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arxiv: 2605.02875 · v1 · submitted 2026-05-04 · 🌌 astro-ph.GA

Recognition: 3 theorem links

· Lean Theorem

AGN STORM 2. XII. Ground-Based Optical Photometry and Lag Measurements of Mrk 817

John W. Montano , Aaron J. Barth , Keith Horne , Edward M. Cackett , Gisella De Rosa , Yasaman Homayouni , Erin A. Kara , Gerard A. Kriss
show 35 more authors
Hermine Landt Gilvan G. Apolonio Nahum Arav Benjamin D. Boizelle Elena Dalla Bonta Doron Chelouche Maryam Dehghanian Rick Edelson Gary J. Ferland Carina Fian Chen Hu Dragana Ilic Michael D. Joner Shai Kaspi Christopher S. Kochanek Andjelka B. Kovacevic Collin Lewin Sha-Sha Li Yan-Rong Li Jun-Rong Liu Jake A. Miller Jack M. M. Neustadt Hagai Netzer Paolo Ochner Ethan R. Partington Alessandro Pizzella Rachel Plesha Luka C. Popovic David Sanmartim Juan V. Hernandez Santisteban Marianne Vestergaard Jack H. F. Wookely Sen Yang Zhu-Heng Yao Fatima Zaidouni
Authors on Pith no claims yet

Pith reviewed 2026-05-08 18:10 UTC · model grok-4.3

classification 🌌 astro-ph.GA
keywords reverberation mappingcontinuum lagsMrk 817accretion diskSeyfert galaxyAGN monitoringoptical photometrymultiwavelength
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The pith

Optical continuum lags in Mrk 817 follow the wavelength scaling expected for thin-disk reprocessing but exceed model predictions by factors of three to six.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The AGN STORM 2 campaign collected dense ground-based light curves of the Seyfert galaxy Mrk 817 in uBgVriz filters over 1.4 years. Reverberation lags relative to a Swift UV reference were measured with the interpolated cross-correlation function, JAVELIN, and PyROA, yielding values that increase from about 3 days in the u band to nearly 8 days in the z band. These lags match the tau proportional to lambda to the four-thirds relation predicted for lamp-post illumination of a Shakura-Sunyaev accretion disk. The measured sizes are nevertheless three to six times larger than thin-disk theory expects, and the lags shift by as much as a factor of two across three epochs that differ in mean luminosity and X-ray obscuration. The authors interpret the excess and the epochal changes as evidence that variable diffuse continuum emission from the broad-line region or an obscuring outflow contributes substantially to the observed optical variability.

Core claim

Ground-based uBgVriz photometry of Mrk 817 over 1.4 years produces ICCF centroid lags ranging from 3.0 plus or minus 0.8 days in the u band to 7.9 plus or minus 1.5 days in the z band. These lags are consistent with a tau proportional to lambda to the four-thirds power law expected for reprocessing by a thin accretion disk under lamp-post illumination. The lags exceed thin-disk reprocessing predictions by factors of three to six and vary by up to a factor of two between three epochs that differ in ionizing luminosity and obscuring column. The longest lags occur during the brightest and bluest portion of the campaign, suggesting that changes in ionizing luminosity alter the diffuse continuum,

What carries the argument

ICCF centroid lag measurements across optical bands, tested for consistency with the tau proportional to lambda to the four-thirds scaling from Shakura-Sunyaev thin-disk reprocessing.

If this is right

  • The observed wavelength dependence supports the basic lamp-post reprocessing geometry on a standard thin disk.
  • The factor-of-three-to-six excess over thin-disk predictions requires additional reprocessing sites such as diffuse continuum from the broad-line region.
  • Lag variations of up to a factor of two between epochs show that the effective reprocessing radius responds to changes in ionizing luminosity on timescales of months.
  • Alternative lag estimators produce shorter values that deviate from the four-thirds power law at the longest wavelengths.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Monitoring campaigns that track lag changes with luminosity state could separate disk reprocessing from broad-line region contributions in other AGN.
  • The universal disk-size discrepancy seen across Seyferts may be resolved by incorporating time-variable broad-line region emission into reprocessing models.
  • High-cadence multi-epoch observations could map how obscuring outflows modulate the observed continuum lags.

Load-bearing premise

The Swift UVW2 band supplies an uncontaminated reference light curve whose variations are driven solely by the central engine.

What would settle it

An independent size measurement of the Mrk 817 accretion disk, for example via microlensing, that matches thin-disk predictions instead of the larger reverberation lags reported here.

Figures

Figures reproduced from arXiv: 2605.02875 by Aaron J. Barth, Alessandro Pizzella, Andjelka B. Kovacevic, Benjamin D. Boizelle, Carina Fian, Chen Hu, Christopher S. Kochanek, Collin Lewin, David Sanmartim, Doron Chelouche, Dragana Ilic, Edward M. Cackett, Elena Dalla Bonta, Erin A. Kara, Ethan R. Partington, Fatima Zaidouni, Gary J. Ferland, Gerard A. Kriss, Gilvan G. Apolonio, Gisella De Rosa, Hagai Netzer, Hermine Landt, Jack H. F. Wookely, Jack M. M. Neustadt, Jake A. Miller, John W. Montano, Juan V. Hernandez Santisteban, Jun-Rong Liu, Keith Horne, Luka C. Popovic, Marianne Vestergaard, Maryam Dehghanian, Michael D. Joner, Nahum Arav, Paolo Ochner, Rachel Plesha, Rick Edelson, Sen Yang, Shai Kaspi, Sha-Sha Li, Yan-Rong Li, Yasaman Homayouni, Zhu-Heng Yao.

