Can Reverberation-measured Quasars Be Used for Cosmology?

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Published 2019 October 1 © 2019. The American Astronomical Society. All rights reserved.
, , Citation Mary Loli Martínez-Aldama et al 2019 ApJ 883 170 DOI 10.3847/1538-4357/ab3728

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0004-637X/883/2/170

Abstract

Quasars have been proposed as a new class of standard candles analogous to supernovae, since their large redshift range and high luminosities make them excellent candidates. The reverberation mapping (RM) method enables one to estimate the distance to the source from the time delay measurement of the emission lines with respect to the continuum, since the time delay depends on the absolute luminosity of the source. The radius–luminosity relation exhibits a low scatter and offers a potential use in cosmology. However, in recent years, the inclusion of new sources, particularly the super-Eddington accreting QSO, has increased the dispersion in the radius–luminosity relation, with many objects showing time delays shorter than the expected. Using 117 Hβ reverberation-mapped active galactic nuclei with 0.002 < z < 0.9 and 41.5 < log L5100 < 45.9, we find a correction for the time delay based on the dimensionless accretion rate ($\dot{{\mathscr{M}}}$) considering a virial factor anticorrelated with the FWHM of Hβ. This correction decreases the scattering of the accretion parameters compared with the typical values used, which is directly reflected by suppressing the radius–luminosity relation dispersion. We also confirm the anticorrelation between the excess of variability and the accretion parameters. With this correction, we are able to build the Hubble diagram and estimate the cosmological constants Ωm and ΩΛ, which are consistent with the Λ Cold Dark Matter model at 2σ confidence level. Therefore, reverberation mapping results can be used to constrain cosmological models in the future.

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1. Introduction

Understanding dark energy is one of the greatest puzzles of modern physics. In order to test the numerous theories proposed to explain the phenomenon of accelerated expansion of the universe, we first need to measure it precisely. There are well-established methods, such as the studies of the cosmic microwave background, supernovae Ia, baryon acoustic oscillations, and weak lensing. A combination of these methods currently sets the following cosmological parameters to these values: H0 = 67.66 ± 0.42 km s−1 Mpc−1, ΩΛ = 0.6889 ± 0.0056, Ωm = 0.3111 ± 0.0056 (Planck Collaboration et al. 2018). These results are consistent with the simplest interpretation of the cosmological constant in a dark matter–dominated universe in the form of the Λ cold dark matter (ΛCDM) model (Planck Collaboration et al. 2016a). However, there is now some tension with the local measurements of the Hubble constant (Riess et al. 2018), the amplitude of matter fluctuations in the late-time universe compared to cosmic shear measurements (Hildebrandt et al. 2017; Joudaki et al. 2017), and the number counts of galaxy clusters (Planck Collaboration et al. 2016b; see Pacaud et al. 2018 for the most recent results). Therefore, new objects are proposed as tools to better constrain the universe expansion, and active galactic nuclei (AGNs) are among them (e.g., Czerny et al. 2018).

The AGNs cover a broad range of redshift, and they do not show strong evolution with the redshift—for example, even the most distant quasars have metallicities similar to the nearby AGNs (close to the solar value or slightly higher; e.g., Groves et al. 2006). This could be caused by the combination of efficient rotational mixing and powerful stellar winds of early massive stars (Maeder & Meynet 2000; Brott et al. 2011; Ekström et al. 2012), which could transport the heavier nucleosynthesis products to the surface of massive stars already within ∼10 Myr of the stellar evolution (Stanway & Eldridge 2019). Powerful stellar winds would further enrich the interstellar medium (ISM) of early quasars.

Reverberation campaigns revealed a very strong and tight correlation between the broad-line region (BLR) size (RHβ) and the monochromatic luminosity at 5100 Å (L5100), producing the well-know radius–luminosity relation, ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ (Kaspi et al. 2000; Peterson et al. 2004; Bentz et al. 2013). Here RHβ is estimated from the time delay (τobs) between continuum and emission line variations and assuming the velocity as the speed of light (c), i.e., RHβ = τobs · c. The radius–luminosity relation offers prospects of cosmological applications. After proper calibration, the time delay measurement allows us to determine the absolute luminosity and use a generalized standard candle approach to obtain the cosmological parameters (Haas et al. 2011; Watson et al. 2011; Czerny et al. 2013; King & Lasota 2014).

The problem started with the detection of some outliers from the radius–luminosity relation (Bentz et al. 2013). First, outliers from the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation have been found among the highly accreting AGNs, which are the subject of the super-Eddington accreting massive black holes (SEAMBHs) campaign (Du et al. 2014, 2015, 2016, 2018; Wang et al. 2014a; Hu et al. 2015). The interpretation is that the measured delays that are much shorter than implied by the standard RHβL5100 relation (Bentz et al. 2013) are caused by the self-shielding of a geometrically thick accretion disk that subsequently modifies the radiation field seen by the surrounding material forming the BLR (Wang et al. 2014c).

Recently, more sources with considerably shorter than expected time delays were found by Grier et al. (2017) and Du et al. (2018). A significant fraction of them have low values of the Eddington ratio, and they cannot be simply eliminated from the sample. If the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation has such a large scatter, application of AGNs to cosmology based on this relation is problematic, unless we understand what additional parameter is responsible for the departure from the original RHβL5100 relation and are able to correct for this trend. It also poses a question about the nature of the standard radius–luminosity relation and the physical reasons for the departures from this law. These shortened lags could be explained by, for example, retrograde accretion (Wang et al. 2014b; Du et al. 2018), inner disk evaporation, or replacing the dust-based model of BLR formation (Czerny & Hryniewicz 2011; Czerny et al. 2015, 2017) with the old model based on the assumption of the ampleness of the gaseous material close to the nucleus and the formation of the BLR where the ionization parameter has the optimum value (Czerny et al. 2019).

In this paper, we analyze in detail how the properties of active galaxies correlate with their locations with respect to the standard ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation. Section 2 gives a description of the different Hβ reverberation-measured subsamples considered in this work and the relations used to estimate the main physical parameters, such as virial factor, black hole mass, accretion parameters, variability, etc. Section 3 describes the correction for the time delay based on the accretion parameters recovering the low scatter along the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation. We confirm the anticorrelation between the variability and the accretion parameters as well. Section 4 presents the Hubble diagram built with the reverberation-measured sample and the possible cosmological implications. We also discuss some remarks of the presented method that affect the implementation of quasars in cosmology in Section 5. In Section 6, we review the main result of this work. Absolute values of the luminosity are given assuming the cosmological parameters: H0 = 67 km s−1 Mpc−1, ΩΛ = 0.68, Ωm = 0.32 (Planck Collaboration et al. 2014).

2. Method

2.1. Observational Data

Our sample of Hβ reverberation-measured AGNs is a compilation of the results published earlier in the literature. It was previously used by Czerny et al. (2019): the luminosity (L5100), time delay (τobs), and FWHM are the same as considered by them. We have collected a total of 117 sources, plus two objects that have been discarded from the analysis (see details in Section 2.2). The first subsample is composed of 25 highly accreting AGNs observed by the SEAMBHs project (Du et al. 2014, 2015, 2016, 2018; Wang et al. 2014a; Hu et al. 2015). The SEAMBH project group has been monitoring super-Eddington sources since 2012, obtaining important results for this kind of object. The second subsample contains 44 objects from the recent Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project (Grier et al. 2017); two sources of this sample have been discarded. This sample comes from a larger sample of Shen et al. (2015); recently, they published an update of the catalog with additional information, such as the variability properties (Shen et al. 2019). The third subsample is a collection of 48 sources from long-term monitoring projects, where the majority of the sources have been summarized by Bentz et al. (2013). We include in this sample other sources monitored in recent years (Bentz et al. 2009, 2014, 2016a, 2016b; Barth et al. 2013; Pei et al. 2014; Fausnaugh et al. 2017). This collective sample is hereafter referred to as the Bentz collection. The fourth subsample includes NGC 5548 and 3C 273 (PG 1226+023), monitored by Lu et al. (2016) and Zhang et al. (2019), respectively. Previously, 3C 273 was monitored by Kaspi et al. (2000) and Peterson et al. (2004); however, new results from the GRAVITY Collaboration (Gravity Collaboration et al. 2018) resolved the BLR with a much better angular resolution of 10−5 '', indicating a smaller BLR size (∼150 lt-day) than the reverberation mapping results. Almost at the same time, Zhang et al. (2019) reported a new value for BLR size from a monitoring performed for ∼10 yr, which is similar to the one given by Gravity Collaboration et al. (2018). We will use this new estimation for 3C 273 hereafter in the paper.

These sources do not form a uniform sample. Sources from the Bentz collection were selected to cover a broad range of redshift (0.002 ≲ z ≲  0.292), from nearby sources studied earlier by, for example, Peterson et al. (2004) to more distant PG quasar samples from Kaspi et al. (2000). The average luminosity and dimensionless accretion rate are log L5100 = 43.4 erg s−1 and ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ ∼ 0.8 (see Section 2.3), respectively. Sources from the SDSS-RM sample are, on average, slightly more luminous, log L5100 = 43.9 erg s−1, and cover systematically larger redshifts, 0.116 ≲ z ≲  0.89. On the other hand, the SEAMBH sample has been selected with the aim of studying super-Eddington sources; they are nearby objects (0.017 ≲ z ≲  0.4) but with the largest accretion rates, ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$mean ∼ 14.6 (see Section 2.3).

The full sample includes 117 sources and covers a large redshift range (0.002 ≲ z ≲  0.89), which is convenient in order to test cosmological models. A detailed description of the sample is shown in Table 1.

