adsabs/FOCAL huggingface dataset:
Cold gas kinematics of radio AGNs can tell us about the nature of feedback to their host galaxies. Both, radiative winds from central optical AGN, and radio jets can affect the gas kinematics in host galaxies. In this section, in order to understand the effect of both radiation and jet on gas kinematics, we compare the radio luminosity at 1.4 GHz and [O iii] λ5007 line luminosity (using the line fluxes from MPA-JHU group) for LERGs and HERGs. While radio luminosity at 1.4 GHz can be used as tracer of jet power (Cavagnolo et al. 2010), [O iii] λ5007 line luminosity can be used as a tracer for AGN bolometric luminosity (LaMassa et al. 2010). We find that there exists a weak but significant correlation (Kendall’s tau=0.4, p=2.4 × 10−16) between the radio luminosities and the [O iii] λ5007 line luminosities of LERGs (Fig. 9), which is consistent with earlier studies (Baum & Heckman 1989; Tadhunter et al. 1998), implying a common source of both luminosities. A similar correlation is noticed for HERGs but with higher [O iii] λ5007 luminosity than LERGs for a particular value of radio luminosity, which could mean the extra energy in form of wind-driven by radiation from accretion disc to cause the turbulence in host galaxy. However, in our sample of radio AGNs, while for low radio power ($P_{1.4 \rm GHz}\, \lt $ 1024.3 W Hz−1) LERGs and HERGs, there is almost no difference in distribution of centroid shifts in the absorption profiles relative to the systemic velocity, with all but one within ±200 km s−1, a larger number of intermediate radio power ($P_{1.4 \rm GHz}\, \sim$ 1024.3−1026.0 W Hz−1) LERGs show centroid velocity shifts greater than 200 km s−1 compared to HERGs. Also the range of centroid velocity shift for LERGs is wider (−479 to +356 km s−1) than HERGs. Although, we have doubled the number of detections compared to our previous analysis (Chandola & Saikia 2017), the overall number of sources with H i absorption detections for HERGs used for kinematic analysis is still small. Hence there are large statistical uncertainties to draw a firm conclusion about H i gas kinematics in HERGs as a population.
Citation: Tadhunter et al. 1998
Citation function: Similarities; Compare/Contrast
Let us first define some terminology before describing our results. “Outflow” means the flow with a positive radial velocity vr, including both “turbulent outflow” and “real outflow.” In the former case, the test particle will first move outward but will eventually return after moving outward for some distance. In the latter case, the test particle continues to flow outward and eventually escapes the outer boundary of the simulation domain. “Real outflow” consists of two components, i.e., jet and wind. The jet region is defined as the region occupied by the time-averaged magnetic field lines connected to the ergosphere (described by 






r


erg


≡


r


g


+


1
−


a


2




cos


2


θ





r


g


;


 Visser 2007) of the black hole. We note that this definition coincides with other notions of the jet based on velocity and magnetization, as seen even in early two-dimensional simulations (McKinney & Gammie 2004). Moreover, turbulence tends not to have a strong effect on these field lines, so that in both individual snapshots and a time-averaged sense, the field lines connecting to the ergosphere coincide with β  2 and σ > 1 (McKinney et al. 2012, see Figures 3 and 6). Thus, the jet region is bounded by the magnetic field line whose foot point is rooted at the black hole ergosphere with θ = 90°, i.e., the boundary between the black hole ergosphere and the accretion flow (refer to the red lines in Figure 5). In this case, all magnetic field lines in the jet region are anchored to the black hole ergosphere and thus can extract the spin energy of the black hole via the Blandford & Znajek mechanism (Blandford & Znajek 1977; hereafter BZ77) to power the jet (“BZ-jet”). Real outflows outside of this boundary are powered by the rotation energy of the accretion flow, and we call them wind. Note that our definition of wind adopted here is different from that adopted in some literature, where they require that the Bernoulli parameter of wind must satisfy Be > 0. We do not add this requirement because we find that for a nonsteady accretion flow, Be is not constant along the trajectories but usually increases outward, at least to the radius within which turbulence is well developed (Yuan et al. 2015). We find that even though Be is negative at a small radius, it can become positive when it propagates outward.
Citation: McKinney & Gammie 2004
Citation function: Similarities
The Planck cosmic microwave background (CMB) mission (Planck Collaboration I 2011) has for the first time allowed us to retrieve all-sky maps (Hill & Spergel 2014; Planck Collaboration XXII 2015; Khatri 2016) of the Sunyaev-Zeldovich (SZ) effect (Zeldovich & Sunyaev 1969). The chief advantage of Planck over other past and current satellite and ground-based missions is its multiple frequency channels covering the low-frequency Rayleigh–Jeans as well as the higher frequency Wien region of the CMB spectrum making the separation of the thermal SZ from CMB and foregrounds feasible. As the blackbody photons from the CMB interact with hot intergalactic/intracluster medium (ICM) travelling from the last scattering surface (Peebles & Yu 1970; Sunyaev & Zeldovich 1970) to us, Compton scattering upscatters a fraction of photons to higher energy creating a distortion from the Planck spectrum $I_{\nu }^{\rm Planck}$ (Sunyaev & Zeldovich 1972). The change in the intensity $\Delta I_{\nu }=I_{\nu }-I_{\nu }^{\rm Planck}$ of the CMB radiation is given by (Zeldovich & Sunyaev 1969)