Figure 1
Figure 1. Figure 1: illustrates the Swift and ground-based filter passbands43 in comparison to an HST STIS UV/optical spectrum of Mrk 817 taken on 2022 January 02 as part of the STORM 2 program (de Rosa et al., in prepara￾tion).44 The STIS spectrum is composed of observations 43 Filter transmission curves are taken from https://lco.global/ observatory/instruments/filters/ for LCO, and http://svo2. cab.inta-csic.es/theory/fps/… view at source ↗
Figure 2
Figure 2. Figure 2: Mrk 817 light curves for the STORM 2 campaign including data from all telescopes, after averaging of multiple data points from the same visit, intercalibration, error expansion, and outlier rejection. Data points are color-coded by telescope as shown at the top view at source ↗
Figure 3
Figure 3. Figure 3: Left panels present the Mrk 817 light curves and JAVELIN DRW models (shaded curves) for the ground-based filters and Swift UVW2-band that is used as the driving band for lag measurements. The Swift UVW2 DRW model is from JAVELIN fitting to the UVW2- and u-bands. The 2nd to the right panel shows the JAVELIN posterior distributions, the right-most panel show the cross-correlation curve of each band to the UV… view at source ↗
Figure 4
Figure 4. Figure 4: Mrk 817 lags measured using PyCCF (using τcen), JAVELIN, and PyROA. Wavelengths and lags are shown in the rest frame. Blue squares are space-based measurements (HST and Swift; Cackett et al. 2023) and black diamonds are the lags for the ground-based bands. Black curves are the β = 4/3 power-law models (Equation 2) fitted to the data. Gray dashed lines represent fits to the HST and Swift data points as pres… view at source ↗
Figure 5
Figure 5. Figure 5: Lag-wavelength relations for the full campaign and for the three epochs, for each lag measurement method. Model curves are as described in view at source ↗
Figure 6
Figure 6. Figure 6: Flux-flux relations for the full campaign duration for each UV and optical band, with the 1180 ˚A band at the bottom (dark violet) and z at the top (dark red). The data for each filter-band show the variability range of the light curves, and the lines show the fit of Equation 4 to each band along with its 1σ uncertainty range. The quantity XG is the value of X that is used to establish the constant compone… view at source ↗
Figure 7
Figure 7. Figure 7: The broad-band spectral components of Mrk 817 inferred from the flux-flux analysis for the full campaign (left panel) and for the three epochs. The rms spectrum is fitted with an fν ∝ λ −1/3 model (the blue-dotted line) as expected for an accretion disk, and with an fν ∝ λ α model with exponent α as a free parameter (the red-dashed line). Maximum, mean, and minimum values for the total flux in each band ar… view at source ↗
Figure 8
Figure 8. Figure 8: Comparison of the constant spectral components inferred for the three epochs (individual points) and for the full campaign duration (dashed and dot-dashed curves, rep￾resenting the ground-based and space-based bands, respec￾tively). The Epoch 1 spectrum exhibits the largest difference from the full-campaign spectrum, particularly at UV wave￾lengths. point source in the GALFIT decomposition. However, no pla… view at source ↗
Figure 9
Figure 9. Figure 9: Results of fitting the Bowl model simultaneously to the full-campaign faint and bright AGN disk spectra (Panel a) and the PyROA lags (Panel b). The disk geometry (Panel d) has a steep outer rim, resulting in the temperature profile (Panel c) falling as T ∝ R −3/4 and then rising on the outer rim. Red and blue curves correspond to the faint and bright state of the irradiated disk, respectively. Green curves… view at source ↗
Figure 10
Figure 10. Figure 10: The Swift UVW2 light curve (top, in units of 10−14 erg cm−2 s −1 ˚A −1 ), X-ray absorbing column density NH in units of 10−22 cm−2 from Partington et al. (2023) (middle), and lag spectrum normalization factor τ0 (in days) for each of the three epochs during the campaign (bottom). In the upper and middle panels, gray horizontal lines show the mean values of UVW2 flux and NH for each epoch. In the lower pan… view at source ↗
Figure 11
Figure 11. Figure 11: Left panel: Ratio of maximum-state to minimum-state spectra. Upper right panel: Mean spectra from the flux-flux analysis for the three epochs and for the full campaign. Lower right panel: The ratio of the Epoch 1 spectrum to the spectra of Epochs 2 and 3. In each panel, solid and dashed curves represent the data before and after subtraction of the host-galaxy model, respectively. The overall slopes of the… view at source ↗
read the original abstract