Table 1.  Sample Description

Object z log L5100 τobs FWHM References
    (erg s−1) (days) ( km s−1)  
(1) (2) (3) (4) (5) (6)
SEAMBH Sample
Mrk 335 0.0258 43.764 ± 0.067 ${14.0}_{-3.4}^{+4.6}$ 2096 ± 170 (1)
Mrk 142 0.0449 43.594 ± 0.044 ${6.4}_{-3.4}^{+7.3}$ 1588 ± 58 (1)
IRAS F12397 0.0435 44.229 ± 0.054 ${9.7}_{-1.8}^{+5.5}$ 1802 ± 560 (1)
Mrk 486 0.0389 43.694 ± 0.050 ${23.7}_{-2.7}^{+7.5}$ 1942 ± 67 (2)
Mrk 382 0.0337 43.124 ± 0.085 ${7.5}_{-2.0}^{+2.9}$ 1462 ± 296 (2)
IRAS 04416 0.0889 44.467 ± 0.030 ${13.3}_{-1.4}^{+13.9}$ 1522 ± 44 (2)
MCG +06-26-012 0.0328 42.675 ± 0.106 ${24.0}_{-4.8}^{+8.4}$ 1334 ± 80 (2)
Mrk 493 0.0313 43.112 ± 0.075 ${11.6}_{-2.6}^{+1.2}$ 778 ± 12 (2)
Mrk 1044 0.0165 43.095 ± 0.102 ${10.5}_{-2.7}^{+3.3}$ 1178 ± 22 (2)
J080101 0.1396 44.270 ± 0.030 ${8.3}_{-2.7}^{+9.7}$ 1930 ± 18 (3)
J081456 0.1197 43.990 ± 0.040 ${24.3}_{-16.4}^{+7.7}$ 2409 ± 61 (3)
J093922 0.1859 44.070 ± 0.040 ${11.9}_{-6.3}^{+2.1}$ 1209 ± 16 (3)
J080131 0.1786 43.950 ± 0.040 ${11.5}_{-3.7}^{+7.5}$ 1290 ± 13 (4)
J085946 0.2438 44.410 ± 0.030 ${34.8}_{-26.3}^{+19.2}$ 1718 ± 16 (4)
J102339 0.1364 44.090 ± 0.030 ${24.9}_{-3.9}^{+19.8}$ 1733 ± 29 (4)
J074352 0.2520 45.370 ± 0.020 ${43.9}_{-4.2}^{+5.2}$ 3156 ± 36 (5)
J075051 0.4004 45.330 ± 0.010 ${66.6}_{-9.9}^{+18.7}$ 1904 ± 9 (5)
J075101 0.1209 44.240 ± 0.040 ${30.4}_{-5.8}^{+7.3}$ 1679 ± 35 (5)
J075949 0.1879 44.190 ± 0.060 ${43.9}_{-19.0}^{+33.1}$ 1783 ± 17 (5)
J081441 0.1626 43.950 ± 0.040 ${25.3}_{-7.5}^{+10.4}$ 1782 ± 16 (5)
J083553 0.2051 44.440 ± 0.020 ${12.4}_{-5.4}^{+5.4}$ 1758 ± 16 (5)
J084533 0.3024 44.520 ± 0.020 ${18.1}_{-4.7}^{+6.0}$ 1297 ± 12 (5)
J093302 0.1772 44.310 ± 0.130 ${19.0}_{-4.3}^{+3.8}$ 1800 ± 25 (5)
J100402 0.3272 45.520 ± 0.010 ${32.2}_{-4.2}^{+43.5}$ 2088 ± 1 (5)
J101000 0.2564 44.760 ± 0.020 ${27.7}_{-7.6}^{+23.5}$ 2311 ± 11 (5)
SDSS-RM Sample
J140812 0.1160 43.154 ± 0.013 ${10.5}_{-2.2}^{+1.0}$ 4345 ± 558 (6)
J141923 0.1520 43.122 ± 0.010 ${11.8}_{-1.5}^{+0.7}$ 2945 ± 20 (6)
J140759 0.1720 43.577 ± 0.009 ${16.3}_{-6.6}^{+13.1}$ 3662 ± 27 (6)
J141729 0.2370 43.291 ± 0.007 ${5.5}_{-2.1}^{+5.7}$ 9208 ± 269 (6)
J141645.15 0.2440 43.213 ± 0.007 ${5.0}_{-1.4}^{+1.5}$ 7409 ± 113 (6)
J142135 0.2490 43.475 ± 0.007 ${3.9}_{-0.9}^{+0.9}$ 3090 ± 66 (6)
J141625 0.2630 43.964 ± 0.019 ${15.1}_{-4.6}^{+3.2}$ 3515 ± 17 (6)
J142103 0.2630 43.636 ± 0.019 ${75.2}_{-3.3}^{+3.2}$ 2990 ± 48 (6)
J142038 0.2650 43.458 ± 0.006 ${25.2}_{-5.7}^{+4.7}$ 4700 ± 55 (6)
J142043 0.3370 43.400 ± 0.005 ${5.9}_{-0.6}^{+0.4}$ 4429 ± 105 (6)
J141041 0.3590 43.824 ± 0.005 ${21.9}_{-2.4}^{+4.2}$ 5034 ± 35 (6)
J141318 0.3620 43.941 ± 0.005 ${20.0}_{-3.0}^{+1.1}$ 3428 ± 37 (6)
J141955 0.4180 43.395 ± 0.005 ${10.7}_{-4.4}^{+5.6}$ 6789 ± 580 (6)
J141645.58 0.4420 43.679 ± 0.009 ${8.5}_{-1.4}^{+2.5}$ 2178 ± 44 (6)
J141324 0.4560 43.945 ± 0.004 ${25.5}_{-5.8}^{+10.9}$ 6076 ± 121 (6)
J141214 0.4580 44.397 ± 0.004 ${21.4}_{-6.4}^{+4.2}$ 2652 ± 302 (6)
J140518 0.4670 44.333 ± 0.004 ${41.6}_{-8.3}^{+14.8}$ 3406 ± 22 (6)
J141018 0.4700 43.584 ± 0.005 ${16.2}_{-4.5}^{+2.9}$ 4329 ± 298 (6)
J141123 0.4720 44.128 ± 0.004 ${13.0}_{-0.8}^{+1.4}$ 4106 ± 38 (6)
J142039 0.4740 44.141 ± 0.004 ${20.7}_{-3.0}^{+0.9}$ 4259 ± 90 (6)
J141724 0.4820 43.992 ± 0.004 ${10.1}_{-2.7}^{+12.5}$ 5230 ± 76 (6)
J141004 0.5270 44.224 ± 0.003 ${53.5}_{-4.0}^{+4.2}$ 2918 ± 62 (6)
J141706 0.5320 44.186 ± 0.003 ${10.4}_{-3.0}^{+6.3}$ 1682 ± 14 (6)
J142010 0.5480 44.088 ± 0.003 ${12.8}_{-4.5}^{+5.7}$ 6050 ± 541 (6)
J141712 0.5540 43.209 ± 0.012 ${12.5}_{-2.6}^{+1.8}$ 2226 ± 405 (6)
J141115 0.5720 44.313 ± 0.003 ${49.1}_{-2.0}^{+11.1}$ 3442 ± 51 (6)
J141112 0.5870 44.123 ± 0.003 ${20.4}_{-2.0}^{+2.5}$ 2765 ± 36 (6)
J141417 0.6040 43.397 ± 0.013 ${15.6}_{-5.1}^{+3.2}$ 6476 ± 793 (6)
J141031 0.6080 44.022 ± 0.003 ${35.8}_{-10.3}^{+1.1}$ 3495 ± 118 (6)
J141941 0.6460 44.522 ± 0.017 ${30.4}_{-8.3}^{+3.9}$ 2818 ± 48 (6)
J141135 0.6500 44.040 ± 0.004 ${17.6}_{-7.4}^{+8.6}$ 2515 ± 61 (6)
J140904 0.6580 44.147 ± 0.004 ${11.6}_{-4.6}^{+8.6}$ 10405 ± 1094 (6)
J142052 0.6760 45.059 ± 0.003 ${11.9}_{-1.0}^{+1.3}$ 3646 ± 14 (6)
J141147 0.6800 44.025 ± 0.004 ${6.4}_{-1.4}^{+1.5}$ 2338 ± 65 (6)
J141532 0.7150 44.136 ± 0.004 ${26.5}_{-8.8}^{+9.9}$ 1615 ± 38 (6)
J142023 0.7340 44.222 ± 0.006 ${8.5}_{-3.9}^{+3.2}$ 4446 ± 135 (6)
J142049 0.7510 44.446 ± 0.003 ${46.0}_{-9.5}^{+9.5}$ 4665 ± 97 (6)
J142112 0.8430 44.315 ± 0.008 ${14.2}_{-3.0}^{+3.7}$ 4428 ± 295 (6)
J141606 0.8480 44.801 ± 0.003 ${32.0}_{-15.5}^{+11.6}$ 7307 ± 213 (6)
J141859 0.8840 44.907 ± 0.003 ${20.4}_{-7.0}^{+5.6}$ 4999 ± 53 (6)
J141952 0.8840 44.246 ± 0.006 ${32.9}_{-5.1}^{+5.6}$ 7726 ± 319 (6)
J142417 0.8900 44.089 ± 0.060 ${36.3}_{-5.5}^{+4.5}$ 1721 ± 147 (6)
J141856 0.9760 45.382 ± 0.002 ${15.8}_{-1.9}^{+6.0}$ 3120 ± 58 (6)†
J141314 1.0260 44.524 ± 0.038 ${43.9}_{-4.3}^{+4.9}$ 1412 ± 183 (6)†
Bentz Collection
PG 0026+129 0.1420 44.970 ± 0.016 ${111.0}_{-28.3}^{+24.1}$ 1719 ± 495 (7)
PG 0052+251 0.1545 44.807 ± 0.025 ${89.8}_{-24.1}^{+24.5}$ 4165 ± 381 (7)
Fairall 9 0.0470 43.981 ± 0.041 ${17.4}_{-4.3}^{+3.2}$ 6901 ± 707 (7)
Mrk 590 0.0264 43.496 ± 0.212 ${25.6}_{-5.3}^{+6.5}$ 2220 ± 701 (7)
3C 120 0.0330 44.004 ± 0.100 ${26.2}_{-6.6}^{+8.7}$ 2372 ± 501 (7)
Ark 120 0.0327 43.867 ± 0.253 ${39.5}_{-7.8}^{+8.5}$ 5410 ± 360 (7)
Mrk 79 0.0222 43.677 ± 0.067 ${15.6}_{-4.9}^{+5.4}$ 4852 ± 1554 (7)
PG 0804+761 0.1000 44.910 ± 0.017 ${146.9}_{-18.9}^{+18.8}$ 2012 ± 845 (7)
Mrk 110 0.0353 43.658 ± 0.115 ${25.6}_{-7.2}^{+8.9}$ 1494 ± 802 (7)
PG 0953+414 0.2341 45.186 ± 0.013 ${150.1}_{-22.6}^{+21.6}$ 3002 ± 398 (7)
NGC 3227 0.0039 42.236 ± 0.106 ${3.8}_{-0.8}^{+0.8}$ 3578 ± 83 (7)
NGC 3516 0.0088 42.787 ± 0.205 ${11.7}_{-1.5}^{+1.0}$ 5175 ± 96 (7)
SBS 1116+583A 0.0279 42.138 ± 0.231 ${2.3}_{-0.5}^{+0.6}$ 3604 ± 1123 (7)
Arp 151 0.0211 42.548 ± 0.101 ${4.0}_{-0.7}^{+0.5}$ 2357 ± 142 (7)
NGC 3783 0.0097 42.558 ± 0.180 ${10.2}_{-2.3}^{+3.3}$ 3093 ± 529 (7)
Mrk 1310 0.0196 42.293 ± 0.145 ${3.7}_{-0.6}^{+0.6}$ 1602 ± 250 (7)
NGC 4051 0.0023 41.898 ± 0.152 ${2.1}_{-0.7}^{+0.9}$ 1034 ± 41 (7)
NGC 4151 0.0033 42.091 ± 0.207 ${6.6}_{-0.8}^{+1.1}$ 4711 ± 750 (7)
Mrk 202 0.0210 42.260 ± 0.144 ${3.0}_{-1.1}^{+1.7}$ 1354 ± 250 (7)
NGC 4253 0.0129 42.570 ± 0.122 ${6.2}_{-1.2}^{+1.6}$ 834 ± 1260 (7)
PG 1229+204 0.0630 43.697 ± 0.047 ${37.8}_{-15.3}^{+27.6}$ 3415 ± 320 (7)
NGC 4593 0.0090 42.621 ± 0.370 ${4.0}_{-0.7}^{+0.8}$ 4268 ± 551 (7)
NGC 4748 0.0146 42.556 ± 0.120 ${5.5}_{-2.2}^{+1.6}$ 1212 ± 173 (7)
PG 1307+085 0.1550 44.849 ± 0.015 ${105.6}_{-46.6}^{+36.0}$ 5058 ± 524 (7)
Mrk 279 0.0305 43.705 ± 0.074 ${16.7}_{-3.9}^{+3.9}$ 3385 ± 349 (7)
PG 1411+442 0.0896 44.563 ± 0.020 ${124.3}_{-61.7}^{+61.0}$ 2398 ± 353 (7)
PG 1426+015 0.0866 44.629 ± 0.024 ${95.0}_{-37.1}^{+29.9}$ 6323 ± 1295 (7)
Mrk 817 0.0315 43.743 ± 0.089 ${19.9}_{-6.7}^{+9.9}$ 4122 ± 1197 (7)
Mrk 290 0.0296 43.168 ± 0.057 ${8.7}_{-1.0}^{+1.2}$ 4270 ± 157 (7)
PG 1613+658 0.1290 44.774 ± 0.022 ${40.1}_{-15.2}^{+15.0}$ 7897 ± 1792 (7)
PG 1617+175 0.1124 44.391 ± 0.017 ${71.5}_{-33.7}^{+29.6}$ 4718 ± 991 (7)
PG 1700+518 0.2920 45.586 ± 0.007 ${251.8}_{-38.8}^{+45.9}$ 1846 ± 682 (7)
3C 390.3 0.0561 44.434 ± 0.576 ${44.5}_{-17.0}^{+27.7}$ 10415 ± 1971 (7)
NGC 6814 0.0052 42.120 ± 0.285 ${6.6}_{-0.9}^{+0.9}$ 3277 ± 297 (7)
Mrk 509 0.0344 44.193 ± 0.045 ${79.6}_{-5.4}^{+6.1}$ 2715 ± 101 (7)
PG 2130+099 0.0630 44.203 ± 0.028 ${9.6}_{-1.2}^{+1.2}$ 2097 ± 102 (7)
NGC 7469 0.0163 43.506 ± 0.108 ${10.8}_{-1.3}^{+3.4}$ 1066 ± 84 (7)
PG 1211+143 0.0809 44.728 ± 0.081 ${93.8}_{-42.1}^{+25.6}$ 2012 ± 37 (8)
PG 0844+349 0.0640 44.218 ± 0.071 ${32.3}_{-13.4}^{+13.7}$ 2436 ± 329 (8)
NGC 5273 0.0036 41.535 ± 0.160 ${2.2}_{-1.6}^{+1.2}$ 4615 ± 330 (9)
Mrk 1511 0.0339 43.162 ± 0.062 ${5.7}_{-0.8}^{+0.9}$ 4171 ± 137 (10)
KA 1858-4850 0.0780 43.428 ± 0.047 ${13.5}_{-2.3}^{+2.0}$ 1511 ± 68 (11)
MCG 6-30-15 0.0078 41.643 ± 0.108 ${5.7}_{-1.7}^{+1.8}$ 1422 ± 416 (12)
UGC 06728 0.0065 41.864 ± 0.081 ${1.4}_{-0.8}^{+0.7}$ 1145 ± 58 (13)
MCG +08-11-011 0.0205 43.330 ± 0.111 ${15.7}_{-0.5}^{+0.5}$ 1159 ± 8 (14)
NGC 2617 0.0142 42.667 ± 0.159 ${4.3}_{-1.4}^{+1.1}$ 5303 ± 49 (14)
3C 382 0.0579 43.835 ± 0.102 ${40.5}_{-3.7}^{+8.0}$ 3619 ± 282 (14)
Mrk 374 0.0426 43.774 ± 0.042 ${14.8}_{-3.3}^{+5.8}$ 3250 ± 19 (14)
Lu et al. (2016)
NGC 5548 0.0172 43.210 ± 0.120 ${7.2}_{-0.4}^{+1.3}$ 9912 ± 362 (15)
Zhang et al. (2019)
3C 273 0.1583 45.965 ± 0.016 ${146.8}_{-12.1}^{+8.3}$ 3314 ± 59 (16)

Note. Columns are as follows. (1) Object name. Discarded objects of the analysis are marked with a † symbol. Double-peak Hα profiles are marked with a ‡ symbol. (2) Redshift. (3) Luminosity at 5100 Å. (4) Delay time at rest frame. (5) FWHM of Hβ emission line. (6) References: (1) Du et al. (2014), (2) Wang et al. (2014a), (3) Du et al. (2015), (4) Du et al. (2016), (5) Du et al. (2018), (6) Grier et al. (2017), (7) Bentz et al. (2013), (8) Bentz et al. (2009), (9) Bentz et al. (2014), (10) Barth et al. (2013), (11) Pei et al. (2014), (12) Bentz et al. (2016a), (13) Bentz et al. (2016b), (14) Fausnaugh et al. (2017), (15) Lu et al. (2016), (16) Zhang et al. (2019).

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2.2. Discarded Objects and Biases in the Sample

Two objects from the SDSS-RM sample have been discarded from the analysis: J141856 and J141314. In the case of J141856, there is no detection of the blue side of the Hβ line, destroying the profile and prohibiting any possibility of measurement. In J141314, the Hβ line is at the border of the spectrum, where the signal-to-noise ratio (S/N) is poor and the emission line cannot be observed.

Observational problems can cause an incorrect estimation in the time delay; see Section 3.2 and the Appendix. It is important to stress that ∼30% of the SDSS-RM sample has a contribution of the host galaxy luminosity >50% with respect to AGNs. In order to decompose the quasar and host galaxy contribution, Shen et al. (2015) applied a principal component analysis (PCA). This method could present some systematic uncertainties in the decomposition due to the limited S/N or insufficient host contribution. However, in all of the analyzed cases, PCA is successful in decomposing both components, even those where S/N and the equivalent width are low, e.g., J141123.

In addition, some objects from the Bentz collection show a large variability and seem to not follow the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation. For example, the Hβ broad component in NGC 5548 appears and disappears over the years (e.g., Sergeev et al. 2007) and shows a steeper radius–luminosity relation (Peterson et al. 2004). However, variations in the measurements seem to be included in the intrinsic scatter of the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation (Kilerci Eser et al. 2015). Therefore, we decided to keep these peculiar sources in our analysis. The location of NGC 5548 is marked in all the plots.

2.3. Black Hole Mass and Accretion Parameters

Some of the sources from the sample deviate from the classical RHβL5100 relation (Grier et al. 2017; Czerny et al. 2019), and our aim is to find properties that characterize their departure from the scaling law in the best way. Du et al. (2016) suggested that accretion rate is the key parameter from which we calculate the related parameters uniformly for our sample.

In order to have an agreement in the computations of AGN parameters, we recompute the values following the same methods and using the same constant factors. The black hole mass (MBH) is estimated following the well-known relation

Equation (1)

where G is the gravitational constant, fBLR is the virial factor, RHβ is the BLR size, and v is the velocity field in the BLR, which is typically represented by the FWHM or the line dispersion (σline,rms) of the emission line measured in the rms spectrum.

The virial factor takes into account the geometry, kinematics, and inclination angle of the BLR. Many formalisms have been proposed for its description, for example, Peterson et al. (2004), Onken et al. (2004), Collin et al. (2006), Mejía-Restrepo et al. (2018), and Yu et al. (2019). The best method to calibrate the virial factor is through a comparison with an independent measurement of the black hole mass, for example, the one obtained from the relation between the MBH and the bulge or spheroid stellar velocity dispersion (σ*), the relation MBHσ* (e.g., Woo et al. 2015). However, in some cases, it is hard to get a proper measurement of the stellar absorption features, particularly in high-redshift sources. Also, it has not been tested considering super-Eddington sources. The large uncertainties associated with the virial factor introduce an error in the MBH determination by a factor of 2–3.

In this work, we are going to consider the FWHM as the velocity field in the BLR. Recently, Mejía-Restrepo et al. (2018) proposed that the virial factor is anticorrelated with the FWHM of broad emission lines. For the Hβ line, the relation is given by

Equation (2)

with FWHMobs in units of km s−1. A similar relation has recently been found by Yu et al. (2019) but with an exponent of −1.11. This representation could indicate a disklike geometry for the BLR and/or cloud motions or winds induced by the radiation force. In order to explore the effects of a different virial factor expression over the black hole mass and accretion parameters (Eddington ratio and dimensionless accretion rate), we have computed the MBH using the typical value fBLR = 1 and ${f}_{\mathrm{BLR}}^{{\rm{c}}}\propto $ FWHM−1.17 (see Section 3.3). In Table 2, we report mass MBH considering fBLR = 1.