(1)

\begin{eqnarray}
\Delta I_{\nu }=y\frac{2 h\nu ^3}{c^2}\frac{x e^x}{(e^x-1)^2}\left[x\left(\frac{e^x+1}{e^x-1}\right)-4\right],
\end{eqnarray}

where $x=\frac{h\nu }{{{k_{\rm B}}}T}$, T = 2.725(1 + z) is the CMB temperature at redshift z, ν = ν0(1 + z) is the frequency of CMB photon at redshift z, ν0 is the observed frequency today (z = 0), h is the Planck constant, kB is Boltzmann constant and c is the speed of light. The amplitude of the distortion, y, is proportional to the integral of the pressure P along the line of sight,

(2)

\begin{eqnarray}
y=\frac{{{\sigma _{\rm T}}}}{{{m_{\rm e}}}c^2} \int {{\rm d}}s\, {{n_{\rm e}}}{{k_{\rm B}}}{{T_{\rm e}}},
\end{eqnarray}

where Te and ne are the electron temperature and electron number density, respectively, in the ICM plasma, me is the mass of the electron, σT is the Thomson scattering cross-section, and s is the distance coordinate along the line of sight.
Citation: Sunyaev & Zeldovich 1970
Citation function: Background
As expected, the orbital parameters obtained from this fit are fully consistent with those reported in Table 1, since the long baseline of the data set guarantees to clearly disentangle orbital phase modulation from and phase variation due to the NS spin frequency changes. From the best-fitting parameter of each frequency phase component we infer the dipolar magnetic moment μF ≃ 4.1(4) × 1026 and μ1h ≃ 4.1(5) × 1026 G cm3, for the fundamental and the first harmonic, respectively. Adopting the Friedman-Pandharipande-Skyrme (FPS) equation of state (see e.g. Friedman & Pandharipande 1981; Pandharipande & Ravenhall 1989) for a 1.4 M⊙ NS, we estimate an NS radius of R = 1.14 × 106 cm, and a moment of inertia I ≃ 1.45 × 1045 g cm2. This corresponds to an equatorial magnetic field of Beq = μ/R3 = 2.8(3) × 108 ≃ 2.8(3) × 108 G. This value is consistent both with the estimation reported in Sanna et al. (2018d) from spin frequency equilibrium considerations for the X-ray pulsar, and the average magnetic field of known AMXPs (Mukherjee et al. 2015). It is noteworthy that the value of Beq obtained here is likely overestimated due to a non-accurate estimation of mass accretion rate in case of spin-down regime. In fact, as discussed by Kluźniak & Rappaport (2007), in this regime the angular momentum deposited in the disc by the pulsar torques leads to a substantial additional dissipation of energy in the disc, hence, the mass accretion rate estimated from equation (17) results on an upper limit of the quantity. However, since it is not quite clear what fraction of this additional dissipation of energy is released in non-thermal process and what is kept inside the disc, it is complicated to quantify the discrepancy. We started approaching the problem considering the worst case scenario at which the whole spin-down luminosity of the pulsar $I\omega \dot{\omega }$ is transferred and released by the accretion disc. With this hypothesis, we subtract the rotation luminosity from observed luminosity in equation (17) and we then fitted the frequency phase delays. We obtained that, taking into account the correction on the mass accretion rate, the NS magnetic field decreases roughly by 15 per cent, reaching the value Beq = 2.4(4) × 108 G. Both the properties of the source during the outburst and the magnetic field estimation obtained from the studies of the spin-down like behaviour of the phase delays do not seem to suggest IGR J17591–2342 as an exception among the AMXPs.
Citation: Mukherjee et al. 2015
Citation function: Similarities
A current topic of active debate is to what extent galaxies are affected by the assembly history of their host halos. The stochasticity in the complex baryonic physics may act to erase the record of halo assembly history. If, however, the galaxy properties closely correlate with the halo formation history, this would lead to a dependence of the galaxy content on large-scale environment and a corresponding clustering signature. This effect has commonly been referred to as galaxy assembly bias both colloquially and in the literature, and we adopt this distinction here. We stress, however, that what is referred to here is the manifestation of halo assembly bias in the galaxy distribution. The predictions for galaxy assembly bias have been explored with simulated galaxies (Zhu et al. 2006; Croton et al. 2007; Reed et al. 2007; Zu et al. 2008; Zentner et al. 2014; Chaves-Montero et al. 2015; Bray et al. 2016; Romano-Diaz et al. 2017). Detecting (galaxy) assembly bias is much more challenging since halo properties are not directly observed. Observational studies of assembly bias have generally produced mixed results. There have been several suggestive detections in observations (Berlind et al. 2006; Yang et al. 2006; Tinker et al. 2008b, 2017b; Wang et al. 2008, 2013b; Cooper et al. 2010; Lacerna et al. 2014a; Hearin et al. 2015; Watson et al. 2015; Miyatake et al. 2016; Saito et al. 2016; Zentner et al. 2016; Montero-Dorta et al. 2017; Tojeiro et al. 2017), while numerous other studies indicate the impact of assembly bias to be small (Abbas & Sheth 2006; Blanton & Berlind 2007; Croton & Farrar 2008; Tinker et al. 2008a, 2011; Deason et al. 2013; Lacerna et al. 2014b; Lin et al. 2016; Vakili & Hahn 2016; Zu & Mandelbaum 2016; Dvornik et al. 2017). The situation is further complicated as various systematic effects can mimic the effects of assembly bias (e.g., Campbell et al. 2015; Zu et al. 2016; Busch & White 2017; Lacerna et al. 2017; Sin et al. 2017; Tinker et al. 2017a; Zu & Mandelbaum 2017) and the evidence for assembly bias to date remains inconclusive and controversial.
Citation: Zhu et al. 2006
Citation function: Background
Cygnus A, at z = 0.0562, is 10 times closer than the next radio galaxy of similar radio luminosity.4

