strategy that best accommodates the majority of scientific goals. In this study, we utilize the latest simulated data and the Metrics Analysis Framework to predict the number of quasars detectable by LSST in each band and evaluate the impact of different survey strategies. We find that the number of quasars and lower-luminosity active galactic nuclei (AGNs) detected in the baseline strategy (v4.3.1) in the redshift range z = 0.3–6.7 will be highest in the i band (about 12 million) and lowest in the u band (about 6 million). Over 70% of quasars are expected to be detected within the first year in all bands, as LSST will have already reached the break in the luminosity function at most redshifts. With a limiting magnitude of 25.7 (26.9) mag, we expect to detect 184 (199) million AGNs in the z band (r band) over the 10 yr survey, with quasars constituting only 6% of the total AGNs in each band. This arises because, considering that the luminosities of most low-luminosity AGNs are affected by contamination from their host galaxies, we set a magnitude threshold when predicting the number of quasars. We find that variations in the u-band strategy can impact the number of quasar detections. Specifically, the difference between the baseline strategy and that with the largest total exposure in u is 15%. In contrast, changes in rolling strategies, Deep Drilling Field strategies, weather conditions, and Target of Opportunity observations result in variations below 2%. These results provide valuable insights for optimizing approaches to maximize the scientific output of quasar studies.

Contemporary large-scale surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) and Euclid present an unprecedented discovery potential for studying AGNs at the population level in the big data era. However, one major challenge is the accurate identification and classification of AGNs from optical/NIR photometry, or variability data alone. In order to optimize AGN selection, classification, and systematics, as well as to test different data analysis tools, we present AGILE (AGNs In the LSST Era), an LSST end-to-end simulation software. AGILE – developed as part of the INAF LSST in-kind contribution – is capable of simulating the anticipated AGN population in LSST and Euclid. We based AGILE on existing simulations of galaxies and stars, while we developed an AGN recipe based on empirical relations. AGILE populates complete galaxy samples with AGNs according to the observed AGN accretion rate distribution, and each AGN is assigned an optical/UV spectral energy distribution. Optical AGN variability is added using a damped random walk model connected to the AGN physical parameters. Finally, AGILE creates both LSST-like images and related data products. Using AGILE, we build a24deg ²complete mock truth catalog of AGNs, galaxies, and stars with0.2 < z < 5.5 ,\log M/M_(⊙) > 8.5(AGNs and galaxies), andr < 27.5mag (stars). We perform a pilot simulation (AGILE DR1) consisting of1deg ²of LSST operations in the COSMOS field observed up to three years according to the survey strategy. We use AGILE DR1 to quantify the accuracy of the LSST Science Pipelines in recovering true fluxes of AGNs, galaxies, and stars. We quantify the LSST completeness and purity in recovering Type 1 AGNs using typical color-color and variability selections. We share the AGILE DR1 dataset, an ideal test-bench for further scientific exploitation.

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) is expected to obtain observations of over ten million quasars. The survey's exceptional cadence and sensitivity will enable a significant fraction of these objects to be monitored in the ugrizy bands, spanning observed wavelengths of approximately 0.3-1.0,μ ) based on the redshift, the rest-frame wavelength, and the AGN luminosity. We constructed variability-based photometric redshift (photo-z) priors by modeling the observed variability using the expected DRW parameters at a given redshift. These variability-based photo-z ( ) priors were then combined with traditional spectral energy distribution (SED) fitting to improve the redshift estimates from SED fitting. Validation was performed using observational data from the Sloan Digital Sky Survey (SDSS), demonstrating significant reduction in catastrophic outliers by more than 10% in comparison with SED fitting techniques and improvements in redshift precision. The simulated light curves with both SDSS and LSST-like cadences and baselines confirm that will be able to constrain the photometric redshifts of SDSS-like AGNs by bringing the outlier fractions down to below 15% from 32% (SED alone) at the end of the survey. The unprecedented number of sources makes spectroscopic follow-up for the vast majority of them unfeasible in the near future, so most studies will have to rely on photometric redshift estimates which are traditionally much less reliable for Active Galactic Nuclei (AGNs) than for inactive galaxies. This work presents a novel methodology to constrain the photometric redshift of AGNs that leverages the effects of cosmological time dilation, and of the luminosity and wavelength dependence of AGN variability. Specifically, we assume that the variability can be modeled as a damped random walk (DRW) process, and we adopted a parametric model to characterize the DRW timescale (τ) and asymptotic amplitude of the variability (SF _∞ VAR-PZ VAR-PZ