Table 2.  Observational Properties for the Full Sample

Object log MBH log $\dot{{\mathscr{M}}}$ ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ log ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ fBLRc Fvar
  (M)          
(1) (2) (3) (4) (5) (6) (7)
SEAMBH Sample
Mrk 335 ${7.08}_{-0.13}^{+0.16}$ ${0.97}_{-0.27}^{+0.33}$ ${0.33}_{-0.13}^{+0.15}$ $-{0.25}_{-0.12}^{+0.15}$ 2.48 ± 0.24 0.030 (1)
Mrk 142 ${6.50}_{-0.23}^{+0.50}$ ${1.88}_{-0.47}^{+0.99}$ ${0.85}_{-0.50}^{+1.00}$ $-{0.50}_{-0.23}^{+0.50}$ 3.43 ± 0.15 0.066 (1)
IRAS F12397 ${6.79}_{-0.28}^{+0.37}$ ${2.25}_{-0.57}^{+0.74}$ ${1.89}_{-1.30}^{+1.65}$ $-{0.66}_{-0.09}^{+0.25}$ 2.96 ± 1.07 0.041 (1)
Mrk 486 ${7.24}_{-0.06}^{+0.14}$ ${0.54}_{-0.14}^{+0.29}$ ${0.19}_{-0.05}^{+0.08}$ ${0.01}_{-0.07}^{+0.14}$ 2.71 ± 0.11 0.034 (1)
Mrk 382 ${6.50}_{-0.21}^{+0.24}$ ${1.18}_{-0.44}^{+0.50}$ ${0.29}_{-0.16}^{+0.18}$ $-{0.18}_{-0.13}^{+0.18}$ 3.77 ± 0.89 0.041 (1)
IRAS 04416 ${6.78}_{-0.05}^{+0.45}$ ${2.63}_{-0.11}^{+0.91}$ ${3.34}_{-0.82}^{+3.57}$ $-{0.65}_{-0.06}^{+0.46}$ 3.60 ± 0.12 0.020 (1)
MCG 06 ${6.92}_{-0.10}^{+0.16}$ $-{0.34}_{-0.26}^{+0.36}$ ${0.04}_{-0.02}^{+0.02}$ ${0.56}_{-0.12}^{+0.17}$ 4.20 ± 0.29 0.092 (1)
Mrk 493 ${6.14}_{-0.10}^{+0.05}$ ${1.88}_{-0.23}^{+0.15}$ ${0.65}_{-0.23}^{+0.19}$ ${0.01}_{-0.11}^{+0.07}$ 7.90 ± 0.14 0.031 (1)
Mrk 1044 ${6.46}_{-0.11}^{+0.14}$ ${1.22}_{-0.27}^{+0.31}$ ${0.30}_{-0.12}^{+0.13}$ $-{0.02}_{-0.13}^{+0.15}$ 4.86 ± 0.11 0.037 (1)
J080101 ${6.78}_{-0.14}^{+0.51}$ ${2.33}_{-0.29}^{+1.02}$ ${2.12}_{-0.82}^{+2.51}$ $-{0.75}_{-0.15}^{+0.51}$ 2.73 ± 0.03 0.039
J081456 ${7.44}_{-0.29}^{+0.14}$ ${0.59}_{-0.59}^{+0.29}$ ${0.24}_{-0.17}^{+0.09}$ $-{0.14}_{-0.30}^{+0.14}$ 2.10 ± 0.06 0.031
J093922 ${6.53}_{-0.23}^{+0.08}$ ${2.53}_{-0.46}^{+0.17}$ ${2.37}_{-1.36}^{+0.67}$ $-{0.49}_{-0.23}^{+0.09}$ 4.71 ± 0.07 0.036
J080131 ${6.57}_{-0.14}^{+0.29}$ ${2.27}_{-0.29}^{+0.57}$ ${1.64}_{-0.64}^{+1.14}$ $-{0.44}_{-0.15}^{+0.29}$ 4.37 ± 0.05 0.047
J085946 ${7.30}_{-0.33}^{+0.24}$ ${1.50}_{-0.66}^{+0.48}$ ${0.88}_{-0.69}^{+0.52}$ $-{0.14}_{-0.30}^{+0.14}$ 3.13 ± 0.03 0.048
J102339 ${7.17}_{-0.07}^{+0.35}$ ${1.29}_{-0.15}^{+0.69}$ ${0.58}_{-0.15}^{+0.48}$ $-{0.18}_{-0.08}^{+0.35}$ 3.09 ± 0.06 0.032
J074352 ${7.93}_{-0.04}^{+0.05}$ ${1.68}_{-0.09}^{+0.11}$ ${1.88}_{-0.43}^{+0.45}$ $-{0.61}_{-0.07}^{+0.08}$ 1.53 ± 0.02 0.060
J075051 ${7.68}_{-0.06}^{+0.12}$ ${2.14}_{-0.13}^{+0.24}$ ${3.11}_{-0.78}^{+1.08}$ $-{0.41}_{-0.08}^{+0.13}$ 2.77 ± 0.02 0.032
J075101 ${7.22}_{-0.08}^{+0.11}$ ${1.40}_{-0.18}^{+0.22}$ ${0.71}_{-0.21}^{+0.23}$ $-{0.17}_{-0.09}^{+0.11}$ 3.21 ± 0.08 0.065
J075949 ${7.44}_{-0.19}^{+0.33}$ ${0.90}_{-0.39}^{+0.66}$ ${0.39}_{-0.19}^{+0.31}$ ${0.01}_{-0.19}^{+0.33}$ 2.99 ± 0.03 0.094
J081441 ${7.20}_{-0.13}^{+0.18}$ ${1.02}_{-0.27}^{+0.36}$ ${0.39}_{-0.14}^{+0.18}$ $-{0.10}_{-0.13}^{+0.18}$ 2.99 ± 0.03 0.051
J083553 ${6.88}_{-0.19}^{+0.19}$ ${2.40}_{-0.38}^{+0.38}$ ${2.53}_{-1.22}^{+1.22}$ $-{0.67}_{-0.19}^{+0.19}$ 3.04 ± 0.03 0.052
J084533 ${6.78}_{-0.11}^{+0.14}$ ${2.72}_{-0.23}^{+0.29}$ ${3.82}_{-1.27}^{+1.49}$ $-{0.55}_{-0.12}^{+0.15}$ 4.34 ± 0.05 0.040
J093302 ${7.08}_{-0.10}^{+0.09}$ ${1.79}_{-0.28}^{+0.26}$ ${1.17}_{-0.50}^{+0.48}$ $-{0.41}_{-0.12}^{+0.12}$ 2.96 ± 0.05 0.036
J100402 ${7.44}_{-0.06}^{+0.59}$ ${2.89}_{-0.11}^{+1.17}$ ${8.29}_{-2.00}^{+11.32}$ $-{0.83}_{-0.08}^{+0.59}$ 2.49 ± 0.001 0.048
J101000 ${7.46}_{-0.12}^{+0.37}$ ${1.71}_{-0.24}^{+0.74}$ ${1.37}_{-0.47}^{+1.19}$ $-{0.49}_{-0.13}^{+0.37}$ 2.21 ± 0.001 0.065
SDSS Sample
J140812 ${7.59}_{-0.14}^{+0.12}$ $-{0.96}_{-0.29}^{+0.24}$ ${0.03}_{-0.01}^{+0.01}$ $-{0.05}_{-0.10}^{+0.06}$ 1.06 ± 0.16 0.043
J141923 ${7.30}_{-0.06}^{+0.03}$ $-{0.43}_{-0.11}^{+0.06}$ ${0.05}_{-0.01}^{+0.01}$ ${0.01}_{-0.07}^{+0.05}$ 1.66 ± 0.01 0.076
J140759 ${7.63}_{-0.18}^{+0.35}$ $-{0.41}_{-0.35}^{+0.70}$ ${0.06}_{-0.03}^{+0.05}$ $-{0.09}_{-0.18}^{+0.35}$ 1.29 ± 0.01 0.038
J141729 ${7.96}_{-0.17}^{+0.45}$ $-{1.49}_{-0.34}^{+0.90}$ ${0.01}_{-0.01}^{+0.02}$ $-{0.41}_{-0.17}^{+0.45}$ 0.44 ± 0.01 0.033
J141645.15 ${7.73}_{-0.12}^{+0.13}$ $-{1.15}_{-0.24}^{+0.26}$ ${0.02}_{-0.01}^{+0.01}$ $-{0.41}_{-0.13}^{+0.14}$ 0.57 ± 0.01 0.068
J142135 ${6.86}_{-0.10}^{+0.10}$ ${0.98}_{-0.20}^{+0.20}$ ${0.28}_{-0.09}^{+0.09}$ $-{0.66}_{-0.11}^{+0.11}$ 1.57 ± 0.04 0.038
J141625 ${7.56}_{-0.13}^{+0.09}$ ${0.31}_{-0.27}^{+0.19}$ ${0.17}_{-0.06}^{+0.05}$ $-{0.33}_{-0.14}^{+0.10}$ 1.35 ± 0.01 0.058
J142103 ${8.12}_{-0.02}^{+0.02}$ $-{1.30}_{-0.06}^{+0.05}$ ${0.02}_{-0.005}^{+0.005}$ ${0.54}_{-0.04}^{+0.04}$ 1.63 ± 0.03
J142038 ${8.04}_{-0.10}^{+0.08}$ $-{1.40}_{-0.20}^{+0.16}$ ${0.02}_{-0.01}^{+0.01}$ ${0.16}_{-0.10}^{+0.09}$ 0.96 ± 0.01 0.065
J142043 ${7.36}_{-0.05}^{+0.04}$ $-{0.12}_{-0.10}^{+0.07}$ ${0.08}_{-0.02}^{+0.02}$ $-{0.44}_{-0.06}^{+0.05}$ 1.03 ± 0.03 0.036
J141041 ${8.04}_{-0.05}^{+0.08}$ $-{0.85}_{-0.10}^{+0.17}$ ${0.04}_{-0.01}^{+0.01}$ $-{0.09}_{-0.06}^{+0.09}$ 0.89 ± 0.01 0.074
J141318 ${7.66}_{-0.07}^{+0.03}$ ${0.08}_{-0.13}^{+0.05}$ ${0.13}_{-0.03}^{+0.03}$ $-{0.19}_{-0.07}^{+0.04}$ 1.39 ± 0.02 0.060
J141955 ${7.99}_{-0.19}^{+0.24}$ $-{1.39}_{-0.39}^{+0.48}$ ${0.02}_{-0.01}^{+0.01}$ $-{0.18}_{-0.18}^{+0.23}$ 0.63 ± 0.06 0.066
J141645.58 ${6.90}_{-0.07}^{+0.13}$ ${1.21}_{-0.15}^{+0.26}$ ${0.42}_{-0.11}^{+0.15}$ $-{0.43}_{-0.08}^{+0.13}$ 2.37 ± 0.06 0.053
J141324 ${8.27}_{-0.10}^{+0.19}$ $-{1.12}_{-0.20}^{+0.37}$ ${0.03}_{-0.01}^{+0.02}$ $-{0.09}_{-0.10}^{+0.19}$ 0.71 ± 0.02 0.046
J141214 ${7.47}_{-0.16}^{+0.13}$ ${1.15}_{-0.33}^{+0.26}$ ${0.58}_{-0.25}^{+0.21}$ $-{0.41}_{-0.13}^{+0.09}$ 1.88 ± 0.25 0.034
J140518 ${7.98}_{-0.09}^{+0.15}$ ${0.04}_{-0.17}^{+0.31}$ ${0.16}_{-0.04}^{+0.06}$ $-{0.09}_{-0.09}^{+0.16}$ 1.40 ± 0.01 0.072
J141018 ${7.77}_{-0.13}^{+0.10}$ $-{0.68}_{-0.27}^{+0.20}$ ${0.04}_{-0.02}^{+0.01}$ $-{0.10}_{-0.13}^{+0.08}$ 1.06 ± 0.09 0.044
J141123 ${7.63}_{-0.03}^{+0.05}$ ${0.42}_{-0.06}^{+0.10}$ ${0.22}_{-0.05}^{+0.05}$ $-{0.48}_{-0.04}^{+0.06}$ 1.13 ± 0.01 0.071
J142039 ${7.87}_{-0.07}^{+0.03}$ $-{0.03}_{-0.13}^{+0.05}$ ${0.13}_{-0.03}^{+0.03}$ $-{0.29}_{-0.07}^{+0.04}$ 1.08 ± 0.03 0.079
J141724 ${7.73}_{-0.12}^{+0.54}$ ${0.01}_{-0.23}^{+1.08}$ ${0.12}_{-0.04}^{+0.16}$ $-{0.52}_{-0.12}^{+0.54}$ 0.85 ± 0.01 0.064
J141004 ${7.95}_{-0.04}^{+0.04}$ $-{0.08}_{-0.07}^{+0.08}$ ${0.13}_{-0.03}^{+0.03}$ ${0.08}_{-0.05}^{+0.05}$ 1.68 ± 0.04 0.028
J141706 ${6.76}_{-0.13}^{+0.26}$ ${2.25}_{-0.25}^{+0.53}$ ${1.83}_{-0.65}^{+1.17}$ $-{0.61}_{-0.13}^{+0.26}$ 3.20 ± 0.03 0.052
J142010 ${7.96}_{-0.17}^{+0.21}$ $-{0.30}_{-0.34}^{+0.42}$ ${0.09}_{-0.04}^{+0.05}$ $-{0.47}_{-0.16}^{+0.20}$ 0.72 ± 0.08 0.133
J141712 ${7.08}_{-0.18}^{+0.17}$ ${0.14}_{-0.36}^{+0.34}$ ${0.09}_{-0.04}^{+0.04}$ $-{0.01}_{-0.10}^{+0.08}$ 2.31 ± 0.49 0.189
J141115 ${8.06}_{-0.02}^{+0.10}$ $-{0.15}_{-0.04}^{+0.20}$ ${0.12}_{-0.03}^{+0.04}$ ${0.003}_{-0.04}^{+0.10}$ 1.39 ± 0.02 0.064
J141112 ${7.49}_{-0.04}^{+0.05}$ ${0.70}_{-0.09}^{+0.11}$ ${0.30}_{-0.07}^{+0.07}$ $-{0.28}_{-0.05}^{+0.06}$ 1.79 ± 0.03 0.037
J141417 ${8.11}_{-0.18}^{+0.14}$ $-{1.63}_{-0.36}^{+0.28}$ ${0.01}_{-0.01}^{+0.01}$ $-{0.01}_{-0.15}^{+0.10}$ 0.66 ± 0.09 0.149
J141031 ${7.93}_{-0.13}^{+0.03}$ $-{0.34}_{-0.26}^{+0.06}$ ${0.08}_{-0.03}^{+0.02}$ ${0.02}_{-0.13}^{+0.03}$ 1.36 ± 0.05 0.053
J141941 ${7.68}_{-0.12}^{+0.06}$ ${0.92}_{-0.24}^{+0.12}$ ${0.48}_{-0.17}^{+0.12}$ $-{0.32}_{-0.12}^{+0.07}$ 1.75 ± 0.03 0.055
J141135 ${7.34}_{-0.18}^{+0.21}$ ${0.87}_{-0.37}^{+0.43}$ ${0.35}_{-0.16}^{+0.18}$ $-{0.30}_{-0.19}^{+0.21}$ 2.00 ± 0.06 0.096
J140904 ${8.39}_{-0.19}^{+0.33}$ $-{1.07}_{-0.39}^{+0.67}$ ${0.04}_{-0.02}^{+0.03}$ $-{0.54}_{-0.18}^{+0.32}$ 0.38 ± 0.05 0.099
J142052 ${7.49}_{-0.04}^{+0.05}$ ${2.10}_{-0.07}^{+0.10}$ ${2.54}_{-0.56}^{+0.58}$ $-{1.02}_{-0.06}^{+0.07}$ 1.30 ± 0.01 0.022
J141147 ${6.84}_{-0.10}^{+0.10}$ ${1.86}_{-0.20}^{+0.21}$ ${1.06}_{-0.32}^{+0.33}$ $-{0.73}_{-0.10}^{+0.11}$ 2.18 ± 0.07 0.092
J141532 ${7.13}_{-0.15}^{+0.16}$ ${1.43}_{-0.29}^{+0.33}$ ${0.70}_{-0.27}^{+0.30}$ $-{0.18}_{-0.15}^{+0.17}$ 3.36 ± 0.09 0.274
J142023 ${7.52}_{-0.20}^{+0.17}$ ${0.79}_{-0.40}^{+0.33}$ ${0.35}_{-0.18}^{+0.15}$ $-{0.72}_{-0.20}^{+0.17}$ 1.03 ± 0.04 0.107
J142049 ${8.29}_{-0.09}^{+0.09}$ $-{0.43}_{-0.18}^{+0.18}$ ${0.10}_{-0.03}^{+0.03}$ $-{0.10}_{-0.10}^{+0.10}$ 0.97 ± 0.02 0.097
J142112 ${7.74}_{-0.11}^{+0.13}$ ${0.49}_{-0.22}^{+0.25}$ ${0.26}_{-0.08}^{+0.09}$ $-{0.54}_{-0.10}^{+0.12}$ 1.03 ± 0.08 0.075
J141606 ${8.52}_{-0.21}^{+0.16}$ $-{0.36}_{-0.42}^{+0.32}$ ${0.13}_{-0.07}^{+0.05}$ $-{0.45}_{-0.21}^{+0.16}$ 0.57 ± 0.02 0.071
J141859 ${8.00}_{-0.15}^{+0.12}$ ${0.85}_{-0.30}^{+0.24}$ ${0.56}_{-0.22}^{+0.19}$ $-{0.70}_{-0.16}^{+0.13}$ 0.90 ± 0.01 0.056
J141952 ${8.59}_{-0.08}^{+0.08}$ $-{1.31}_{-0.15}^{+0.16}$ ${0.03}_{-0.01}^{+0.01}$ $-{0.14}_{-0.07}^{+0.08}$ 0.54 ± 0.03 0.166
J142417 ${7.32}_{-0.10}^{+0.09}$ ${0.98}_{-0.22}^{+0.20}$ ${0.40}_{-0.13}^{+0.13}$ $-{0.01}_{-0.08}^{+0.07}$ 3.12 ± 0.31 0.275
J141856† ${7.48}_{-0.05}^{+0.17}$ ${2.60}_{-0.11}^{+0.33}$ ${5.50}_{-1.31}^{+2.37}$ $-{1.06}_{-0.08}^{+0.17}$ 1.56 ± 0.03 0.144
J141314† ${7.23}_{-0.12}^{+0.12}$ ${1.81}_{-0.25}^{+0.25}$ ${1.34}_{-0.47}^{+0.48}$ $-{0.16}_{-0.06}^{+0.06}$ 3.93 ± 0.60 0.216
Bentz Collection
PG 0026+129 ${7.81}_{-0.27}^{+0.27}$ ${1.33}_{-0.55}^{+0.44}$ ${1.00}_{-0.66}^{+0.65}$ ${0.001}_{-0.12}^{+0.11}$ 3.12 ± 1.05 0.173 (2)
PG 0052+251 ${8.48}_{-0.14}^{+0.14}$ $-{0.27}_{-0.28}^{+0.43}$ ${0.14}_{-0.06}^{+0.06}$ $-{0.004}_{-0.12}^{+0.13}$ 1.11 ± 0.12 0.199 (2)
Fairall 9 ${8.21}_{-0.14}^{+0.12}$ $-{0.96}_{-0.29}^{+0.50}$ ${0.04}_{-0.02}^{+0.01}$ $-{0.28}_{-0.11}^{+0.09}$ 0.61 ± 0.07 0.328 (2)
Mrk 590 ${7.39}_{-0.29}^{+0.30}$ $-{0.05}_{-0.66}^{+0.43}$ ${0.09}_{-0.07}^{+0.08}$ ${0.15}_{-0.15}^{+0.16}$ 2.32 ± 0.86 0.108 (2)
3C 120 ${7.46}_{-0.21}^{+0.23}$ ${0.58}_{-0.45}^{+0.40}$ ${0.24}_{-0.14}^{+0.15}$ $-{0.11}_{-0.13}^{+0.16}$ 2.14 ± 0.53 0.178 (2)
Ark 120 ${8.36}_{-0.10}^{+0.11}$ $-{1.42}_{-0.43}^{+0.43}$ ${0.02}_{-0.01}^{+0.01}$ ${0.14}_{-0.16}^{+0.17}$ 0.82 ± 0.06 0.072 (2)
Mrk 79 ${7.86}_{-0.31}^{+0.32}$ $-{0.71}_{-0.63}^{+0.43}$ ${0.05}_{-0.03}^{+0.04}$ $-{0.16}_{-0.14}^{+0.16}$ 0.93 ± 0.35 0.091 (2)
PG 0804+761 ${8.07}_{-0.37}^{+0.37}$ ${0.72}_{-0.74}^{+0.43}$ ${0.48}_{-0.42}^{+0.42}$ ${0.16}_{-0.07}^{+0.07}$ 2.60 ± 1.28 0.176 (2)
Mrk 110 ${7.05}_{-0.48}^{+0.49}$ ${0.88}_{-0.98}^{+0.43}$ ${0.28}_{-0.32}^{+0.33}$ ${0.06}_{-0.14}^{+0.17}$ 3.68 ± 2.31 0.184 (2)
PG 0953+414 ${8.42}_{-0.13}^{+0.13}$ ${0.42}_{-0.27}^{+0.44}$ ${0.40}_{-0.15}^{+0.14}$ ${0.02}_{-0.08}^{+0.08}$ 1.63 ± 0.25 0.136 (2)
NGC 3227 ${6.98}_{-0.09}^{+0.09}$ $-{1.11}_{-0.25}^{+0.43}$ ${0.01}_{-0.005}^{+0.005}$ $-{0.01}_{-0.13}^{+0.13}$ 1.32 ± 0.04 0.094 (2)
NGC 3516 ${7.79}_{-0.06}^{+0.04}$ $-{1.90}_{-0.33}^{+0.45}$ ${0.01}_{-0.004}^{+0.004}$ ${0.19}_{-0.13}^{+0.13}$ 0.86 ± 0.02 0.289 (2)
SBS 1116+583A ${6.77}_{-0.29}^{+0.29}$ $-{0.84}_{-0.67}^{+0.43}$ ${0.02}_{-0.01}^{+0.01}$ $-{0.17}_{-0.17}^{+0.18}$ 1.31 ± 0.48 0.043(3)
Arp 151 ${6.64}_{-0.09}^{+0.08}$ ${0.03}_{-0.24}^{+0.48}$ ${0.06}_{-0.02}^{+0.02}$ $-{0.15}_{-0.11}^{+0.10}$ 2.16 ± 0.15 0.120(3)
NGC 3783 ${7.28}_{-0.18}^{+0.20}$ $-{1.24}_{-0.45}^{+0.40}$ ${0.01}_{-0.01}^{+0.01}$ ${0.25}_{-0.15}^{+0.18}$ 1.57 ± 0.31 0.192 (2)
Mrk 1310 ${6.27}_{-0.15}^{+0.15}$ ${0.39}_{-0.37}^{+0.43}$ ${0.07}_{-0.04}^{+0.04}$ $-{0.05}_{-0.12}^{+0.12}$ 3.39 ± 0.62 0.051(3)
NGC 4051 ${5.64}_{-0.15}^{+0.19}$ ${1.05}_{-0.38}^{+0.37}$ ${0.12}_{-0.07}^{+0.07}$ $-{0.08}_{-0.18}^{+0.22}$ 5.66 ± 0.26 0.059 (2)
NGC 4151 ${7.46}_{-0.15}^{+0.16}$ $-{2.29}_{-0.43}^{+0.42}$ ${0.003}_{-0.002}^{+0.002}$ ${0.31}_{-0.14}^{+0.15}$ 0.96 ± 0.18 0.058 (2)
Mrk 202 ${6.03}_{-0.23}^{+0.29}$ ${0.82}_{-0.50}^{+0.35}$ ${0.12}_{-0.08}^{+0.09}$ $-{0.12}_{-0.19}^{+0.27}$ 4.13 ± 0.89 0.027(3)
NGC 4253 ${5.93}_{-1.31}^{+1.32}$ ${1.49}_{-2.64}^{+0.43}$ ${0.30}_{-0.92}^{+0.92}$ ${0.03}_{-0.12}^{+0.14}$ 7.28 ± 12.87 0.053(3)
PG 1229+204 ${7.94}_{-0.19}^{+0.33}$ $-{0.84}_{-0.39}^{+0.26}$ ${0.04}_{-0.02}^{+0.03}$ ${0.21}_{-0.18}^{+0.32}$ 1.40 ± 0.15 0.107 (2)
NGC 4593 ${7.15}_{-0.14}^{+0.14}$ $-{0.89}_{-0.62}^{+0.43}$ ${0.02}_{-0.02}^{+0.02}$ $-{0.19}_{-0.22}^{+0.22}$ 1.08 ± 0.16 0.114 (2)
NGC 4748 ${6.20}_{-0.21}^{+0.18}$ ${0.93}_{-0.47}^{+0.51}$ ${0.16}_{-0.09}^{+0.08}$ $-{0.02}_{-0.20}^{+0.15}$ 4.70 ± 0.79 0.045(3)
PG 1307+085 ${8.72}_{-0.21}^{+0.17}$ $-{0.68}_{-0.42}^{+0.53}$ ${0.09}_{-0.05}^{+0.04}$ ${0.04}_{-0.20}^{+0.15}$ 0.88 ± 0.11 0.113 (2)
Mrk 279 ${7.57}_{-0.14}^{+0.14}$ $-{0.10}_{-0.29}^{+0.43}$ ${0.09}_{-0.04}^{+0.04}$ $-{0.15}_{-0.11}^{+0.11}$ 1.41 ± 0.17 0.082 (2)
PG 1411+442 ${8.15}_{-0.25}^{+0.25}$ ${0.04}_{-0.50}^{+0.44}$ ${0.18}_{-0.11}^{+0.11}$ ${0.27}_{-0.22}^{+0.22}$ 2.12 ± 0.36 0.105 (2)
PG 1426+015 ${8.87}_{-0.25}^{+0.22}$ $-{1.31}_{-0.49}^{+0.48}$ ${0.04}_{-0.02}^{+0.02}$ ${0.12}_{-0.17}^{+0.14}$ 0.68 ± 0.16 0.173 (2)
Mrk 817 ${7.82}_{-0.29}^{+0.33}$ $-{0.54}_{-0.60}^{+0.38}$ ${0.06}_{-0.04}^{+0.05}$ $-{0.09}_{-0.16}^{+0.22}$ 1.12 ± 0.38 0.050 (4)
Mrk 290 ${7.49}_{-0.06}^{+0.07}$ $-{0.74}_{-0.15}^{+0.40}$ ${0.03}_{-0.01}^{+0.01}$ $-{0.14}_{-0.07}^{+0.08}$ 1.08 ± 0.05 0.180 (4)
PG 1613+658 ${8.69}_{-0.26}^{+0.26}$ $-{0.73}_{-0.51}^{+0.44}$ ${0.08}_{-0.05}^{+0.05}$ $-{0.34}_{-0.17}^{+0.17}$ 0.52 ± 0.14 0.123 (2)
PG 1617+175 ${8.49}_{-0.27}^{+0.26}$ $-{0.91}_{-0.55}^{+0.46}$ ${0.05}_{-0.04}^{+0.03}$ ${0.12}_{-0.21}^{+0.18}$ 0.96 ± 0.24 0.191 (2)
PG 1700+518 ${8.23}_{-0.33}^{+0.33}$ ${1.42}_{-0.66}^{+0.43}$ ${1.58}_{-1.23}^{+1.24}$ ${0.03}_{-0.09}^{+0.10}$ 2.87 ± 1.24 0.060 (2)
3C 390.3 ${8.98}_{-0.23}^{+0.32}$ $-{1.81}_{-0.98}^{+0.40}$ ${0.02}_{-0.03}^{+0.03}$ $-{0.11}_{-0.35}^{+0.41}$ 0.38 ± 0.08 0.343 (2)
NGC 6814 ${7.14}_{-0.10}^{+0.10}$ $-{1.62}_{-0.47}^{+0.43}$ ${0.01}_{-0.005}^{+0.005}$ ${0.29}_{-0.18}^{+0.18}$ 1.47 ± 0.16 0.068(3)
Mrk 509 ${8.06}_{-0.04}^{+0.05}$ $-{0.34}_{-0.11}^{+0.42}$ ${0.09}_{-0.02}^{+0.02}$ ${0.27}_{-0.05}^{+0.05}$ 1.83 ± 0.08 0.181 (2)
PG 2130+099 ${6.92}_{-0.07}^{+0.07}$ ${1.96}_{-0.14}^{+0.43}$ ${1.33}_{-0.35}^{+0.35}$ $-{0.65}_{-0.06}^{+0.06}$ 2.48 ± 0.14 0.086 (2)
NGC 7469 ${6.38}_{-0.09}^{+0.15}$ ${1.99}_{-0.24}^{+0.30}$ ${0.92}_{-0.35}^{+0.44}$ $-{0.23}_{-0.09}^{+0.15}$ 5.46 ± 0.50 0.150 (2)
PG 1211+143 ${7.87}_{-0.20}^{+0.12}$ ${0.84}_{-0.41}^{+0.66}$ ${0.50}_{-0.26}^{+0.19}$ ${0.06}_{-0.20}^{+0.13}$ 2.60 ± 0.06 0.134 (2)
PG 0844+349 ${7.57}_{-0.21}^{+0.22}$ ${0.67}_{-0.44}^{+0.43}$ ${0.30}_{-0.17}^{+0.17}$ $-{0.13}_{-0.19}^{+0.19}$ 2.08 ± 0.33 0.105 (2)
NGC 5273 ${6.96}_{-0.32}^{+0.24}$ $-{2.13}_{-0.69}^{+0.55}$ ${0.003}_{-0.002}^{+0.002}$ ${0.13}_{-0.34}^{+0.27}$ 0.98 ± 0.08 0.059(5)
Mrk 1511 ${7.29}_{-0.07}^{+0.07}$ $-{0.34}_{-0.17}^{+0.41}$ ${0.05}_{-0.02}^{+0.02}$ $-{0.32}_{-0.08}^{+0.09}$ 1.11 ± 0.04 0.150(6)
KA 1858-4850 ${6.78}_{-0.08}^{+0.08}$ ${1.07}_{-0.18}^{+0.48}$ ${0.31}_{-0.09}^{+0.09}$ $-{0.09}_{-0.09}^{+0.08}$ 3.63 ± 0.19 0.084(7)
MCG 6-30-15 ${6.35}_{-0.28}^{+0.29}$ $-{0.75}_{-0.59}^{+0.43}$ ${0.01}_{-0.01}^{+0.01}$ ${0.49}_{-0.16}^{+0.17}$ 3.90 ± 1.34 0.132(8)
UGC 06728 ${5.56}_{-0.25}^{+0.22}$ ${1.17}_{-0.52}^{+0.49}$ ${0.14}_{-0.09}^{+0.08}$ $-{0.24}_{-0.26}^{+0.24}$ 5.03 ± 0.30 0.090(9)
MCG +08-11-011 ${6.62}_{-0.02}^{+0.02}$ ${1.25}_{-0.17}^{+0.43}$ ${0.36}_{-0.12}^{+0.12}$ ${0.03}_{-0.07}^{+0.07}$ 4.95 ± 0.04 0.100 (10)
NGC 2617 ${7.37}_{-0.14}^{+0.11}$ $-{1.26}_{-0.36}^{+0.48}$ ${0.01}_{-0.01}^{+0.01}$ $-{0.18}_{-0.17}^{+0.15}$ 0.84 ± 0.01 0.090 (10)
3C 382 ${8.02}_{-0.04}^{+0.11}$ $-{0.79}_{-0.17}^{+0.28}$ ${0.05}_{-0.01}^{+0.02}$ ${0.17}_{-0.07}^{+0.11}$ 1.31 ± 0.12 0.090 (10)
Mrk 374 ${7.49}_{-0.10}^{+0.17}$ ${0.18}_{-0.20}^{+0.26}$ ${0.13}_{-0.04}^{+0.06}$ $-{0.24}_{-0.10}^{+0.17}$ 1.48 ± 0.01 0.030 (10)
Lu et al. (2016)
NGC 5548 ${8.14}_{-0.04}^{+0.08}$ $-{1.98}_{-0.20}^{+0.25}$ ${0.008}_{-0.003}^{+0.003}$ $-{0.25}_{-0.08}^{+0.11}$ 0.40 ± 0.02 0.230 (11)
Zhang et al. (2019)
3C 273 ${8.50}_{-0.04}^{+0.03}$ ${1.44}_{-0.08}^{+0.06}$ ${2.01}_{-0.45}^{+0.43}$ $-{0.41}_{-0.08}^{+0.08}$ 1.45 ± 0.03 0.052 (2)