4
Radio luminosity >1045 erg s−1.
 The nuclear regions in Cygnus A have been observed extensively at radio through X-ray wavelengths (Carilli & Barthel 1996). The inner few arcseconds is a complex mix of optically obscuring dust clouds (Vestergaard & Barthel 1993; Whysong & Antonucci 2004; Lopez-Rodriguez et al. 2014; Merlo et al. 2014), atomic gas seen in narrow line emission (Stockton et al. 1994; Taylor et al. 2003), H i 21 cm absorption toward the inner radio jets, with a neutral atomic column density >1023 cm−2, depending on H i excitation temperature (Struve & Conway 2010), polarized, broad optical emission lines due to scattering by dust (Antonnuci et al. 1994; Ogle et al. 1997), and a highly absorbed hard X-ray spectrum with a total gas column density of ∼3 × 1023 cm−2 (Ueno et al. 1994; Reynolds et al. 2015). VLBI radio observations at 0.05 mas resolution reveal highly collimated jets originating on scales ∼200 times the Schwarzschild radius (Boccardi et al. 2016). Tadhunter et al. (2003), derive a black hole mass of 2.5 ± 0.7 × 109 M⊙ from HST and Keck spectroscopy of Pa-α and [O iii], and conclude that Cygnus A contains an AGN with a bolometric luminosity of order 1046 erg s−1, comparable to high redshift quasars (Runnoe et al. 2012). This AGN is highly obscured in the optical due to dust along our line of sight, with Av > 50 magnitudes, based on near-IR spectroscopy (Imanishi & Ueno 2000). Studies of the mid- to far-IR spectral and polarization properties have led to a model of a clumpy, dusty torus obscuring the AGN in Cygnus A, with a radius of at least 130 pc, although these conclusions are based on spatially integrated properties; these observations did not have the spatial resolution to resolve the torus, and hence are partially contaminated by emission from the radio core-jet (Privon et al. 2012; Lopez-Rodriguez et al. 2018).
Citation: Taylor et al. 2003
Citation function: Background; Background
Citation: Stockton et al. 1994
Citation function: Background; Background
The mass accretion onto the black hole is important for a better understanding of AGN evolution. The Eddington ratio, the ratio between the AGN bolometric luminosity and the Eddington luminosity (Lbol/LEdd), provides insight into the black hole growth because the bolometric luminosity reflects the mass accretion rate. We show AGN bolometric luminosity versus black hole mass for our sample of broad-line AGNs in the different redshift bins in the left panel of Figure 5. The different X-ray surveys are shown with different symbols as labeled. The dotted reference lines indicate constant Eddington ratios of 1, 0.1, 0.01, and 0.001. Our sample of broad-line AGNs covers the black hole mass range 7.0  log MBH/M⊙  9.5 and the bolometric luminosity range 43  log Lbol  47 with a wide dispersion in the Eddington ratio distribution. For comparison, we show published observations in the same redshift range from the literature in the right panel of Figure 5 (Gavignaud et al. 2008; Merloni et al. 2010; Shen et al. 2011; Nobuta et al. 2012; Matsuoka et al. 2013). The SDSS quasar sample (gray points; Shen et al. 2011) is limited to the