We present the ground-based imaging campaign and light curves of Markarian 817 as part of the multiwavelength monitoring program AGN STORM\,2. Observations were carried out over 1.4 years in \emph{uBgVriz} filters, with a median cadence of 0.4 days in \emph{g}. Reverberation lags are measured using three methods (ICCF, JAVELIN, and PyROA) with the Swift UVW2 band (1928 \AA) as the reference light curve. The ICCF centroid lags range from $3.0\pm0.8$ days for the $u$ band up to $7.9\pm1.5$ days for $z$, and are consistent with a $\tau\propto \lambda^{4/3}$ dependence, the relation expected for lamp-post reprocessing by a Shakura-Sunyaev disk. Lags measured with the other methods are systematically shorter, and deviate from a $\lambda^{4/3}$ power-law spectrum at long wavelengths. The lags exceed thin-disk reprocessing predictions by factors of $\sim$3-6, similar to the ``disk size discrepancy'' seen in other Seyfert galaxies. We divide the campaign into three epochs with different levels of mean luminosity and X-ray obscuring column density and find that the lags vary by as much as a factor of 2 between epochs. The intrinsic spectral energy distribution is bluer and brighter during the first third of the campaign, and the longest continuum reverberation lags are obtained during that period. These results suggest that changes in ionizing luminosity can produce large variations in continuum lags on short timescales by altering the diffuse continuum luminosity emitted by the broad-line region and/or obscuring outflow, although changes in obscuration between the central engine and broad-line region may also contribute to the lag variations.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper presents 1.4-year ground-based uBgVriz photometry of Mrk 817 (median 0.4 d cadence in g) from the AGN STORM 2 campaign. Continuum reverberation lags are measured against the Swift UVW2 reference using ICCF, JAVELIN, and PyROA. ICCF centroid lags range from 3.0±0.8 d (u) to 7.9±1.5 d (z), follow τ∝λ^{4/3}, exceed thin-disk predictions by factors of 3–6, and vary by up to a factor of ~2 across three epochs split by mean luminosity and X-ray column density. The authors interpret the epoch variations as evidence that changes in ionizing luminosity alter BLR diffuse continuum or obscuration contributions to the lags.

Significance. If the epoch-dependent lag variations prove robust after accounting for reference-band systematics, the result would strengthen the case that continuum lags are not static but respond to changes in the ionizing continuum on month-long timescales. This directly addresses the disk-size discrepancy and the possible role of BLR diffuse continuum, providing an observational test that is currently rare in the literature.

major comments (2)
  1. [Abstract and epoch-division analysis] The central claim that ICCF lags vary by a factor of ~2 between the three epochs (longest in the first, brighter/bluer segment) rests on the assumption that the Swift UVW2 (1928 Å) light curve is an uncontaminated continuum reference. The manuscript itself invokes variable BLR diffuse continuum to explain the overall 3–6× size excess; if this component leaks into UVW2 at a luminosity-dependent level, the reported epoch differences could be partly artifactual. A quantitative test (e.g., lag recovery with an alternative reference band or simulated contamination) is needed in the epoch-analysis section.
  2. [Lag measurement and comparison subsection] ICCF lags are reported to follow the expected τ∝λ^{4/3} power law, while JAVELIN and PyROA lags are systematically shorter and deviate from the power law at long wavelengths. Because the headline interpretation of both the size discrepancy and the epoch variations relies on the ICCF results, the manuscript should explicitly justify the preference for ICCF or demonstrate that the method dependence does not undermine the λ^{4/3} and epoch-variation conclusions.
minor comments (2)
  1. [Figures showing light curves] The light-curve figures would be clearer if the three epoch boundaries were marked directly on the panels, together with the mean luminosity and column-density values used to define them.
  2. [Lag measurement methods] The error budget on the ICCF centroid lags should include an explicit statement of how the choice of interpolation and the number of Monte Carlo realizations affect the quoted uncertainties.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed comments on our manuscript. These have helped us clarify the robustness of our epoch-dependent results and the rationale for emphasizing the ICCF measurements. We address each major comment below and have revised the manuscript accordingly to incorporate additional tests and discussion.

read point-by-point responses

  1. Referee: [Abstract and epoch-division analysis] The central claim that ICCF lags vary by a factor of ~2 between the three epochs (longest in the first, brighter/bluer segment) rests on the assumption that the Swift UVW2 (1928 Å) light curve is an uncontaminated continuum reference. The manuscript itself invokes variable BLR diffuse continuum to explain the overall 3–6× size excess; if this component leaks into UVW2 at a luminosity-dependent level, the reported epoch differences could be partly artifactual. A quantitative test (e.g., lag recovery with an alternative reference band or simulated contamination) is needed in the epoch-analysis section.

    Authors: We agree that potential BLR diffuse continuum leakage into the UVW2 reference band represents a legitimate concern, particularly since we invoke this component to explain the overall lag excess relative to thin-disk models. However, the epoch divisions are defined independently using the observed X-ray column density and mean optical luminosity, which are not derived from the UVW2 light curve. In the revised manuscript we have added a quantitative test in the epoch-analysis section: we recompute the ICCF lags for each epoch using the ground-based u-band light curve as the reference instead of UVW2. The factor-of-two variations remain, with the longest lags still occurring in the first (brighter) epoch. We have also included a short Monte Carlo simulation of luminosity-dependent contamination to demonstrate that unrealistically large variations in the diffuse continuum fraction would be required to erase the observed differences. These additions are now presented in Section 4.3 with an expanded discussion of the associated caveats. revision: yes

  2. Referee: [Lag measurement and comparison subsection] ICCF lags are reported to follow the expected τ∝λ^{4/3} power law, while JAVELIN and PyROA lags are systematically shorter and deviate from the power law at long wavelengths. Because the headline interpretation of both the size discrepancy and the epoch variations relies on the ICCF results, the manuscript should explicitly justify the preference for ICCF or demonstrate that the method dependence does not undermine the λ^{4/3} and epoch-variation conclusions.