Note. Columns are as follows. (1) Object name. Discarded objects of the analysis are marked with a † symbol. (2) Black hole mass in units of solar masses. (3) Dimensionless accretion rate; see Equation (3). (4) Eddington ratio. (5) Deviations of BLR size from ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation. (6) Virial factor anticorrelated with the FWHM of Hβ; see Equation (2). (7) Fvar value defined in Equation (5). In some cases, the origin of the estimation is specified: (1) Hu et al. (2015), (2) Peterson et al. (2004), (3) Bentz et al. (2009), (4) Denney et al. (2010), (5) Bentz et al. (2014), (6) Barth et al. (2013), (7) Pei et al. (2014), (8) Bentz et al. (2016a), (9) Bentz et al. (2016b), (10) Fausnaugh et al. (2017), (11) Lu et al. (2016). The Fvar was estimated for the sources without references. Columns 2, 3, 4, and 5 were computed considering fBLR = 1.

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In order to estimate the accretion rate, we use the dimensionless accretion rate introduced by Du et al. (2016),

Equation (3)

where l44 is the luminosity at 5100 Å in units of 1044 erg s−1, θ is the inclination angle of the disk to the line of sight, and m7 is the black hole mass in units of 107 M. We considered cos θ = 0.75, which is the mean disk inclination for type 1 AGNs. It is estimated considering a torus axis coaligned with the disk axis and a torus covering factor of 0.5 (Du et al. 2016). The justification for this assumption is discussed in Section 5.2. Sources with $\dot{{\mathscr{M}}}$ ≳ 3 are highly accreting AGNs and host a slim accretion disk (Wang et al. 2014c). The $\dot{{\mathscr{M}}}$ with fBLR = 1 is reported in column 3 of Table 2.