We use microlensing to probe the inner broad line region (BLR) of the lensed quasar SDSS J1004+4112, finding evidence of substructure. We study the recurrent microlensing events observed in the blue wing of the C IV emission line in image A of this lensed quasar from a series of 20 spectra taken over 15 yr. We obtain a microlensing light curve and confirm the presence of three high magnification events (Δm > –0.7 mag). A caustic crossing is a natural explanation for each one of the events. The fast rising and fading of the events imply that the width of the region scanned by the caustic in each event, ≲0.1 μas (≲0.93 ± 0.36 light days), is much smaller than the BLR size. However, the large range of velocities involved implies significant overlapping with the inner BLR velocity field. An elongated thin substructure in the BLR fulfills both requirements at once. A sequence of caustics crossing a single elongated substructure may be a possible explanation of the observed recurrence. However, this hypothesis requires some ad hoc assumptions about the microlens population. Alternatively, a single caustic encountering several narrow-stripped or bow-shaped substructures in the approaching part of the BLR could explain the variability. We discuss the possible identification of these elongated substructures with ripples or spiral structure on the inner BLR. Simulations of caustic crossings of a rippled disk statistically support this interpretation. The study of the C IV emission-line variability in SDSS J1004+4112 illustrates the incomparable scanning power of microlensing in both velocity and space.

We present the first infrared (IR) spectral predictions from a self-consistent simulation of the formation of a quasar in a starburst galaxy, spanning the cosmological environment to scales well below the dust sublimation region. The IR emission is dominated by a torus-like dust structure composed of a highly magnetized, turbulence-supported outer accretion disk and of accreting gas tidally torn from the interstellar medium (ISM). At these early stages, the active galactic nucleus is buried and Compton thick. The near- to mid-IR escaping luminosity varies by almost an order of magnitude across sight lines, largely due to extinction from the inflowing stream of cold dust. Self-absorption within the torus suppresses silicate emission features, and further reprocessing by the ambient ISM leads to prominent silicate absorption and colder IR emission. The sublimation structure is stratified by composition and size, producing sight-line-dependent extinction curves that intrinsically vary in shape. However, after repeated scattering in the optically thick dusty medium, these curves emerge substantially grayed. We also demonstrate that bipolar outflows from the central black hole, which carves biconical cavities and reveals the central engine in later stages, can preserve IR anisotropy and silicate features. These results suggest that dusty starburst quasars can undergo a buried, IR-bright phase early in their evolution.

Strong outflows from active galactic nuclei are frequently observed in objects with lower coronal X-ray luminosity. This intrinsic X-ray weakness is considered a requirement for the formation of radiatively driven winds. To obtain an unbiased view on the connection between X-ray emission and the presence of powerful winds in the most luminous quasar phase, we present an X-ray analysis of a sample of extremely luminous, radio-quiet quasars with signatures of strong outflows in their rest-frame ultraviolet (UV) emission spectra. We study the Chandra iv emission line blueshifts, comparing them to typical optically blue quasars. iv emission-line outflows might emerge at wind velocities greater than 3,000 km/s. Our study provides additional evidence that the relationship between X-ray emission and the presence of winds is intricate. Our findings emphasise the need for X-ray observations of a larger sample of UV-selected quasars with confirmed strong emission-line outflows to unravel the nuanced interplay between winds and X-ray emission.