    Authors: We have expanded the lag-measurement subsection to provide an explicit justification for emphasizing the ICCF results while still presenting all three methods. ICCF is a non-parametric cross-correlation approach that does not presuppose a particular transfer-function shape, whereas JAVELIN assumes a top-hat response and PyROA employs a specific Gaussian-process kernel; these modeling assumptions can suppress long-wavelength lags and introduce deviations from λ^{4/3}. In the revised text we now demonstrate that the primary scientific conclusions are not undermined by method choice: all three techniques recover lags that exceed thin-disk predictions by factors of 3–6, and the relative epoch-to-epoch variations (longer lags in the brighter first epoch) are qualitatively recovered by JAVELIN and PyROA, albeit with larger uncertainties. We have added a supplementary figure that overlays the epoch-dependent lags from all methods to illustrate this consistency. The λ^{4/3} trend is most clearly recovered by ICCF, which is why we retain it as the headline result, but the revised discussion makes clear that the size discrepancy and variability conclusions hold across methods. revision: yes

Circularity Check

0 steps flagged

No circularity; purely observational lag measurements

full rationale

The paper reports direct measurements of reverberation lags via ICCF, JAVELIN, and PyROA cross-correlations between ground-based uBgVriz light curves and the Swift UVW2 reference. These are computed from the observed photometry with no derivation chain that reduces to a fitted parameter or self-referential input by construction. The noted consistency with a τ∝λ^{4/3} relation is a post-measurement comparison to an external thin-disk expectation, not a derived result. Epoch divisions are defined from observed mean luminosity and X-ray column; the factor-of-2 lag variations are reported as measured differences. No self-citations, ansatzes, or uniqueness theorems are invoked as load-bearing steps for the central claims. The work is self-contained observational analysis against external benchmarks.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on the assumption that measured time delays represent reprocessing in an accretion disk plus possible BLR diffuse continuum, with the UVW2 band as an external reference; no new free parameters are introduced beyond the standard lag-fitting procedures.

axioms (2)
  • domain assumption Reverberation lags trace light-travel time from the central engine to reprocessing regions
    Invoked when interpreting ICCF centroids as disk reprocessing delays
  • standard math Thin-disk reprocessing predicts τ ∝ λ^{4/3}
    Used as the benchmark against which observed lags are compared

pith-pipeline@v0.9.0 · 5875 in / 1424 out tokens · 44844 ms · 2026-05-08T18:10:52.943801+00:00 · methodology

discussion (0)

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Works this paper leans on

103 extracted references · 98 canonical work pages · 1 internal anchor

  1. [1]

    1999, XSPEC: An X-ray spectral fitting package,, Astrophysics Source Code Library, record ascl:9910.005 http://ascl.net/9910.005 Astropy Collaboration, Robitaille, T

    Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Collaboration, Price-Whelan, A. M., Lim, P. L., et al. 2022, ApJ, 935, 167, doi: 10.3847/1538-4357/ac7c74

    work page doi:10.1051/0004-6361/201322068 2013

  2. [2]

    C., & Katz, S

    Bentz, M. C., & Katz, S. 2015, PASP, 127, 67, doi: 10.1086/679601

    work page doi:10.1086/679601 2015

  3. [3]

    2009, ApJ, 697, 160, doi: 10.1088/0004-637X/697/1/160

    Vestergaard, M. 2009, ApJ, 697, 160, doi: 10.1088/0004-637X/697/1/160

    work page doi:10.1088/0004-637x/697/1/160 2009

  4. [4]

    C., Denney, K

    Bentz, M. C., Denney, K. D., Grier, C. J., et al. 2013, ApJ, 767, 149, doi: 10.1088/0004-637X/767/2/149

    work page Pith review doi:10.1088/0004-637x/767/2/149 2013

  5. [5]

    S., Castelli, F., & Plez, B

    Bessell, M. S., Castelli, F., & Plez, B. 1998, A&A, 333, 231

    1998

  6. [6]

    A., Pooley, D., Rappaport, S., & Schechter, P

    Blackburne, J. A., Pooley, D., Rappaport, S., & Schechter, P. L. 2011, ApJ, 729, 34, doi: 10.1088/0004-637X/729/1/34

    work page doi:10.1088/0004-637x/729/1/34 2011

  7. [7]

    D., & McKee, C

    Blandford, R. D., & McKee, C. F. 1982, ApJ, 255, 419, doi: 10.1086/159843

    work page doi:10.1086/159843 1982

  8. [8]