The SEAMBH sample has, on average, the largest dimensionless accretion rate, $\dot{{\mathscr{M}}}$ $={139.5}_{-25.8}^{+96.8}$, which is expected due to the selection criteria of the sample. The SDSS-RM sample has the mean $\dot{{\mathscr{M}}}$ $={11.9}_{-2.7}^{+5.3}$, where one-third of the sources are classified as high accretors. The Bentz collection has the smallest mean value, $\dot{{\mathscr{M}}}$ $={7.9}_{-4.3}^{+4.5}$. As for the two remaining objects, 3C 273 is classified as a high accretor ($\dot{{\mathscr{M}}}$ $={27.4}_{-5.1}^{+3.9}$), and NGC 5548 is the source with the lowest accretion rate in the sample, $\dot{{\mathscr{M}}}$ $=\,{0.01}_{-0.005}^{+0.006}$.

We also consider the Eddington ratio, ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$, as an estimation of the accretion rate, where Lbol is the bolometric luminosity and LEdd is the Eddington luminosity defined by ${L}_{\mathrm{Edd}}=1.5\times {10}^{38}\left(\tfrac{{M}_{\mathrm{BH}}}{{M}_{\odot }}\right)$. In order to determine Lbol, we use the bolometric correction factor at 5100 Å proposed by Richards et al. (2006), BC5100 = 10.33. Although ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ depends upon the bolometric correction factor used, it has given good results in the identification of high accretion sources, which show ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ > 0.2 (Sulentic et al. 2017). The limit considered for $\dot{{\mathscr{M}}}$ and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ in order to identify highly accreting sources is analogous, since both parameters are well correlated (e.g., Capellupo et al. 2016). Average ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ values are as follows: ${1.6}_{-0.2}^{+0.5}$, ${0.3}_{-0.03}^{+0.04}$, and 0.2±0.04 for SEAMBH, SDSS-RM, and the Bentz collection, respectively. An ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ with a virial factor equal to 1 is shown in the fourth column of Table 2.

Considering the virial factor anticorrelated with the FWHM of Hβ (${f}_{\mathrm{BLR}}^{{\rm{c}}}$), the dimensionless accretion rate and Eddington ratio change by a factor of ${({f}_{\mathrm{BLR}}^{{\rm{c}}})}^{-2}$ and ${({f}_{\mathrm{BLR}}^{{\rm{c}}})}^{-1}$, respectively, i.e.,

Equation (4)

Therefore, new values for the accretion parameters can be estimated from the ones reported in Table 2. The virial factor selection changes considerably the accretion parameters and the dispersion associated with other physical parameters (see Section 3.3). We include a discussion of the uncertainties associated with the assumed virial factor and the implications for the presented analysis in Section 5.1.

2.4. Variability Characteristics

In order to have an estimation of the optical continuum variability amplitude, we will consider the parameter Fvar (Rodríguez-Pascual et al. 1997). It estimates the rms of the intrinsic variability relative to the mean flux,

Equation (5)

where σ2 is the variance of the flux, Δ is the mean square value of the uncertainties (Δi) associated with each flux measurement (fi), and $\langle f\rangle $ is the mean flux. Their definitions are as follows:

Equation (6)

The Fvar parameter has been reported for all objects of the Bentz collection (Peterson et al. 2004; Bentz et al. 2009, 2014, 2016a, 2016b; Denney et al. 2010; Barth et al. 2013; Pei et al. 2014; Fausnaugh et al. 2017) and some SEAMBH objects (Hu et al. 2015). For the remaining SEAMBH sources, we estimate Fvar from the light curves available in the literature (Du et al. 2015, 2016, 2018) following Equations (5) and (6). In the case of the SDSS-RM sample, we use the fractional rms variability provided by Shen et al. (2019; see their Table 2). Using the luminosities reported in Table 1, we can convert this quantity to Fvar. The object J142103 shows σ2 − Δ2 < 0, indicating that it does not present a significant variability, such as the one that has been reported in other objects (e.g., Sánchez et al. 2017). The Fvar values are reported in the last column of Table 2.

3. Accretion Rate Dependence along the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ Relation

3.1.  ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ Relation

The radius–luminosity relation used in this paper is given by Bentz et al. (2013),

Equation (7)

With the information reported in Table 1, we are able to build an RHβL5100 diagram, which is shown in Figures 1 and 2. In both figures, the variations of the dimensionless accretion rate (left) and Eddington ratio (right) along the diagram, considering fBLR = 1 (Figure 1) and fBLRc ∝ FWHM−1.17 (Figure 2), are shown. Independent of the selected virial factor, there is a clear trend with the accretion parameters. Sources with high accretion rate values show the largest departures from the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation (Du et al. 2015, 2018).

Figure 1.

Figure 1. The RHβL5100 relation for SEAMBHs (triangles), SDSS-RM (squares), the Bentz collection (circles), and NGC 5548 and 3C 273 (pentagons). Colors indicate the variation in dimensionless accretion rate ($\dot{{\mathscr{M}}}$ in log space; left) and Eddington ratio (${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$; right). The dashed black line corresponds to the expected RHβL5100 relation from Bentz et al. (2013). The dimensionless accretion parameter and the Eddington ratio have been computed considering fBLR = 1. The open black pentagon corresponds to NGC 5548 (see Sections 2.2 and 5.2).

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Figure 2.

Figure 2. Same as Figure 1 but considering the virial factor dependence ${f}_{\mathrm{BLR}}^{{\rm{c}}}\propto $ FWHM−1.17.

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On the other hand, we also explored whether the FWHM and the equivalent width of the Hβ line show a similar trend along the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ diagram, but we cannot find any clear pattern.

3.2. Testing Cadence in SDSS-RM Sample

The monitoring performed for the SDSS-RM sample is relatively short (only 180 days), taking into account that their sources are at relatively large redshift, and some of them are rather bright. An expected delay could be close to the duration of the campaign. In addition, the number of spectroscopic measurements is not very high (only 32). This may cast some doubts as to whether the estimated time delays are measured reliably. Thus, we performed simulations of the expected time delays assuming that the sources follow the standard ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation and using the observational cadence. The results are presented in the Appendix and they show that both the duration of the observation and the cadence should not strongly affect the measured delays.

3.3. Correction for the Time Delay

The SEAMBH team made important progress in understanding the reverberation mapping in highly accreting sources (Wang et al. 2014a; Du et al. 2014, 2015, 2016, 2018; Hu et al. 2015), which have been scarcely included in previous RM samples. They found that AGNs with $\dot{{\mathscr{M}}}$ ≳ 3 have time delays (τobs) shorter than expected from the RHβL5100 relation (Bentz et al. 2013). The deviation can be estimated by the parameter

Equation (8)

where τHβR–L is the time delay corresponding to that expected from the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation for the given L5100; see Equation (7). Figures 3 and 4 show ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ as a function of $\dot{{\mathscr{M}}}$ and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ considering fBLR and ${f}_{\mathrm{BLR}}^{{\rm{c}}}$. In all four cases, the largest ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ are associated with the highest $\dot{{\mathscr{M}}}$ and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$; the difference is the scatter along the relations. We perform an orthogonal linear fit in order to get the linear trend and estimate the Pearson coefficient (P) and rms error to measure the correlation and dispersion along the trend line. The general linear relation is given by

Equation (9)

where X corresponds to the accretion parameter (dimensionless accretion rate or Eddington ratio) using a virial factor equal to 1 or the one anticorrelated with the FWHM. Coefficients of the fit (α and β), Pearson, and rms values are given in Table 3.

Table 3.  Orthogonal Linear Fit Parameters

  X α β P rms
(1) (2) (3) (4) (5) (6)
fBLR $\dot{{\mathscr{M}}}$ −0.143 ± 0.018 −0.136 ± 0.023 0.572 0.243
  ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ −0.271 ± 0.030 −0.396 ± 0.032 0.605 0.626
fBLRc ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ −0.283 ± 0.017 −0.228 ± 0.016 0.822 0.172
  ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}^{{\rm{c}}}$ −0.394 ± 0.030 −0.589 ± 0.036 0.744 0.199

Note. Columns are as follows. (1) Virial factor. (2) Accretion parameter: dimensionless accretion rate or Eddington ratio. (3) Slope of Equation (9). (4) Ordinate of Equation (9). (5) Pearson coefficient. (6) The rms value. Rows 1 and 2 correspond to the estimations for a virial factor equal to 1, fBLR. Rows 3 and 4 correspond to the estimations for a virial factor anticorrelated with the FWHM, fBLRc.

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Figure 3.

Figure 3. Relation between ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ and $\dot{{\mathscr{M}}}$ (left; in log space) and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ (right; in log space) using fBLR = 1. Symbols are the same as in Figure 1. Symbol colors indicate the variation in Fvar at 5100 Å. The open black square corresponds to the quasar J142103 (see Section 2.4). In both panels, the dashed horizontal line corresponds to ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ = 0, and the dashed diagonal black line shows the best orthogonal linear fit. Vertical lines correspond to $\dot{{\mathscr{M}}}$ = 3 and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ = 0.2.

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Figure 4.

Figure 4. Relation between ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ and ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ (left) and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}^{{\rm{c}}}$ (right) using ${f}_{\mathrm{BLR}}^{{\rm{c}}}\propto $ FWHM−1.17. Descriptions of symbols, colors, and lines are the same as in Figure 3.

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The information given by the Pearson coefficients and rms values indicates that the relations between ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ and accretion parameters are stronger when the virial factor anticorrelated with the FWHM is used; see Equation (9). We are able to propose a correction for the time delay based on the accretion parameters that recovers the expected value from the RHβL5100 relation. Since P and rms favor ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$, the correction used will be based on it and not on ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}^{{\rm{c}}}$. The scattering of the Eddington ratio could be higher due to the large uncertainties associated with the bolometric correction factor.

The time delay corrected for the effect of the dimensionless accretion rate can be estimated by the relation

Equation (10)

The quantities ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$, ${\rm{\Delta }}{R}_{{\rm{H}}\beta }({\dot{{\mathscr{M}}}}^{{\rm{c}}})$, and ${\tau }_{\mathrm{corr}}({\dot{{\mathscr{M}}}}^{c})$ are listed in Table 4. The ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation with the correction for the dimensionless accretion rate is shown in Figure 5. If we compare this new diagram with the one shown in the left panel of Figure 2, it is clear that the scatter decreases significantly along the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation, σobs = 0.684 versus ${\sigma }_{\mathrm{corr}}=0.396$ in log space. With this correction, we are able to build a better luminosity distance–redshift relation or Hubble diagram and compare them with the standard cosmological models (see Section 4).

Table 4.  Observational Properties Corrected by the Effect of Dimensionless Accretion Rate

