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Enregistrement 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 sur OpenAlexaff
A G Gonzalez, Luigi Gallo, J. M. Mïller, Elias Kammoun, Akshay Ghosh, B A Pottie

Notice bibliographique

RevueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Langueen
DomainePhysics and Astronomy
ThématiqueAstrophysical Phenomena and Observations
Établissements canadiensSaint Mary's University
Organismes subventionnairesnon disponible
Mots-clésSwiftPhysicsCadenceAstrophysicsAstronomy

Résumé

récupéré en direct d'OpenAlex

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 We have since discovered that an outdated Calibration Database (CALDB) version was erroneously used to process the Swift UVOT data in that work.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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,022
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,096
Score d'incertitude au seuil0,321

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,022
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0070,006
Études des sciences et des technologies0,0020,001
Communication savante0,0030,002
Science ouverte0,0030,003
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,0960,048

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,227
Écart entre enseignants0,211 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2024
Routes d'admission1
Résumé présentoui

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