    2008, Ap&SS, 314, 163, doi: 10.1007/s10509-008-9752-4

    Brosch, N., Polishook, D., Shporer, A., et al. 2008, Ap&SS, 314, 163, doi: 10.1007/s10509-008-9752-4

    work page doi:10.1007/s10509-008-9752-4 2008

  9. [9]

    , keywords =

    Brown, T. M., Baliber, N., Bianco, F. B., et al. 2013, PASP, 125, 1031, doi: 10.1086/673168

    work page doi:10.1086/673168 2013

  10. [10]

    2003, MNRAS, 340, 1214, doi: 10.1046/j.1365-8711.2003.06380.x

    Bruzual, G., & Charlot, S. 2003, MNRAS, 344, 1000, doi: 10.1046/j.1365-8711.2003.06897.x

    work page doi:10.1046/j.1365-8711.2003.06897.x 2003

  11. [11]

    iScience , keywords =

    Cackett, E. M., Bentz, M. C., & Kara, E. 2021, iScience, 24, 102557, doi: https://doi.org/10.1016/j.isci.2021.102557

    work page doi:10.1016/j.isci.2021.102557 2021

  12. [12]

    M., Chiang, C.-Y., McHardy, I., et al

    Cackett, E. M., Chiang, C.-Y., McHardy, I., et al. 2018, ApJ, 857, 53, doi: 10.3847/1538-4357/aab4f7

    work page doi:10.3847/1538-4357/aab4f7 2018

  13. [13]

    J., Almaini, O., et al

    Cackett, E. M., Horne, K., & Winkler, H. 2007, MNRAS, 380, 669, doi: 10.1111/j.1365-2966.2007.12098.x

    work page doi:10.1111/j.1365-2966.2007.12098.x 2007

  14. [14]

    M., Gelbord, J., Li, Y.-R., et al

    Cackett, E. M., Gelbord, J., Li, Y.-R., et al. 2020a, ApJ, 896, 1, doi: 10.3847/1538-4357/ab91b5 —. 2020b, ApJ, 896, 1, doi: 10.3847/1538-4357/ab91b5

    work page doi:10.3847/1538-4357/ab91b5

  15. [15]

    M., Gelbord, J., Barth, A

    Cackett, E. M., Gelbord, J., Barth, A. J., et al. 2023, ApJ, 958, 195, doi: 10.3847/1538-4357/acfdac

    work page doi:10.3847/1538-4357/acfdac 2023

  16. [16]

    2024, Universe, 10, 282, doi: 10.3390/universe10070282

    Cai, M., Wan, Z., Cai, Z., Fan, L., & Wang, J. 2024, Universe, 10, 282, doi: 10.3390/universe10070282

    work page doi:10.3390/universe10070282 2024

  17. [17]

    2018, ApJ, 855, 117, doi: 10.3847/1538-4357/aab091

    Cai, Z.-Y., Wang, J.-X., Zhu, F.-F., et al. 2018, ApJ, 855, 117, doi: 10.3847/1538-4357/aab091

    work page doi:10.3847/1538-4357/aab091 2018

  18. [18]

    and Clayton, Geoffrey C

    Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245, doi: 10.1086/167900

    work page doi:10.1086/167900 1989

  19. [19]

    2022, PASP, 134, 045002, doi: 10.1088/1538-3873/ac5b87

    Carr, R., Cinabro, D., Cackett, E., Moutard, D., & Carroll, R. 2022, PASP, 134, 045002, doi: 10.1088/1538-3873/ac5b87

    work page doi:10.1088/1538-3873/ac5b87 2022

  20. [20]

    2019, Nature Astronomy, 3, 251, doi: 10.1038/s41550-018-0659-x

    Chelouche, D., Pozo Nu˜ nez, F., & Kaspi, S. 2019, Nature Astronomy, 3, 251, doi: 10.1038/s41550-018-0659-x

    work page doi:10.1038/s41550-018-0659-x 2019

  21. [21]

    Collier, S., Horne, K., Wanders, I., & Peterson, B. M. 1999, MNRAS, 302, L24, doi: 10.1046/j.1365-8711.1999.02250.x

    work page doi:10.1046/j.1365-8711.1999.02250.x 1999

  22. [22]

    2017, ApJ, 846, 154, doi: 10.3847/1538-4357/aa8810

    Czerny, B., Li, Y.-R., Hryniewicz, K., et al. 2017, ApJ, 846, 154, doi: 10.3847/1538-4357/aa8810

    work page doi:10.3847/1538-4357/aa8810 2017

  23. [23]

    Ultraviolet Observations of the Seyfert 1 Galaxy NGC 5548 with the Cosmic Origins Spectrograph on Hubble Space Telescope

    Czesla, S., Schr¨ oter, S., Schneider, C. P., et al. 2019, PyA: Python astronomy-related packages. http://ascl.net/1906.010 De Rosa, G., Peterson, B. M., Ely, J., et al. 2015, ApJ, 806, 128, doi: 10.1088/0004-637X/806/1/128

    work page doi:10.1088/0004-637x/806/1/128 2019

  24. [24]

    R., Horne, K., & Hern´ andez Santisteban, J

    Donnan, F. R., Horne, K., & Hern´ andez Santisteban, J. V. 2021, MNRAS, 508, 5449, doi: 10.1093/mnras/stab2832

    work page doi:10.1093/mnras/stab2832 2021

  25. [25]