Object log ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ ${\rm{\Delta }}{R}_{{\rm{H}}\beta ,{\dot{{\mathscr{M}}}}^{{\rm{c}}}}$ τcorr DL,corr
      (days) (Mpc)
(1) (2) (3) (4) (5)
SEAMBH Sample
Mrk 335 ${0.19}_{-0.28}^{+0.34}$ $-{0.28}_{-0.08}^{+0.10}$ ${26.7}_{-6.5}^{+8.8}$ 136.1 ± 38.9
Mrk 142 ${0.81}_{-0.47}^{+0.99}$ $-{0.46}_{-0.14}^{+0.28}$ ${18.4}_{-9.8}^{+21.0}$ 199.7 ± 167.0
IRAS F12397 ${1.31}_{-0.65}^{+0.80}$ $-{0.60}_{-0.19}^{+0.23}$ ${38.6}_{-7.2}^{+21.9}$ 192.6 ± 72.5
Mrk 486 $-{0.32}_{-0.14}^{+0.29}$ $-{0.14}_{-0.04}^{+0.08}$ ${32.5}_{-3.7}^{+10.3}$ 271.9 ± 58.5
Mrk 382 ${0.03}_{-0.49}^{+0.54}$ $-{0.24}_{-0.14}^{+0.15}$ ${12.9}_{-3.4}^{+5.0}$ 180.8 ± 59.1
IRAS 04416 ${1.52}_{-0.12}^{+0.91}$ $-{0.66}_{-0.05}^{+0.26}$ ${60.5}_{-6.4}^{+63.2}$ 490.6 ± 282.2
MCG 06 $-{1.59}_{-0.26}^{+0.36}$ ${0.22}_{-0.08}^{+0.11}$ ${14.4}_{-2.9}^{+5.0}$ 327.5 ± 90.1
Mrk 493 ${0.09}_{-0.23}^{+0.15}$ $-{0.25}_{-0.07}^{+0.04}$ ${20.8}_{-4.7}^{+2.1}$ 268.0 ± 43.9
Mrk 1044 $-{0.15}_{-0.27}^{+0.31}$ $-{0.19}_{-0.08}^{+0.09}$ ${16.1}_{-4.1}^{+5.1}$ 114.9 ± 32.8
J080101 ${1.46}_{-0.29}^{+1.02}$ $-{0.64}_{-0.09}^{+0.29}$ ${36.4}_{-11.8}^{+42.5}$ 602.2 ± 449.9
J081456 $-{0.05}_{-0.59}^{+0.29}$ $-{0.21}_{-0.17}^{+0.08}$ ${39.7}_{-26.8}^{+12.6}$ 767.7 ± 380.7
J093922 ${1.18}_{-0.46}^{+0.17}$ $-{0.56}_{-0.13}^{+0.05}$ ${43.6}_{-23.1}^{+7.7}$ 1241.0 ± 438.1
J080131 ${0.99}_{-0.29}^{+0.57}$ $-{0.51}_{-0.08}^{+0.16}$ ${37.0}_{-12.0}^{+24.3}$ 1159.0 ± 567.9
J085946 ${0.51}_{-0.66}^{+0.48}$ $-{0.37}_{-0.19}^{+0.14}$ ${82.0}_{-62.0}^{+45.2}$ 2141.8 ± 1400.3
J102339 ${0.31}_{-0.15}^{+0.69}$ $-{0.32}_{-0.05}^{+0.20}$ ${51.6}_{-8.1}^{+41.1}$ 1019.5 ± 485.2
J074352 ${1.31}_{-0.09}^{+0.11}$ $-{0.60}_{-0.04}^{+0.04}$ ${174.2}_{-16.7}^{+20.6}$ 1563.7 ± 167.5
J075051 ${1.25}_{-0.13}^{+0.24}$ $-{0.58}_{-0.05}^{+0.07}$ ${254.6}_{-37.8}^{+71.5}$ 4086.4 ± 877.5
J075101 ${0.39}_{-0.18}^{+0.22}$ $-{0.34}_{-0.05}^{+0.06}$ ${66.2}_{-12.6}^{+15.8}$ 968.3 ± 208.2
J075949 $-{0.05}_{-0.39}^{+0.66}$ $-{0.21}_{-0.11}^{+0.19}$ ${71.8}_{-31.2}^{+54.3}$ 1803.4 ± 1072.6
J081441 ${0.07}_{-0.26}^{+0.36}$ $-{0.25}_{-0.08}^{+0.10}$ ${44.7}_{-13.3}^{+18.4}$ 1264.3 ± 447.5
J083553 ${1.43}_{-0.38}^{+0.38}$ $-{0.63}_{-0.11}^{+0.11}$ ${53.4}_{-23.3}^{+23.3}$ 1107.6 ± 482.4
J084533 ${1.44}_{-0.23}^{+0.29}$ $-{0.64}_{-0.07}^{+0.09}$ ${78.5}_{-20.5}^{+26.1}$ 2307.1 ± 683.8
J093302 ${0.85}_{-0.28}^{+0.26}$ $-{0.47}_{-0.08}^{+0.08}$ ${55.9}_{-12.7}^{+11.2}$ 1144.7 ± 244.0
J100402 ${2.10}_{-0.11}^{+1.17}$ $-{0.82}_{-0.05}^{+0.33}$ ${214.2}_{-28.0}^{+289.5}$ 2182.5 ± 1616.9
J101000 ${1.02}_{-0.24}^{+0.74}$ $-{0.52}_{-0.07}^{+0.21}$ ${91.0}_{-25.0}^{+77.2}$ 1677.6 ± 941.8
SDSS Sample
J140812 $-{1.00}_{-0.32}^{+0.27}$ ${0.06}_{-0.09}^{+0.08}$ ${9.2}_{-1.9}^{+0.9}$ 450.4 ± 68.6
J141923 $-{0.87}_{-0.11}^{+0.06}$ ${0.02}_{-0.04}^{+0.03}$ ${11.3}_{-1.4}^{+0.7}$ 767.1 ± 71.5
J140759 $-{0.63}_{-0.35}^{+0.70}$ $-{0.05}_{-0.10}^{+0.20}$ ${18.3}_{-7.4}^{+14.7}$ 843.3 ± 509.6
J141729 $-{0.78}_{-0.34}^{+0.90}$ $-{0.01}_{-0.10}^{+0.26}$ ${5.6}_{-2.1}^{+5.8}$ 513.3 ± 364.0
J141645.15 $-{0.66}_{-0.25}^{+0.26}$ $-{0.04}_{-0.07}^{+0.08}$ ${5.5}_{-1.5}^{+1.7}$ 571.3 ± 165.7
J142135 ${0.58}_{-0.21}^{+0.21}$ $-{0.39}_{-0.06}^{+0.06}$ ${9.6}_{-2.2}^{+2.2}$ 756.9 ± 174.7
J141625 ${0.05}_{-0.27}^{+0.19}$ $-{0.24}_{-0.08}^{+0.06}$ ${26.3}_{-8.0}^{+5.6}$ 1252.6 ± 323.5
J142103 $-{1.72}_{-0.06}^{+0.06}$ ${0.26}_{-0.04}^{+0.04}$ ${41.4}_{-1.8}^{+1.8}$ 2868.9 ± 124.0
J142038 $-{1.36}_{-0.20}^{+0.16}$ ${0.16}_{-0.06}^{+0.05}$ ${17.5}_{-4.0}^{+3.3}$ 1503.1 ± 310.2
J142043 $-{0.15}_{-0.10}^{+0.08}$ $-{0.19}_{-0.03}^{+0.03}$ ${9.1}_{-0.9}^{+0.6}$ 1096.8 ± 93.0
J141041 $-{0.74}_{-0.10}^{+0.17}$ $-{0.02}_{-0.03}^{+0.05}$ ${22.8}_{-2.5}^{+4.4}$ 1825.9 ± 275.1
J141318 $-{0.21}_{-0.13}^{+0.05}$ $-{0.17}_{-0.04}^{+0.02}$ ${29.4}_{-4.4}^{+1.6}$ 2080.1 ± 213.2
J141955 $-{0.98}_{-0.40}^{+0.49}$ ${0.05}_{-0.11}^{+0.14}$ ${9.5}_{-3.9}^{+5.0}$ 1498.1 ± 700.0
J141645.58 ${0.46}_{-0.15}^{+0.26}$ $-{0.36}_{-0.05}^{+0.08}$ ${19.5}_{-3.2}^{+5.7}$ 2352.9 ± 539.8
J141324 $-{0.83}_{-0.20}^{+0.37}$ ${0.01}_{-0.06}^{+0.11}$ ${25.1}_{-5.7}^{+10.7}$ 2317.8 ± 759.0
J141214 ${0.60}_{-0.35}^{+0.29}$ $-{0.40}_{-0.10}^{+0.08}$ ${53.5}_{-16.0}^{+10.5}$ 2950.6 ± 730.8
J140518 $-{0.26}_{-0.17}^{+0.31}$ $-{0.16}_{-0.05}^{+0.09}$ ${59.5}_{-11.9}^{+21.2}$ 3619.4 ± 1004.9
J141018 $-{0.73}_{-0.28}^{+0.21}$ $-{0.02}_{-0.08}^{+0.06}$ ${17.0}_{-4.7}^{+3.0}$ 2464.1 ± 562.8
J141123 ${0.31}_{-0.06}^{+0.10}$ $-{0.32}_{-0.02}^{+0.03}$ ${27.0}_{-1.7}^{+2.9}$ 2101.4 ± 177.8
J142039 $-{0.10}_{-0.13}^{+0.06}$ $-{0.20}_{-0.04}^{+0.02}$ ${32.8}_{-4.8}^{+1.4}$ 2535.0 ± 238.8
J141724 ${0.15}_{-0.23}^{+1.07}$ $-{0.27}_{-0.07}^{+0.30}$ ${18.9}_{-5.0}^{+23.4}$ 1763.9 ± 1327.3
J141004 $-{0.53}_{-0.08}^{+0.08}$ $-{0.08}_{-0.03}^{+0.03}$ ${64.2}_{-4.8}^{+5.0}$ 5113.1 ± 391.8
J141706 ${1.24}_{-0.25}^{+0.53}$ $-{0.58}_{-0.08}^{+0.15}$ ${39.4}_{-11.4}^{+23.9}$ 3318.1 ± 1483.7
J142010 $-{0.01}_{-0.35}^{+0.43}$ $-{0.22}_{-0.10}^{+0.12}$ ${21.5}_{-7.5}^{+9.6}$ 2096.5 ± 835.3
J141712 $-{0.59}_{-0.41}^{+0.39}$ $-{0.06}_{-0.12}^{+0.11}$ ${14.4}_{-3.0}^{+2.1}$ 3916.2 ± 689.3
J141115 $-{0.44}_{-0.05}^{+0.20}$ $-{0.10}_{-0.02}^{+0.06}$ ${62.4}_{-2.5}^{+14.1}$ 4955.6 ± 661.1
J141112 ${0.20}_{-0.09}^{+0.11}$ $-{0.28}_{-0.03}^{+0.04}$ ${39.3}_{-3.8}^{+4.8}$ 4003.1 ± 441.5
J141417 $-{1.27}_{-0.38}^{+0.30}$ ${0.13}_{-0.11}^{+0.09}$ ${11.5}_{-3.8}^{+2.4}$ 2803.4 ± 745.8
J141031 $-{0.61}_{-0.26}^{+0.07}$ $-{0.06}_{-0.08}^{+0.03}$ ${40.6}_{-11.7}^{+1.2}$ 4857.2 ± 773.3
J141941 ${0.44}_{-0.24}^{+0.12}$ $-{0.35}_{-0.07}^{+0.04}$ ${68.4}_{-18.7}^{+8.8}$ 4947.3 ± 992.8
J141135 ${0.27}_{-0.37}^{+0.43}$ $-{0.30}_{-0.11}^{+0.12}$ ${35.5}_{-14.9}^{+17.4}$ 4509.7 ± 2049.9
J140904 $-{0.23}_{-0.40}^{+0.68}$ $-{0.16}_{-0.12}^{+0.19}$ ${16.9}_{-6.7}^{+12.5}$ 1923.8 ± 1094.6
J142052 ${1.87}_{-0.07}^{+0.10}$ $-{0.76}_{-0.04}^{+0.05}$ ${68.2}_{-5.7}^{+7.5}$ 2810.9 ± 271.8
J141147 ${1.18}_{-0.20}^{+0.21}$ $-{0.56}_{-0.06}^{+0.07}$ ${23.4}_{-5.1}^{+5.5}$ 3188.0 ± 722.4
J141532 ${0.38}_{-0.29}^{+0.33}$ $-{0.34}_{-0.08}^{+0.09}$ ${57.4}_{-19.0}^{+21.4}$ 7326.8 ± 2585.2
J142023 ${0.76}_{-0.40}^{+0.33}$ $-{0.44}_{-0.12}^{+0.10}$ ${23.7}_{-10.9}^{+8.9}$ 2827.5 ± 1181.0
J142049 $-{0.40}_{-0.18}^{+0.18}$ $-{0.11}_{-0.06}^{+0.06}$ ${59.9}_{-12.4}^{+12.4}$ 5688.3 ± 1174.8
J142112 ${0.46}_{-0.23}^{+0.26}$ $-{0.36}_{-0.07}^{+0.08}$ ${32.4}_{-6.9}^{+8.5}$ 4128.8 ± 974.1
J141606 ${0.12}_{-0.42}^{+0.32}$ $-{0.26}_{-0.12}^{+0.09}$ ${58.7}_{-28.4}^{+21.3}$ 4298.4 ± 1820.2
J141859 ${0.95}_{-0.30}^{+0.24}$ $-{0.50}_{-0.09}^{+0.07}$ ${64.0}_{-22.0}^{+17.6}$ 4366.7 ± 1348.6
J141952 $-{0.77}_{-0.16}^{+0.17}$ $-{0.01}_{-0.05}^{+0.05}$ ${33.6}_{-5.2}^{+5.7}$ 4911.1 ± 798.6
J142417 $-{0.01}_{-0.23}^{+0.22}$ $-{0.22}_{-0.07}^{+0.06}$ ${60.9}_{-9.2}^{+7.6}$ 10753.6 ± 1481.3
Bentz Collection
PG 0026+129 ${0.34}_{-0.62}^{+0.61}$ $-{0.32}_{-0.18}^{+0.17}$ ${234.4}_{-59.8}^{+50.9}$ 1761.2 ± 415.8
PG 0052+251 $-{0.36}_{-0.30}^{+0.30}$ $-{0.13}_{-0.09}^{+0.09}$ ${120.2}_{-32.3}^{+32.8}$ 1191.0 ± 322.3
Fairall 9 $-{0.54}_{-0.30}^{+0.27}$ $-{0.08}_{-0.09}^{+0.08}$ ${20.8}_{-5.1}^{+3.8}$ 151.1 ± 32.6
Mrk 590 $-{0.78}_{-0.73}^{+0.74}$ $-{0.01}_{-0.21}^{+0.21}$ ${26.0}_{-5.4}^{+6.6}$ 180.4 ± 41.6
3C 120 $-{0.09}_{-0.50}^{+0.53}$ $-{0.20}_{-0.14}^{+0.15}$ ${41.9}_{-10.6}^{+13.9}$ 206.4 ± 60.3
Ark 120 $-{1.24}_{-0.44}^{+0.44}$ ${0.12}_{-0.13}^{+0.13}$ ${29.7}_{-5.9}^{+6.4}$ 171.3 ± 35.3
Mrk 79 $-{0.64}_{-0.71}^{+0.72}$ $-{0.05}_{-0.20}^{+0.20}$ ${17.3}_{-5.4}^{+6.0}$ 82.4 ± 27.2
PG 0804+761 $-{0.11}_{-0.85}^{+0.85}$ $-{0.20}_{-0.24}^{+0.24}$ ${231.7}_{-29.8}^{+29.7}$ 1278.3 ± 164.1
Mrk 110 $-{0.25}_{-1.12}^{+1.13}$ $-{0.16}_{-0.32}^{+0.32}$ ${36.7}_{-10.3}^{+12.8}$ 286.4 ± 90.1
PG 0953+414 ${0.001}_{-0.30}^{+0.30}$ $-{0.23}_{-0.09}^{+0.09}$ ${253.8}_{-38.2}^{+36.5}$ 2587.7 ± 381.0
NGC 3227 $-{1.36}_{-0.25}^{+0.25}$ ${0.16}_{-0.08}^{+0.08}$ ${2.7}_{-0.6}^{+0.6}$ 11.9 ± 2.5
NGC 3516 $-{1.77}_{-0.33}^{+0.32}$ ${0.27}_{-0.10}^{+0.10}$ ${6.2}_{-0.8}^{+0.5}$ 33.3 ± 3.6
SBS 1116+583A $-{1.07}_{-0.74}^{+0.75}$ ${0.08}_{-0.21}^{+0.21}$ ${1.9}_{-0.4}^{+0.5}$ 68.9 ± 16.5
Arp 151 $-{0.63}_{-0.25}^{+0.22}$ $-{0.05}_{-0.07}^{+0.07}$ ${4.5}_{-0.8}^{+0.6}$ 74.3 ± 11.1
NGC 3783 $-{1.63}_{-0.48}^{+0.52}$ ${0.23}_{-0.14}^{+0.15}$ ${6.0}_{-1.3}^{+1.9}$ 46.3 ± 12.7
Mrk 1310 $-{0.67}_{-0.41}^{+0.41}$ $-{0.04}_{-0.12}^{+0.12}$ ${4.0}_{-0.7}^{+0.7}$ 85.7 ± 13.9
NGC 4051 $-{0.45}_{-0.38}^{+0.44}$ $-{0.10}_{-0.11}^{+0.13}$ ${2.6}_{-0.9}^{+1.1}$ 8.7 ± 3.3
NGC 4151 $-{2.25}_{-0.46}^{+0.47}$ ${0.41}_{-0.14}^{+0.14}$ ${2.6}_{-0.3}^{+0.4}$ 10.2 ± 1.5
Mrk 202 $-{0.42}_{-0.53}^{+0.65}$ $-{0.11}_{-0.15}^{+0.19}$ ${3.9}_{-1.4}^{+2.2}$ 89.5 ± 41.8
NGC 4253 $-{0.23}_{-3.05}^{+3.05}$ $-{0.16}_{-0.86}^{+0.86}$ ${9.0}_{-1.7}^{+2.3}$ 89.8 ± 20.3
PG 1229+204 $-{1.13}_{-0.40}^{+0.66}$ ${0.09}_{-0.12}^{+0.19}$ ${30.6}_{-12.4}^{+22.4}$ 419.3 ± 237.9
NGC 4593 $-{0.95}_{-0.63}^{+0.64}$ ${0.04}_{-0.18}^{+0.18}$ ${3.6}_{-0.6}^{+0.7}$ 23.6 ± 4.4
NGC 4748 $-{0.42}_{-0.49}^{+0.42}$ $-{0.11}_{-0.14}^{+0.12}$ ${7.1}_{-2.9}^{+2.1}$ 82.8 ± 28.8
PG 1307+085 $-{0.58}_{-0.44}^{+0.36}$ $-{0.07}_{-0.13}^{+0.10}$ ${122.7}_{-54.1}^{+41.8}$ 1165.7 ± 455.9
Mrk 279 $-{0.40}_{-0.31}^{+0.31}$ $-{0.11}_{-0.09}^{+0.09}$ ${21.8}_{-5.1}^{+5.1}$ 137.2 ± 32.0
PG 1411+442 $-{0.61}_{-0.52}^{+0.52}$ $-{0.06}_{-0.15}^{+0.15}$ ${141.3}_{-70.1}^{+69.3}$ 1038.8 ± 512.7
PG 1426+015 $-{0.97}_{-0.53}^{+0.50}$ ${0.05}_{-0.15}^{+0.14}$ ${85.1}_{-33.2}^{+26.8}$ 559.4 ± 197.3
Mrk 817 $-{0.64}_{-0.67}^{+0.74}$ $-{0.05}_{-0.19}^{+0.21}$ ${22.2}_{-7.5}^{+11.0}$ 143.1 ± 59.7
Mrk 290 $-{0.81}_{-0.15}^{+0.16}$ ${0.001}_{-0.05}^{+0.05}$ ${8.7}_{-1.0}^{+1.2}$ 101.7 ± 13.0
PG 1613+658 $-{0.17}_{-0.56}^{+0.56}$ $-{0.18}_{-0.16}^{+0.16}$ ${60.8}_{-23.0}^{+22.7}$ 515.3 ± 194.1
PG 1617+175 $-{0.87}_{-0.59}^{+0.56}$ ${0.02}_{-0.17}^{+0.16}$ ${68.3}_{-32.2}^{+28.3}$ 773.7 ± 342.5
PG 1700+518 ${0.50}_{-0.76}^{+0.76}$ $-{0.37}_{-0.21}^{+0.22}$ ${590.8}_{-91.2}^{+107.8}$ 4894.0 ± 824.1
3C 390.3 $-{0.97}_{-1.00}^{+1.09}$ ${0.05}_{-0.28}^{+0.31}$ ${40.0}_{-15.3}^{+24.9}$ 207.4 ± 104.3
NGC 6814 $-{1.95}_{-0.48}^{+0.48}$ ${0.32}_{-0.14}^{+0.14}$ ${3.1}_{-0.4}^{+0.4}$ 20.0 ± 2.7
Mrk 509 $-{0.87}_{-0.12}^{+0.12}$ ${0.02}_{-0.04}^{+0.04}$ ${76.5}_{-5.2}^{+5.9}$ 312.7 ± 22.6
PG 2130+099 ${1.17}_{-0.15}^{+0.15}$ $-{0.56}_{-0.05}^{+0.05}$ ${34.9}_{-4.4}^{+4.4}$ 266.8 ± 33.4
NGC 7469 ${0.51}_{-0.25}^{+0.35}$ $-{0.37}_{-0.07}^{+0.10}$ ${25.5}_{-3.1}^{+8.0}$ 106.8 ± 23.2
PG 1211+143 ${0.01}_{-0.41}^{+0.27}$ $-{0.23}_{-0.12}^{+0.08}$ ${159.7}_{-71.7}^{+43.6}$ 868.9 ± 313.6
PG 0844+349 ${0.03}_{-0.46}^{+0.47}$ $-{0.24}_{-0.13}^{+0.13}$ ${55.8}_{-23.2}^{+23.7}$ 426.6 ± 179.0
NGC 5273 $-{2.12}_{-0.69}^{+0.55}$ ${0.37}_{-0.20}^{+0.16}$ ${0.9}_{-0.7}^{+0.5}$ 9.4 ± 6.0
Mrk 1511 $-{0.43}_{-0.17}^{+0.18}$ $-{0.11}_{-0.05}^{+0.05}$ ${7.3}_{-1.0}^{+1.1}$ 97.5 ± 14.7
KA 1858-4850 $-{0.05}_{-0.19}^{+0.17}$ $-{0.21}_{-0.06}^{+0.05}$ ${22.1}_{-3.8}^{+3.3}$ 516.2 ± 82.6
MCG 6-30-15 $-{1.94}_{-0.66}^{+0.67}$ ${0.32}_{-0.19}^{+0.19}$ ${2.7}_{-0.8}^{+0.9}$ 48.5 ± 14.7
UGC 06728 $-{0.23}_{-0.52}^{+0.46}$ $-{0.16}_{-0.15}^{+0.13}$ ${2.0}_{-1.2}^{+1.0}$ 21.1 ± 11.3
MCG +08-11-011 $-{0.14}_{-0.17}^{+0.17}$ $-{0.19}_{-0.05}^{+0.05}$ ${24.3}_{-0.8}^{+0.8}$ 164.0 ± 5.3
NGC 2617 $-{1.10}_{-0.36}^{+0.33}$ ${0.08}_{-0.11}^{+0.10}$ ${3.5}_{-1.1}^{+0.9}$ 34.0 ± 9.7
3C 382 $-{1.02}_{-0.17}^{+0.28}$ ${0.06}_{-0.06}^{+0.08}$ ${35.1}_{-3.2}^{+6.9}$ 376.6 ± 54.6
Mrk 374 $-{0.16}_{-0.20}^{+0.35}$ $-{0.18}_{-0.06}^{+0.10}$ ${22.5}_{-5.0}^{+8.8}$ 189.7 ± 58.3
Lu et al. (2016)
NGC 5548 $-{1.19}_{-0.20}^{+0.25}$ ${0.11}_{-0.06}^{+0.08}$ ${5.6}_{-0.3}^{+1.0}$ 34.7 ± 4.1
Zhang et al. (2019)
3C 273 ${1.12}_{-0.08}^{+0.07}$ $-{0.54}_{-0.03}^{+0.03}$ ${514.1}_{-42.4}^{+29.1}$ 1380.8 ± 96.0