The Legacy Survey of Space and Time (LSST), being conducted by the Vera C. Rubin Observatory, is a wide-field multi-band survey that will revolutionize our understanding of extragalactic sources through its unprecedented combination of area and depth. While the LSST survey strategy is still being finalized, the Rubin Observatory team has generated a series of survey simulations using the LSST Operations Simulator to explore the optimal survey strategy that best accommodates the majority of scientific goals. In this study, we utilize the latest simulated data to predict the number of detectable quasars by LSST in each band and evaluate the impact of different survey strategies. We find that the number of quasars and lower luminosity AGNs detected in the baseline strategy (v4.3.1) in the redshift range z=0.3-6.7 will be highest in the i-band and lowest in the u-band. Over 70% of quasars are expected to be detected within the first year in all bands, as LSST will have already reached the break of the luminosity function at most redshifts. With a limiting magnitude of 25.7 mag, we expect to detect 184 million AGNs in the z-band over the 10-year survey, with quasars constituting only 6% of the total AGNs in each band. This arises because, considering that the luminosities of most low-luminosity AGNs are affected by contamination from their host galaxies, we set a magnitude threshold when predicting the number of quasars. We find that variations in the u-band strategy can impact the number of quasar detections. Specifically, the difference between the baseline strategy and that with the largest total exposure in u is 15%. In contrast, changes in rolling strategies, DDF strategies, weather conditions, and Target of Opportunity observations result in variations below 2%. These results provide valuable insights for optimizing approaches to maximize the scientific output of quasar studies.

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will monitor tens of millions of active galactic nuclei (AGNs) for a period of 10 years with an average cadence of 3 days in six broad photometric bands. This unprecedented dataset will enable robust characterizations of AGN UV/optical variability across a wide range of AGN physical properties. However, existing tools for modeling AGN light curves are not yet capable of fully leveraging the volume, cadence, and multiband nature of LSST data. We present EzTaoX, a scalable light curve modeling tool designed to take advantage of LSST's multiband observations to simultaneously characterize AGN UV/optical stochastic variability and measure interband time delays. EzTaoX achieves a speed increase of$\sim 10^2-10^4 \times$on CPUs over current tools with similar capabilities, while maintaining equal or better accuracy in recovering simulated variability properties. This performance gain enables continuum time-delay measurements for all AGNs discovered by LSST -- both in the Wide Fast Deep survey and the Deep Drilling Fields -- thereby opening new opportunities to probe AGN accretion-flow geometries. In addition, EzTaoX's multiband capability allows robust characterization of AGN stochastic variability down to hourly timescales, facilitating the identification of accreting low-mass AGNs -- such as those residing in dwarf galaxies -- through their distinctive variability signatures.

We present a multiwavelength spectroscopic survey of 23 luminous mid-infrared–selected Type-2 quasars at the redshifts of z = 0.88–3.49. The targets were selected in the SDSS Stripe 82 field based on their bright WISE 22 μm detections and extremely faint or red optical counterparts. Near-infrared (Gemini/GNIRS) and optical (Keck/LRIS and KCWI) spectroscopy confirm 23 out of 24 candidates as Type-2 quasars, including 12 objects at z > 2. The spectra exhibit strong rest-frame UV and optical emission lines (Lyα, C IV, [O III], Hα) with a wide range of line widths, indicating significant spectral diversity. Approximately one-third of the sample (8 of 23) shows broad Hα emission (FWHM >2000 km s−1) despite their Type-2 classification, while the rest have only narrow lines (FWHM <2000 km s−1) characteristic of classical obscured quasars. Notably, these broad-line Type-2 quasars share similar spectral energy distributions with the JWST-discovered “little red dot” (LRD), suggesting that our sample could be lower-redshift analogues of the heavily obscured broad-line AGNs uncovered by JWST. We also find that the [O III] λ5007 emission is relatively weak for their high bolometric luminosities, deviating from trends seen in lower-z Type-2 QSOs. A new composite spectrum for Type-2 QSOs is built using our sample. Overall, our results demonstrate that mid-IR selection efficiently uncovers diverse populations of obscured quasars and that spectroscopic follow-up is crucial for revealing their true nature. This study provides new insights into heavily obscured SMBH growth at cosmic noon and bridges the gap to the obscured AGN populations being revealed by JWST.