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Record W4399676696 · doi:10.1093/mnras/stae1353

Correction to: Characterizing X-ray, UV, and optical variability in NGC 6814 using high-cadence <i>Swift</i> observations from a 2022 monitoring campaign

2024· article· en· W4399676696 on OpenAlexaff
A G Gonzalez, Luigi Gallo, J. M. Mïller, Elias Kammoun, Akshay Ghosh, B A Pottie

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsSwiftPhysicsCadenceAstrophysicsAstronomy

Abstract

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We recently published the paper ‘Characterizing X-ray, UV, and optical variability in NGC 6814 using high-cadence Swift observations from a 2022 monitoring campaign’ in Monthly Notices of the Royal Astronomical Society 527, 5569–5579 (2024). We have since discovered that an outdated Calibration Database (CALDB) version was erroneously used to process the Swift UVOT data in that work. We have reprocessed those data using the most recent CALDB version (20240201) and find that the original UV flux densities are significantly larger than those obtained with the new CALDB. Fortunately, the variability products (i.e. fractional variability, structure function, and interpolated cross-correlation function) of sections 3.1−3.3 remain consistent within the uncertainties reported in the original work due to the normalization processes that are performed when computing each product. section 3.4 (i.e. flux-flux analysis), however, changes, as do the related Discussion points and Conclusions that are based on that result. We present the updated results and interpretations using the reprocessed data below. We performed the flux-flux analysis presented in section 3.4 of Gonzalez et al. (2024) following the exact same procedure, changing only the input light curves to the reprocessed ones. The updated results are shown in Fig. 1 and Table 1, where it can be seen that the UV fit parameters for the average flux [A(λ)] and RMS [R(λ)], and consequently computed intrinsic AGN variability spectrum [D(λ)] and constant (i.e. host galaxy) component [G(λ)], are ∼1.6 times smaller on average than those in the original work. Now, the intrinsic AGN variability spectrum does not differ significantly from the expected Fν ∝ λ−1/3 of a standard accretion disc, except for in the U band. Fitting of the host galaxy component does not change due to the minimal effect of the updated CALDB version on the optical results, which dominate that fit. Left: Flux–flux plots for all de-reddened and filtered UVOT flux density light curves. Colour-coded solid lines represent the best-fitting lines Fν(λ, t) = A(λ) + R(λ)X(t), with fit parameters given in Table 1. The vertical grey dashed line represents the W2 zero crossing point, which is used to estimate the minimum host galaxy contribution in each other band. Right: Measured total [A(λ)] and RMS [R(λ)] spectra alongside the computed AGN [D(λ)] and host galaxy [G(λ)] spectra based on the best-fitting lines to the flux–flux plots in the left panel (all values given in Table 1). The expected accretion disc spectrum of Fν ∝ λ−1/3 is plotted alongside the RMS and AGN spectra as the dashed dark grey curves and has been scaled by the V-band flux of each. The Sc spiral template is shown as the solid light grey curve. Flux–flux fit parameters for the average [A(λ)] and RMS [R(λ)] as well as computed values to isolate the AGN [D(λ)] and host galaxy [G(λ)] components, in units of mJy. The fit to all UVOT light curves yields |$\chi ^{2}_{\nu }=1.22$|⁠. Flux–flux fit parameters for the average [A(λ)] and RMS [R(λ)] as well as computed values to isolate the AGN [D(λ)] and host galaxy [G(λ)] components, in units of mJy. The fit to all UVOT light curves yields |$\chi ^{2}_{\nu }=1.22$|⁠. We jointly fit the updated intrinsic AGN variability spectrum and time-averaged X-ray spectrum from the original work using kynsed (Dovčiak et al. 2022) in xspec (Arnaud 1996) following the exact same procedure outlined in the Discussion of Gonzalez et al. (2024). While we fixed the black hole mass to MBH = 1.85 × 107 M⊙ in the original work, here we left it free to vary when fitting in order to achieve realistic X-ray luminosities that did not exceed the total disc luminosity. We note that we kept the colour-temperature correction factor fixed to fcol = 1.7 as we found it to provide the best fit to the data, which was determined by following the procedure in appendix B of the original work. Moreover, when using the prescription of colour-temperature correction factor described by Done et al. (2012) the fit became worse at the >99 per cent confidence level. We were able to adequately fit the updated AGN SED (excluding the U band), finding a black hole mass of MBH = (9 ± 1) × 106 M⊙, Eddington accretion rate of |$\dot{m}_{\mathrm{Edd}}=\dot{M}/\dot{M}_{\mathrm{Edd}}=0.035^{+0.019}_{-0.006}$| where |$\dot{M}$| and |$\dot{M}_{\mathrm{Edd}}$| are the accretion rate and Eddington rate, and outer disc radius of Rout ≳ 1800 rg as well as neutral, partially covering X-ray absorption consistent with what was reported in the original work. For these best-fitting parameters, we find that the dust sublimation radius (Baskin & Laor 2018) is Rdust ≈ 1350 rg and that the self-gravity radius (Laor & Netzer 1989) is Rsg ≈ 580 rg, which may suggest the former as a possible truncation mechanism of the outer accretion disc. The un-fit U band data exceed the predicted model flux by ∼20 per cent. Although the inter-band continuum lags found with the reprocessed data are consistent with those in the original work, we computed the predicted model lags using kynxiltr (Kammoun et al. 2023) following the exact same procedure outlined in the Discussion of Gonzalez et al. (2024) now using MBH = 9 × 106 M⊙ as the input black hole mass. We find that with this lower mass |$\dot{m}_{\mathrm{Edd}}=4^{+9}_{-3}$| and Rout = 2800 ± 800 rg best fit the lags when excluding the U band, parameters which yield Rdust ≈ 5370 rg and Rsg ≈ 4750 rg, both of which are too large to explain the required outer disc truncation. The un-fit U band data exceed the predicted model lag by ∼50 per cent. The results of both fitting procedures are shown in Fig. 2, where we have also plotted the corresponding inter-band continuum lag and AGN SED model predictions as in the Discussion of Gonzalez et al. (2024). The results obtained using the reprocessed data make it clear that no extreme outer disc truncation is required by the data, as was reported in the original work. However, it remains that a standard accretion disc does not provide a self-consistent description of both the AGN SED and inter-band continuum lags. A significant contribution from the diffuse continuum emission in NGC 6814 seems a plausible explanation for the observed discrepancies. The lag–wavelength spectrum (top left) and AGN SED (top right; observed as dotted curves, intrinsic as solid curves) are shown as the black data points. Each panel in the top row displays the results from individually fitting the lag–wavelength spectrum (red) and SED (blue) with kynxiltr and kynsed, respectively. The relevant colour-coded fit statistics when fitting filled data points are shown in each panel of the top row, where the values in parentheses include the excluded empty data points in each panel. For the SED fits, the fit statistics for the UV/optical (χ2) and X-ray (C) data are shown separately, near the corresponding data. The bottom two rows display the colour-coded best-fitting model residuals corresponding to the SED and lag fits, respectively. The authors would like to thank Hannah Cornfield and Keith Horne for contacting us about the UV flux discrepancy when using the updated CALDB. The data presented here are publicly available through the NASA HEASARC Archive (https://heasarc.gsfc.nasa.gov/docs/archive.html) and Swift observatory (https://www.swift.ac.uk/index.php) websites. The reprocessed light curves are available via the corresponding author (AGG) upon reasonable request.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.006
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0960.048

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.227
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2024
Admission routes1
Has abstractyes

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