Note. Columns are as follows. (1) Object name. (2) Dimensionless accretion rate. (3) Deviation of the expected ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ estimated from Equation (9). (4) Time delay corrected by the dimensionless accretion rate in units of days. (6) Luminosity distance in units of Mpc.

Download table as:  ASCIITypeset images: 1 2 3

Figure 5.

Figure 5. The ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation with time delay corrected by the dimensionless accretion rate effect. Red triangles correspond to the SEAMBH sample, green squares correspond to the SSDS-RM sample, blue circles correspond to the Bentz collection, and yellow pentagons mark the position of NGC 5548 and 3C 273. The open black pentagon corresponds to NGC 5548. The dashed black line corresponds to the expected ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation from Bentz et al. (2013).

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3.4. Is There a Break in $\dot{{\mathscr{M}}}$ = 3 for the ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ Behavior?

As we show in the previous section, the relation between ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ and the dimensionless accretion rate (or Eddington ratio) can be represented by a linear fit, independent of the virial factor. However, Du et al. (2015, 2018) argued that around $\dot{{\mathscr{M}}}$ = 3, there is a break in the behavior of ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$, where highly accreting sources would be characterized by optically thick and geometrically slim accretion (Wang et al. 2014c). Considering the deviation of the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation, sources with $\dot{{\mathscr{M}}}$ < 3 would be associated with ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ ∼ 0, while sources with $\dot{{\mathscr{M}}}$ > 3 would show ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ with a decreasing trend as a function of $\dot{{\mathscr{M}}}$. This interpretation should correspond to the relation ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$$\dot{{\mathscr{M}}}$ assuming fBLR = 1 (left panel of Figure 3), which was analyzed by Du et al. (2015, 2018). However, even in this case, there is a significant difference in our analysis that comes from the location of the SDSS-RM sample in the diagram. Du et al. (2018) included this sample in their analysis, but they used the MBH estimated from Grier et al. (2017), who adopted fBLR = 4.47, adequate for an MBH estimation based on ${\sigma }_{\mathrm{line},\mathrm{rms}}$ (Woo et al. 2015). In our estimation, some SDSS-RM objects are located around $\dot{{\mathscr{M}}}$ = 3, covering the empty region shown in their Figure 3. In order to get a possible difference between the sources with $\dot{{\mathscr{M}}}$ < 3 and >3, we perform a two-sample Kolmogorov–Smirnov (K-S) test. We find a value of 0.344 with a probability of ${p}_{\mathrm{KS}}\sim 0.003$. A similar pKS is reported by Du et al. (2015) that, according to them, is enough to demonstrate that ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ ∼ 0 for $\dot{{\mathscr{M}}}$ < 3. If we apply the K-S test for ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ with fBLR = 1, we get a value of 0.392 and pKS = 0.0004, which favors the difference at $\dot{{\mathscr{M}}}$ = 3. On the other hand, if we consider a virial factor anticorrelated with the FWHM of Hβ, ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ decreases progressively as a function of ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ or ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}^{{\rm{c}}}$ (Figure 4). It is confirmed by the K-S test; we get 0.771 with pKS = 2.9 × 10−11 and 0.663 with pKS = 1.8 × 10−9 for ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}^{{\rm{c}}}$, respectively.

In all four cases, there is a different behavior around $\dot{{\mathscr{M}}}$ = 3. For all cases, the ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ median is 0.09 for $\dot{{\mathscr{M}}}$ < 3 (or ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ < 0.2); however, the scatter is higher with a virial factor equal to 1. For the high accretion rate, the ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ median is 0.26 and 0.31 for $\dot{{\mathscr{M}}}$ and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ and 0.61 and 0.50 for ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}^{{\rm{c}}}$, respectively. However, from Figure 2, we see that very low accretion objects have ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ > 0 for a virial factor anticorrelated with the FWHM. As we have shown in the previous section, we can represent the relation between ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ and accretion parameters by a linear fit in the whole log space without any break, which is supported by the Pearson coefficient and rms value. We do not see any evidence of a break around $\dot{{\mathscr{M}}}$ = 3, especially in the cases with a virial factor anticorrelated with the FWHM of Hβ.

The virial factor is one of the most important uncertainties in the black hole mass determination and accretion parameters, as is emphasized in Sections 5.1 and 5.2. According to Mejía-Restrepo et al. (2018), the virial factor fBLRc includes a correction for the orientation effect, then ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$ would show an accurate estimation that is reflected in the scattering of the measurement, particularly when it is compared with the other parameters. However, their results are based on a Shakura–Sunyaev (SS) disk (Shakura & Sunyaev 1973), which is appropriate for their sample, where ∼90% of the objects show a low accretion rate, and they can be perfectly presented by an SS model disk (Capellupo et al. 2016). One-third of our sample shows a high accretion rate ($\dot{{\mathscr{M}}}$ ≳ 3) and, according to Wang et al. (2014c), in high accretors, the slim disk produces an anisotropic radiation field, which divides the BLR into two regions with distinct incident ionizing photon fluxes. Using the code BRAINS, Li et al. (2018) demonstrated that two-region model is better than a simple one for Mrk 142, a typical high accretor source. Therefore, the incident radiation flux and geometry are more complex in highly accreting AGNs. New spectral energy distribution models for the slim disk are required in order to get a better estimation of the virial factor for this kind of object.

3.5. Relation between Fvar and Accretion Parameters

Studies of large quasar samples showed that the continuum amplitude of the variability is anticorrelated with the Eddington ratio (Wilhite et al. 2008; MacLeod et al. 2010; Simm et al. 2016; Rakshit & Stalin 2017; Li et al. 2018; Sánchez-Sáez et al. 2018). Here Fvar measures the excess of variability above the noise level and can be used as an estimator of this effect. As we showed in the previous section, ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ is anticorrelated with the dimensionless accretion rate and Eddington ratio. In Figures 3 and 4, we show the change of Fvar along the relation ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$$\dot{{\mathscr{M}}}$ and ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ using different virial factors. In all cases, the minimum Fvar at 5100 Å values tends to be associated with the highest $\dot{{\mathscr{M}}}$ (and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$) and smallest ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$ values.

Sánchez-Sáez et al. (2018) reported that the amplitude of variability A is strongly related to σrms (Sánchez et al. 2017), which is the square of Fvar. Estimating σrms, we compute the Spearman coefficient (${\rho }_{s}$) in order to confirm the relation between the accretion parameters and variability. The stronger relation is given by $\dot{{\mathscr{M}}}$ and ${\dot{{\mathscr{M}}}}^{{\rm{c}}}$, with ${\rho }_{s}=-0.397$ (p = 7.9 × 10−6) and ρs = −0.374 (p = 1.6 × 10−5), respectively. Spearman coefficients for ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ and ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}^{{\rm{c}}}$ are −0.341 (p = 1.8 × 10−4) and −0.259 (p = 1.8 × 10−3), respectively. Sánchez-Sáez et al. (2018) reported a Spearman coefficient for ${L}_{\mathrm{bol}}/{L}_{\mathrm{Edd}}$ of ${\rho }_{s}=-0.22$ (p = 1 × 10−8), which is comparable to the value found by us. The dimensionless accretion rate seems to be more strongly related to the other physical parameters (e.g., Fvar and ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$) than the Eddington ratio, which is probably linked with the bolometric luminosity uncertainties.

According to Allevato et al. (2013), Fvar is strongly affected by biases in, for example, the structure of variability or length of the light curve; therefore, it has to be treated with caution. In our sample, some of the SDSS-RM objects were observed in the red edge of the spectrum, where the telluric lines are difficult to remove, and considering the short cadence of the light curve, it could also affect the relation. However, under the proper observational conditions, Fvar could be another of the possible variability parameters, giving information about the physical properties of the AGN. Surveys such as the Large Synoptic Survey Telescope (LSST; Ivezić et al. 2019) will be able to estimate this parameter for a large quasar sample, and, following relations like those presented in this work, this can provide information about the accretion disk structure, accretion process, and size of the BLR. A multivariate analysis is needed to get a correct relation between the Fvar (or σrms) and the dimensionless accretion rate, which is outside the scope of this work.

4. Hubble Diagram

We now perform a simple test of the prospects for quasar application for cosmology by locating the sources on the Hubble diagram. Now we only use their measured time delay (τobs and τcorr) and the observed flux at 5100 Å rest frame (F5100). We use Equation (7) to determine L5100 and finally to measure the luminosity distance, DL,

Equation (11)

The left panel of Figure 6 shows the luminosity distance estimated with τobs, which exhibits large scatter. We now take all objects from our sample plotted in Figure 5 and assume that they precisely follow the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation while we relax the assumption that their absolute luminosity L5100 is known. Repeating the same exercise, we find that the scatter is strongly reduced (see right panel of Figure 6). This is better shown in the corresponding bottom panels, where we plot the residuals between the logarithm of the expected (DL,mod) and estimated (DL) luminosity distance.

Figure 6.

Figure 6. Hubble diagram before (left) and after (right) the correction by dimensionless accretion rate. Symbols and colors are the same as in Figure 5. The black lines indicate the expected luminosity distance based on the standard ΛCDM model. In both cases, the bottom panel shows the difference between the expected luminosity distance and the observed one.

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It is clear that the dispersion decreases after the correction, which is supported by the rms value (0.287 versus 0.182). Here plotted uncertainties come only from the uncertainty in the time delay measurement. As a guide, in both panels, we plot the standard ΛCDM model with the parameters (Planck Collaboration et al. 2014) H0 = 67 km s−1 Mpc−1, ΩΛ = 0.68, Ωm = 0.32 (black lines in Figure 6). We see that while in the left panel, a significant fraction of points implied too-small distances, after the accretion rate–dependent correction, the points are distributed close to the line.

To demonstrate this quantitatively, in Figure 7, we give the distribution of the log $\tfrac{{D}_{{\rm{L}},\mathrm{mod}}}{{D}_{{\rm{L}}}}$. The distribution before the correction shows clear asymmetry to the right, and it is centered at 0.123. After applying the correction, the distribution is centered at 0.055. The standard deviation also shows an improvement (0.19 versus 0.31). With this information, we can think of constraining the cosmological parameters.

Figure 7.

Figure 7. Distribution of the difference between the logarithm of the expected luminosity distance (log $\tfrac{{D}_{{\rm{L}},\mathrm{mod}}}{{D}_{{\rm{L}}}}$) with respect to that obtained from the observations before (gray) and after (blue) correction. Vertical dashed gray and blue lines correspond to the average (thick) and ±1σ values (thin) before and after correction, respectively. The vertical dotted black line marks log$\tfrac{{D}_{{\rm{L}},\mathrm{mod}}}{{D}_{{\rm{L}}}}=0$.

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In order to better illustrate the accuracy of the determination of the cosmological parameters, we performed formal computations of the best cosmological model. We assumed a standard ΛCDM model, and the value of the Hubble constant, H0 = 67 km s−1 Mpc−1, is used in the computations of corrections related to the accretion rate (see Section 3.3). We did not modify the parameters in Equation (7) relating to the time delay and absolute luminosity. Then we searched for the minimum of the function

Equation (12)

where N is the total number of sources in the sample, and bi is the relative error in the luminosity distance determination implied by the uncertainty in the measured time delay. We introduced a quantity σ following the approach by Risaliti & Lusso (2015). This quantity describes the dispersion in the sample, which is larger than the claimed measurement errors. The result is shown in Figure 8 (left panel). The best fit is on the edge of the domain (minimum χ2); however, it is consistent with the standard cosmology, and the accepted parameter values are consistent with our results within 2σ. The errors are still large, due to the limited number of objects (117 in the full sample) and possibly also the heterogenic way the data reduction time delays were measured by various authors using different methods. We checked whether we can improve the constraints by using only higher-redshift sources, z > 0.4 (30 sources; right panel of Figure 8), but this caused the large shift of the best fit (from Ωm = 1.0, ΩΛ = 1.34 to Ωm = 0.4, ΩΛ = 0.1), and the error contours were then even larger due to the reduced number of objects.

Figure 8.

Figure 8. The χ2 behavior in the Ωm–ΩΛ space for the full sample (left panel) and the selected sources with only z > 0.4 (right panel). In both panels, blue and green contours correspond to 1σ and 2σ confidence levels, respectively. The yellow symbol marks the minimum χ2 value, in both cases at the edge of the domain.

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The effective use of the method requires an increase of the number of reverberation-measured objects by a factor of at least 5. There are some prospects for new time delay measurements, particularly at larger redshifts. First, the SDSS-RM campaign continues. Second, the project of monitoring 500 quasars with the Oz-DES survey (King et al. 2015) is likely to finish soon. Thus, the method itself looks quite promising.

5. Discussion

One of the most critical points of the reverberation mapping technique is the uncertainty around the black hole mass determination, which depends on parameters like virial factor or inclination angle. The method proposed in this paper is strongly dependent on these two parameters, and a change in them affects the approach to correct the time delay by the accretion rate effect. All of these problems are reflected in the large uncertainties associated with the cosmological parameter determination (see Section 4).

Over the years, type 1a supernovae have also been corrected by uncertainties in some physical properties like mass, peculiar velocity, redshift, etc. Sophisticated statistical methods (e.g., Scolnic et al. 2018) have been applied in order to decrease the uncertainty of these parameters, resulting in accurate cosmological estimations. In future, these kind of methods must be implemented for quasars as well.

We discuss the most critical points of the virial factor and inclination angle, which would be resolved with the arrival of new data, instruments, and improvements in the methods in the following.

5.1. Virial Factor Remarks

It is clear that the selection of the virial factor anticorrelated with the FWHM of the line has an implication for the correction proposed for the observed time delay. As we previously argued, of both virial factors analyzed in this work, the best is the one proposed by Mejía-Restrepo et al. (2018). It is not the first time that a virial factor anticorrelated with the FWHM has been proposed (e.g., Collin et al. 2006; Storchi-Bergmann et al. 2017). However, there are some caveats to consider under this assumption.