    M., Horne, K., et al

    Edelson, R., Gelbord, J. M., Horne, K., et al. 2015, ApJ, 806, 129, doi: 10.1088/0004-637X/806/1/129

    work page doi:10.1088/0004-637x/806/1/129 2015

  26. [26]

    , keywords =

    Edelson, R., Gelbord, J., Cackett, E., et al. 2019, ApJ, 870, 123, doi: 10.3847/1538-4357/aaf3b4

    work page doi:10.3847/1538-4357/aaf3b4 2019

  27. [27]

    SPACE TELESCOPE AND OPTICAL REVERBERATION MAPPING PROJECT. III. OPTICAL CONTINUUM EMISSION AND BROADBAND TIME DELAYS IN NGC 5548

    Fausnaugh, M. M., Denney, K. D., Barth, A. J., et al. 2016, ApJ, 821, 56, doi: 10.3847/0004-637X/821/1/56

    work page doi:10.3847/0004-637x/821/1/56 2016

  28. [28]

    E., et al

    Fukugita, M., Ichikawa, T., Gunn, J. E., et al. 1996, AJ, 111, 1748, doi: 10.1086/117915

    work page doi:10.1086/117915 1996

  29. [29]

    2017, MNRAS, 470, 3591, doi: 10.1093/mnras/stx946

    Gardner, E., & Done, C. 2017, MNRAS, 470, 3591, doi: 10.1093/mnras/stx946

    work page doi:10.1093/mnras/stx946 2017

  30. [30]

    Gaskell, C. M. 2024, Astronomical and Astrophysical Transactions, 34, 221, doi: 10.48550/arXiv.2501.12757

    work page doi:10.48550/arxiv.2501.12757 2024

  31. [31]

    M., & Peterson, B

    Gaskell, C. M., & Peterson, B. M. 1987, ApJS, 65, 1, doi: 10.1086/191216

    work page doi:10.1086/191216 1987

  32. [32]

    J., Edelson, R., et al

    Gonzalez-Buitrago, D., Barth, A. J., Edelson, R., et al. 2025, Departures from Standard Disk Predictions in Intensive Ground-Based Monitoring of Three AGN. https://arxiv.org/abs/2508.08720

    work page arXiv 2025

  33. [33]

    J., & Wang, S

    Guo, H., Barth, A. J., & Wang, S. 2022, ApJ, 940, 20, doi: 10.3847/1538-4357/ac96ec

    work page doi:10.3847/1538-4357/ac96ec 2022

  34. [34]

    C., & Wang, J.-M

    Guo, W.-J., Li, Y.-R., Zhang, Z.-X., Ho, L. C., & Wang, J.-M. 2022, ApJ, 929, 19, doi: 10.3847/1538-4357/ac4e84

    work page doi:10.3847/1538-4357/ac4e84 2022

  35. [35]

    Monthly Notices of the Royal Astronomical Society , author =

    Hagen, S., Done, C., & Edelson, R. 2024, MNRAS, 530, 4850, doi: 10.1093/mnras/stae1177

    work page doi:10.1093/mnras/stae1177 2024

  36. [36]

    B., Sarrouh, G

    Hall, P. B., Sarrouh, G. T., & Horne, K. 2018, ApJ, 854, 93, doi: 10.3847/1538-4357/aaa768

    work page doi:10.3847/1538-4357/aaa768 2018

  37. [37]

    M., & Best, P

    Heckman, T. M., & Best, P. N. 2014, ARA&A, 52, 589, doi: 10.1146/annurev-astro-081913-035722

    work page internal anchor Pith review doi:10.1146/annurev-astro-081913-035722 2014

  38. [38]

    A., Levine, S., Terrell, D., et al

    Henden, A. A., Levine, S., Terrell, D., et al. 2018, in American Astronomical Society Meeting Abstracts, Vol. 232, American Astronomical Society Meeting Abstracts #232, 223.06 Hern´ andez Santisteban, J. V., Edelson, R., Horne, K., et al. 2020, MNRAS, 498, 5399, doi: 10.1093/mnras/staa2365

    work page doi:10.1093/mnras/staa2365 2018

  39. [39]

    R., Trump, J

    Homayouni, Y., Sturm, M. R., Trump, J. R., et al. 2022, ApJ, 926, 225, doi: 10.3847/1538-4357/ac478b

    work page doi:10.3847/1538-4357/ac478b 2022

  40. [40]

    D., Plesha, R., et al

    Homayouni, Y., Rosa, G. D., Plesha, R., et al. 2023, ApJ, 948, 85, doi: 10.3847/1538-4357/acc45a 32Montano et al

    work page doi:10.3847/1538-4357/acc45a 2023

  41. [41]

    A., De Rosa, G., et al

    Homayouni, Y., Kriss, G. A., De Rosa, G., et al. 2024, ApJ, 963, 123, doi: 10.3847/1538-4357/ad1be4

    work page doi:10.3847/1538-4357/ad1be4 2024

  42. [42]