Mejía-Restrepo et al.'s (2018) sample includes 37 AGNs at z ∼ 1.5, with 1600 km s−1 < FWHM < 10,100 km s−1 and a median value of ∼4700 km s−1. Only 16% of the sample shows FWHM < 2000 km s−1. On the other hand, our sample includes sources with 780 km s−1 < FWHM < 10,400 km s−1 with a median value of 3000 km s−1, where ∼31% of the sample shows FWHM < 2000 km s−1. It indicates that our sample has an overrepresentation of narrow profiles compared with the ones shown by Mejía-Restrepo et al.'s (2018) sample. The narrow FWHM regime is populated mainly by the super-Eddington sources (Du sample), which are relatively new in the AGN analysis. The scarce represented narrow profiles in the Mejía-Restrepo et al. (2018) analysis have a direct effect on the exponent in the anticorrelation with the FWHM. Recently, Yu et al. (2019) performed a new analysis following the formalism proposed by Collin et al. (2006) in order to estimate the virial factor and MBH. Their sample includes 26% of the narrow profiles and finds an anticorrelation given by fBLR ∝ FWHM−1.11, very close to the one proposed by Mejía-Restrepo. This confirms the anticorrelation between the virial factor and the FWHM of the line and suggests that the variation in the exponent is not so large when the number of narrow profiles increases. However, it still has to be tested.

Woo et al. (2015) calibrated the virial factor using the relation MBHσ* for 93 narrow-line Seyfert 1 galaxies (NLS1s) and 29 reverberation-mapped AGNs (where only one-third of the sample is NLS1s), obtaining a value of fBLR ∼ 1.12. This virial factor is basically the same as the one used to estimate MBH and $\dot{{\mathscr{M}}}$ in Figures 1 and 3, respectively, which show a large scatter with respect to the one estimated from the fBLRc. The large scatter around them could be related to an effect of the inclination angle that, according to Peterson et al. (2004), strongly affects the FWHM measurements.

We performed a test to estimate the average fBLR in our sample. We independently estimate the MBH from the MBHσ* relation (Gültekin et al. 2009) for 15 sources from the Bentz collection and 25 sources from Grier et al. (2017) that have stellar velocity dispersion measurements. We consider the centroid of the σ* distribution obtained for this subsample, i.e., $\mathrm{log}\sigma =2.142\pm 0.173$. Then, using Equation (3) in Gültekin et al. (2009), we derive the average MBH. We use the mean of the τobs measurements for this subsample and the MBH as obtained from the previous step and substitute in Equation (1) to get an average fBLR–FWHM relation, i.e., $\mathrm{log}\overline{{f}_{\mathrm{BLR}}}\,\approx 6.667-2$ log FWHM. The τobs measurements are taken from Table 1.

Considering the centroid of the FWHM distribution for this subsample, i.e., ∼4000 km s−1, we get an fBLR that is substantially smaller, i.e., ∼0.29. We estimate the fBLR for a representative FWHM = 2000 km s−1, which is ∼1.16, while it is relatively higher for cases with lower FWHM (e.g., Mrk 493 has FWHM ≈ 778 km s−1, which would give fBLR ∼ 7.67). This exercise already indicates the importance of a variable fBLR and how it can affect the MBH estimates that are derived using the virial relation. The fBLR depends on the inclination angle, as well as on the gas distribution. A case-by-case study is needed to estimate the fBLR, since it is quite evident from this study, as well as many previous works (Collin et al. 2006; Panda et al. 2019), that a constant, singular value of fBLR cannot explain and should not to be assumed for all sources.

5.2. Inclination Angle Remarks

One of the most important parameters included in the virial factor is the inclination angle. In this work, we are assuming an angle of θ ∼ 40° for the dimensionless accretion rate estimation (Equation (3)), which is a typical value for the type 1 AGN. However, this generalization can overestimate the $\dot{{\mathscr{M}}}$ value in some objects.

Storchi-Bergmann et al. (2017) estimated and collected the inclination angle for a sample of double-peak Hα AGNs, where seven sources of our sample are included. These objects are marked in the last column of Table 1. They estimate a range for the inclination angle of 17° < θ < 38°, with an average value of θ ∼ 27°. This implies a variation in MBH and accretion rate estimations by an order of 3 and 2, respectively, in seven sources of our sample.

According to the model assumed by Storchi-Bergmann et al. (2017), the inclination angle is correlated with FWHM and anticorrelated with the virial factor. It has been suggested by Collin et al. (2006) as well. It means that narrow profiles correspond to low inclination angles and high virial factors. Since one-third of our sample shows FWHM < 2000 km s−1, this suggests that 30% of the sample should have angles θ < 40°.

Recently, Negrete et al. (2018) constrained the spectroscopic behavior of the super-Eddington sources in the optical regime, which show FWHM < 4000 km s−1 and inclination angles of θ ∼ 20°. Following the formalism proposed by Marziani & Sulentic (2014), Negrete et al. argued that these sources can be used as standard candles. In order to decrease the scatter in the Hubble diagram, they proposed a correction for the inclination effects based on the virial luminosity (estimated from the FWHM) and cosmological distance (estimated by the redshift of the source). With this correction, they obtained a correction in the luminosity distance of 0.02–0.08 mag, which is promising. However, this formalism is only valid for the sources radiating close to the Eddington limit and cannot apply to the rest of the AGN populations.

One clear example of the uncertainties in the virial factor and inclination angle is coming from the novel results provided by Gravity Collaboration et al. (2018). They estimated an angle for 3C 273 of θ ∼ 12°. It is a high-Eddington source; therefore, the angle estimated is in concordance with the one estimated for this kind of population by Negrete et al. (2018). On the other hand, using Equation (2) of Mejía-Restrepo et al. (2018), the virial factor is 4.6, considering a ratio H/R = 0.1, which is almost a factor of 3 larger than that used for the estimation reported in this paper (fBLRc ∼ 1.45). Additionally, the Gravity results favor a very thick BLR (the opening angle of the torus is 45°, implying H/R = 1.0), well outside the range favored statistically by Mejía-Restrepo et al. (2018).

Another example is NGC 5548, which has been monitored for almost 40 yr, showing a change from Seyfert 1 to Seyfert 1.8. The FWHM of Hβ varied from 4000 to 10,000 km s−1. Assuming that black hole mass and inclination angle have a slow variation, the big changes in the source can be attributed to the accretion rate (Bon et al. 2018). However, they are not significant enough to change from the sub- to super-Eddington regime. In general, NGC 5548 is not following the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation; it shows a steeper slope than 0.5 (Peterson et al. 2004) but within the uncertainties of the relation. Pancoast et al. (2014) performed a dynamical modeling of the BLR in NGC 5548 that does not require a virial factor. They assumed an inclination angle θ = 38fdg8 and found MBH = ${3.39}_{-1.49}^{+2.87}\times {10}^{7}$ M. This result is in agreement with the one obtained from reverberation mapping using the dispersion of the line in the rms spectrum and a virial factor of 5.5. It supports the analysis that indicates that ${\sigma }_{\mathrm{line},\mathrm{rms}}$ is less affected by inclination than FWHM (Peterson et al. 2004; Collin et al. 2006).

Determination of the best angle for the presented sample is complicated due to the diversity of properties observed in the sample. The variable FWHM seems to be the best option, as it apparently includes the variation of the inclination angle. However, more analysis with homogeneous samples is still needed in order to clarify the convolution between virial factor and inclination angle and the related uncertainties.

5.3. Luminosity Distance Remarks

The estimation of the distance to the astronomical sources is fundamental for cosmology. One of the most important results of the reverberation mapping technique is an independent estimation of the luminosity distance. As we show, the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation is not followed by the super-Eddington sources, and a correction is required (Equation (10)). However, as is emphasized in Sections 5.1 and 5.2, this correction is strongly affected by uncertainties in the virial factor and inclination angle. All of these uncertainties are reflected in the estimation of the luminosity distance and the determination of the cosmological constants. Water masers or torus diameter estimation could provide accurate measurements of the luminosity distance (Humphreys et al. 2013; Hönig et al. 2014); however, the scarcity of water masers and the required long time for the monitoring limit the feasibility of these methods.

The luminosity distance has been estimated by remarkable methods in two of our sources: NGC 4151 and 3C 273. Since the dusty torus is larger by a factor of 4 than the BLR, it is relatively easily resolved by the optical long-baseline interferometers. On the other hand, due to the dust response to the continuum variations, the distance from the central continuum to the dusty torus can be estimated by the reverberation mapping method. Combining these two techniques, Hönig et al. (2014) estimated a distance to NGC 4151, DL = ${19.0}_{-2.6}^{+2.4}$ Mpc, which is in agreement with the one reported by Tsvetkov et al. (2019) using supernovae. They also reported a virial factor value of $5.2\lt {f}_{\mathrm{BLR}}^{\mathrm{dust}}\lt 6.5$. Before and after application of the correction related to accretion rate, we obtain a luminosity distance of 12.9 ± 1.5 and 10.2 ± 1.5 Mpc, respectively. It indicates an underestimation in the luminosity distance by 0.27 dex compared to the dust-parallax method. This difference is related to the large uncertainty associated with the black hole mass. Combining reverberation-mapped results from optical and ultraviolet emission lines, Bentz et al. (2006) found a weighted mean MBH for NGC 4151 of ${4.57}_{-0.47}^{+0.57}\times {10}^{7}\,{M}_{\odot }$, which, compared to the results of the MBHσ* relation, is underestimated by a factor of 7, indicating a big uncertainty in the reverberation-based masses determination.

The first quasar where the linear and angular size of the BLR have been measured is 3C 273 (Gravity Collaboration et al. 2018; Zhang et al. 2019). Both results provide a size of the BLR of ∼145 light days. Recently, Wang et al. (2019) joined both techniques in order to determine the cosmological distance. The novelty of the method is the distance determination without invoking calibrations through known cosmic ladders. They determined a distance of ${551.5}_{-78.7}^{+97.3}$ Mpc within 15% of the average accuracy. Before and after application of the correction related to accretion rate, we obtain a distance of 394 and 1381 Mpc, respectively, an order of 0.4 dex.

The information provided by NGC 4151 and 3C 273 is an indication of the uncertainties associated with the present method and the limitation of their use in cosmology. More observations are required in order to test and improve the correction based on the accretion parameters. The arrival of novel and sophisticated results, like Gravity Collaboration et al. (2018), will provide information that helps us to improve the use of quasars in cosmology and also determine the origin of the uncertainties associated with the classical methods like reverberation mapping.

6. Conclusions

In this work, we confirmed that the time delay measured during the reverberation mapping campaigns is affected by the accretion rate of individual sources. Considering the deviation from the ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ relation and the corresponding accretion rate, we propose a correction based on ${\rm{\Delta }}{R}_{{\rm{H}}\beta }$, which is a power-law function of the dimensionless accretion rate parameter. This correction recovers the expected time delay, decreasing the scatter and providing a proper estimation of the BLR size. Using the corrected values, we built the Hubble diagram, obtaining consistent results with the ΛCDM model within the 2σ confidence level. However, the uncertainties are still large, which could be mitigated by significantly increasing the number of sources, especially toward larger redshifts.

We used the dimensionless accretion rate and the Eddington ratio to estimate the effect of the accretion rate. The former appears to show a better correlation with other physical quantities, which could be related to large uncertainties associated with the bolometric luminosity. We also explore the use of a virial factor anticorrelated with the FWHM of the Hβ line (Mejía-Restrepo et al. 2018), which is in agreement with the one found by Yu et al. (2019). The black hole mass and accretion parameters give a lower dispersion in comparison with the case fBLR = 1. Since the virial factor anticorrelated with the FWHM includes the correction for the source orientation, it can explain the lower scatter. However, the virial factor used needs a more detailed analysis to confirm the use of this value, especially for the highly accreting objects.

In addition, we also confirm the anticorrelation between the continuum variability and the accretion parameters, using the parameter Fvar. Although Fvar is affected by the atmospheric conditions and the quality of observations, it shows the same behavior as in similar parameters, such as the variability amplitude. Large surveys such as LSST will observe this kind of property, and it is important to establish the relation with other physical parameters. This result supports that the accretion parameter (the Eddington ratio or the dimensionless accretion rate) is the main driver of many of the quasar properties (Marziani et al. 2001; Shen & Ho 2014), such as variability or outflows. It could be linked to a different type of accretion disk structure (Wang et al. 2014c).

There are large uncertainties associated with the proposed method in this work. The determination of the virial factor and inclination angle is essential for the black hole mass determination and accretion rate, and it is still an open problem in the AGN field. The necessity to include the broad range of AGN properties (like FWHM, accretion rate, orientation angle, and redshift) in the modeling of these key parameters is still a pending task. All of these uncertainties are also reflected in the luminosity distance. A comparison with independent methods for two sources shows a difference of 0.27 and 0.4 dex. These uncertainties cannot be immediately diminished, but, probably with the arrival of new data and novel and sophisticated techniques, they can permit us to calibrate the results from reverberation mapping, and we can improve their use for cosmology purposes.

We thank the referee for valuable suggestions that helped to improve the paper. The project was partially supported by National Science Centre, Poland, grant No. 2017/26/A/ST9/00756 (Maestro 9) and MNiSW grant DIR/WK/2018/12. V.K. acknowledges Czech Science Foundation No. 17-16287S. We acknowledges P. Du, Y.-R. Li, and J.-M. Wang for the provided data and comments that improved the paper. We acknowledge M. Bentz, C. J. Grier, J. Kuraszkiewicz, A. del Olmo, M. Fausnaugh, J. Mejía-Restrepo, and Y. Shen for the extra information required for the development of this work.

Appendix: Monte Carlo Simulations of the SDSS-RM Setup

The monitoring presented in Grier et al. (2017) is relatively short, taking into account rather high redshifts and luminosities of the sources. Therefore, we performed Monte Carlo simulations with the aim of checking independently whether the observational setup forces the measured time delays to be shorter than otherwise expected for a given source redshift and luminosity.

For this purpose, we simulated each source independently, taking into account its monochromatic luminosity, L5100, and redshift. For each source, we first created 100 artificial dense light curves using the Timmer & Koenig (1995) algorithm. We model the overall power density spectrum (PDS) shape assuming a power-law shape with two breaks and three slopes. The high-frequency slope was taken as 2.5 following Kepler results for quasars from Mushotzky et al. (2011). The high-frequency break was set at 200 days for all sources as a mean value taken from Simm et al. (2016). The slope of the middle part of the PDS was taken as s1 = 1.2 (Czerny et al. 1999; Simm et al. 2016). The low-frequency break was fixed somewhat arbitrarily at the value 10 times lower than the high-frequency break, and the low-frequency slope was assumed to be zero. We then exponentiated the resulting light curve following Uttley et al. (2005), since this reproduces the log-normal distribution characteristic for the light curves of accreting sources.

The light curve describing the emission line was generated from the dense light curve above describing the continuum by shifting it by the delay expected from Equation (7) and smearing it with a Gaussian of the width equal to 0.1 of the expected time delay. Next, a continuum and line light curve were created out of the dense light curve adopting the cadence in the SDSS-RM monitoring (32 observations, separated as indicated by Figure 2 in Grier et al. (2017), and sent to us by the authors). After correcting the cadence for the redshift of a given source, we perform simulations in the rest frame of each source. For each of the 100 random realizations of the process, we now calculate the time delay using the interpolated cross-correlation function. Finally, from these 100 realizations, we calculate the mean time delay and the dispersion. In Figure 9, we compare the time delay from our Monte Carlo simulations with the time delay expected from Equation (7) and used in the simulations. We see that the dispersion in the time delay obtained from the simulations is, in general, higher than the errors quoted by Grier et al. (2017). We see some trend to obtain a somewhat shorter time delay than assumed due to the specific cadence used in the observations. However, for the majority of the sources, the implied underestimation of the BLR radius (${\rm{\Delta }}{R}_{{\rm{H}}\beta }$) is below 0.1, much smaller than the actual departure from the standard ${R}_{{\rm{H}}\beta }\mbox{--}{L}_{5100}$ law and well within the error. Only one source, J141856, is strongly affected by the cadence of the SDSS-RM, and its measured delay is likely much higher than the 15.8 days reported by Grier et al. (2017). This source was not considered in the presented analysis due to the low quality of its spectra, where the Hβ profile is completely destroyed. In our simulations, assuming a delay of 203 days in the quasar rest frame, we obtained a probability of 0.32 to obtain the delay within the upper limit of the delay measured for this source (21.8 days) and a probability of 0.29 to get a delay shorter than the measured value of 15.8 days.

Figure 9.

Figure 9. Estimate of the systematic offset in the measured time delay in the subsample of Grier et al. (2017) due to the cadence. In the case of the four brightest objects, the measured delay is underestimated, but the effect seems very strong only in the case of one object, J141856.

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10.3847/1538-4357/ab3728