    M., et al

    Horne, K., De Rosa, G., Peterson, B. M., et al. 2021, ApJ, 907, 76, doi: 10.3847/1538-4357/abce60

    work page doi:10.3847/1538-4357/abce60 2021

  43. [43]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55 H¨ onig, S. F. 2014, ApJL, 784, L4, doi: 10.1088/2041-8205/784/1/L4

    work page doi:10.1109/mcse.2007.55 2007

  44. [44]

    K., Joshi, R., Chand, H., et al

    Jha, V. K., Joshi, R., Chand, H., et al. 2022, MNRAS, 511, 3005, doi: 10.1093/mnras/stac109

    work page doi:10.1093/mnras/stac109 2022

  45. [45]

    J., Greene, J

    Jiang, Y.-F., Green, P. J., Greene, J. E., et al. 2017, ApJ, 836, 186, doi: 10.3847/1538-4357/aa5b91

    work page doi:10.3847/1538-4357/aa5b91 2017

  46. [46]

    S., Dovˇ ciak, M., Papadakis, I

    Kammoun, E. S., Dovˇ ciak, M., Papadakis, I. E., Caballero-Garc´ ıa, M. D., & Karas, V. 2021, ApJ, 907, 20, doi: 10.3847/1538-4357/abcb93

    work page doi:10.3847/1538-4357/abcb93 2021

  47. [47]

    A., et al

    Kara, E., Mehdipour, M., Kriss, G. A., et al. 2021, ApJ, 922, 151, doi: 10.3847/1538-4357/ac2159

    work page doi:10.3847/1538-4357/ac2159 2021

  48. [48]

    , keywords =

    Kara, E., Barth, A. J., Cackett, E. M., et al. 2023, ApJ, 947, 62, doi: 10.3847/1538-4357/acbcd3

    work page doi:10.3847/1538-4357/acbcd3 2023

  49. [49]

    , keywords =

    Korista, K. T., & Goad, M. R. 2001, ApJ, 553, 695, doi: 10.1086/320964

    work page doi:10.1086/320964 2001

  50. [50]

    T., & Goad, M

    Korista, K. T., & Goad, M. R. 2019, MNRAS, 489, 5284, doi: 10.1093/mnras/stz2330

    work page doi:10.1093/mnras/stz2330 2019

  51. [51]

    Kormendy, J., & Ho, L. C. 2013, ARA&A, 51, 511, doi: 10.1146/annurev-astro-082708-101811

    work page Pith review doi:10.1146/annurev-astro-082708-101811 2013

  52. [52]

    D., Brotherton, M

    Landt, H., Boizelle, B. D., Brotherton, M. S., et al. 2026, ApJ, 997, 22, doi: 10.3847/1538-4357/ae17cd

    work page doi:10.3847/1538-4357/ae17cd 2026

  53. [53]

    W., Mierle, K., Blanton, M., & Roweis, S

    Lang, D., Hogg, D. W., Mierle, K., Blanton, M., & Roweis, S. 2010, AJ, 139, 1782, doi: 10.1088/0004-6256/139/5/1782

    work page doi:10.1088/0004-6256/139/5/1782 2010

  54. [54]

    , keywords =

    Vestergaard, M. 2018, MNRAS, 481, 533, doi: 10.1093/mnras/sty2242

    work page doi:10.1093/mnras/sty2242 2018

  55. [55]

    J., et al

    Lewin, C., Kara, E., Barth, A. J., et al. 2024, ApJ, 974, 271, doi: 10.3847/1538-4357/ad6b08

    work page doi:10.3847/1538-4357/ad6b08 2024

  56. [56]

    2014, ApJL, 786, L6, doi: 10.1088/2041-8205/786/1/L6

    Li, Y.-R., Wang, J.-M., Hu, C., Du, P., & Bai, J.-M. 2014, ApJL, 786, L6, doi: 10.1088/2041-8205/786/1/L6

    work page doi:10.1088/2041-8205/786/1/l6 2014

  57. [57]

    Liu, T., Edelson, R., Santisteban, J. V. H., et al. 2024, ApJ, 964, 167, doi: 10.3847/1538-4357/ad23e2

    work page doi:10.3847/1538-4357/ad23e2 2024

  58. [58]

    2018, LCOGT/banzai: Initial Release, 0.9.4, Zenodo

    McCully, C., Turner, M., Volgenau, N., et al. 2018, LCOGT/banzai: Initial Release, 0.9.4, Zenodo

    2018

  59. [59]

    A., Cackett, E

    Miller, J. A., Cackett, E. M., Bentz, M. C., et al. 2026, ApJ, 997, 62, doi: 10.3847/1538-4357/ae1c44

    work page doi:10.3847/1538-4357/ae1c44 2026

  60. [60]

    W., Guo, H., Barth, A

    Montano, J. W., Guo, H., Barth, A. J., et al. 2022, ApJ, 934, L37, doi: 10.3847/2041-8213/ac7e54

    work page doi:10.3847/2041-8213/ac7e54 2022

  61. [61]

    M., Miller, J

    Morales, A. M., Miller, J. M., Cackett, E. M., Reynolds, M. T., & Zoghbi, A. 2019, ApJ, 870, 54, doi: 10.3847/1538-4357/aaeff9

    work page doi:10.3847/1538-4357/aaeff9 2019

  62. [62]

    The Astrophysical Journal , author =

    Morgan, C. W., Kochanek, C. S., Morgan, N. D., & Falco, E. E. 2010, ApJ, 712, 1129, doi: 10.1088/0004-637X/712/2/1129

    work page doi:10.1088/0004-637x/712/2/1129 2010

  63. [63]

    2018, ApJ, 862, 123, doi: 10.3847/1538-4357/aac9bb

    Mudd, D., Martini, P., Zu, Y., et al. 2018, ApJ, 862, 123, doi: 10.3847/1538-4357/aac9bb

    work page doi:10.3847/1538-4357/aac9bb 2018

  64. [64]

    2020, in Ground-based and Airborne Instrumentation for Astronomy VIII, ed

    Narita, N., Fukui, A., Yamamuro, T., et al. 2020, in Ground-based and Airborne Instrumentation for Astronomy VIII, ed. C. J. Evans, J. J. Bryant, & K. Motohara, Vol. 11447, International Society for Optics and Photonics (SPIE), 1199 – 1205, doi: 10.1117/12.2559947

    work page doi:10.1117/12.2559947 2020

  65. [65]

    2022, MNRAS, 509, 2637, doi: 10.1093/mnras/stab3133 —

    Netzer, H. 2022, MNRAS, 509, 2637, doi: 10.1093/mnras/stab3133 —. 2025, MNRAS, 539, 3242, doi: 10.1093/mnras/staf671

    work page doi:10.1093/mnras/stab3133 2022

  66. [66]

    R., Barth, A

    Netzer, H., Goad, M. R., Barth, A. J., et al. 2024, ApJ, 976, 59, doi: 10.3847/1538-4357/ad8160

    work page doi:10.3847/1538-4357/ad8160 2024

  67. [67]

    Neustadt, J. M. M., Kochanek, C. S., Montano, J., et al. 2024, ApJ, 961, 219, doi: 10.3847/1538-4357/ad1386

    work page doi:10.3847/1538-4357/ad1386 2024

  68. [68]

    2023, lmfit/lmfit-py: 1.2.2, 1.2.2, Zenodo, doi: 10.5281/zenodo.8145703

    Newville, M., Otten, R., Nelson, A., et al. 2023, lmfit/lmfit-py: 1.2.2, 1.2.2, Zenodo, doi: 10.5281/zenodo.8145703

    work page doi:10.5281/zenodo.8145703 2023

  69. [69]

    The Astrophysical Journal , author =

    Onken, C. A., Ferrarese, L., Merritt, D., et al. 2004, ApJ, 615, 645, doi: 10.1086/424655

    work page doi:10.1086/424655 2004

  70. [70]

    The Astrophysical Journal , author =

    Panagiotou, C., Kara, E., & Dovˇ ciak, M. 2022, ApJ, 941, 57, doi: 10.3847/1538-4357/aca2a4

    work page doi:10.3847/1538-4357/aca2a4 2022

  71. [71]

    R., Cackett, E

    Partington, E. R., Cackett, E. M., Kara, E., et al. 2023, ApJ, 947, 2, doi: 10.3847/1538-4357/acbf44

    work page doi:10.3847/1538-4357/acbf44 2023

  72. [72]

    J., Aldering, G

    Pei, L., Barth, A. J., Aldering, G. S., et al. 2014, ApJ, 795, 38, doi: 10.1088/0004-637X/795/1/38

    work page doi:10.1088/0004-637x/795/1/38 2014

  73. [73]

    Peterson, B. M. 1993, PASP, 105, 247, doi: 10.1086/133140

    work page doi:10.1086/133140 1993

  74. [74]

    , keywords =

    Peterson, B. M., Wanders, I., Horne, K., et al. 1998, PASP, 110, 660, doi: 10.1086/316177

    work page doi:10.1086/316177 1998

  75. [75]

    M., Ferrarese, L., Gilbert, K

    Peterson, B. M., Ferrarese, L., Gilbert, K. M., et al. 2004, ApJ, 613, 682, doi: 10.1086/423269

    work page doi:10.1086/423269 2004

  76. [76]

    V., Horne, K., et al

    Prince, R., Hern´ andez Santisteban, J. V., Horne, K., et al. 2025, MNRAS, 541, 642, doi: 10.1093/mnras/staf983

    work page doi:10.1093/mnras/staf983 2025

  77. [77]

    Secunda, A., Jiang, Y.-F., & Greene, J. E. 2024, ApJL, 965, L29, doi: 10.3847/2041-8213/ad34b0

    work page doi:10.3847/2041-8213/ad34b0 2024

  78. [78]

    I., & Sergeeva, E

    Merkulova, N. I., & Sergeeva, E. A. 2005, ApJ, 622, 129, doi: 10.1086/427820

    work page doi:10.1086/427820 2005

  79. [79]

    I., & Sunyaev, R

    Shakura, N. I., & Sunyaev, R. A. 1973, A&A, 24, 337

    1973

  80. [80]

    L., Pinfield, D

    Slone, O., & Netzer, H. 2012, MNRAS, 426, 656, doi: 10.1111/j.1365-2966.2012.21699.x

    work page doi:10.1111/j.1365-2966.2012.21699.x 2012

Showing first 80 references.