high-mass and high-luminosity regime because the SDSS detection limit corresponds to a luminosity of log Lbol ∼ 46 at z ∼ 1. Compared to the SDSS quasar sample, our sample of broad-line AGNs shows a wider dispersion in the black hole mass, AGN bolometric luminosity, and Eddington ratio distribution, consistent with previous studies on deep AGN samples (Gavignaud et al. 2008; Merloni et al. 2010; Nobuta et al. 2012; Matsuoka et al. 2013), which fill in the low-mass and low-luminosity region. The figure shows contours at the 1σ level, together with the literature data, except the SDSS quasar sample. The figure also reveals that only a small number of AGNs exceed the Eddington limit by a small amount. AGNs with similar black hole masses show a broad range of bolometric luminosities spanning about two orders of magnitude, indicating that the accretion rate of black holes is widely distributed. This suggests that the AGN cosmic downsizing phenomenon could be explained by some more-massive black holes with low accretion rates, which are relatively fainter than less-massive black holes with efficient accretion. Lusso et al. (2012) suggest that AGNs show higher Eddington ratios at higher redshift at any given MBH, and the Eddington ratio increases with bolometric luminosity. We confirm that there is a tendency for low-luminosity AGNs (log Lbol ≲ 45.5) with less-massive black holes (log MBH/M⊙ ≲ 8) to have lower Eddington ratios than high-luminosity AGNs (log Lbol ≳ 45.5) with massive black holes (log MBH/M⊙ ≳ 8), consistent with Lusso et al. (2012). It is important to note that, when comparing with results in the literature, one should take into account the different methods of spectral line fitting and correction for bolometric luminosities. Nevertheless, they show similar distributions of the accretion rate of black holes over a wide range, consistent with previous studies.
Citation: Shen et al. 2011
Citation function: Uses; Uses; Differences
Recently, rotationally supported disks have been found not only in Class I sources but also in some Class 0 sources (e.g., Murillo et al. 2013; Yen et al. 2013, 2017; Ohashi et al. 2014; Tobin et al. 2015, 2016b, 2016a; Seifried et al. 2016; Aso et al. 2017; Lee et al. 2017; Okoda et al. 2018). In spite of these extensive studies, there is still controversy regarding when and how a disk structure is formed around a newly born protostar. Moreover, the disk formation process has been revealed to be much more complicated for binary and multiple cases, both in observations (Dutrey et al. 2014; Tokuda et al. 2014; Takakuwa et al. 2014, 2017; Tobin et al. 2016b, 2016a; Boehler et al. 2017; Artur de la Villarmois et al. 2018; Alves et al. 2019) and in numerical simulations (e.g., Bate & Bonnell 1997; Kratter et al. 2008; Fateeva et al. 2011; Shi et al. 2012; Ragusa et al. 2017; Satsuka et al. 2017; Price et al. 2018; Matsumoto et al. 2019). For instance, circumbinary/circummultiple disk structures with a spiral structure as well as a circumstellar disk for each component are reported (e.g., Tobin et al. 2016a; Takakuwa et al. 2017; Artur de la Villarmois et al. 2018; Matsumoto et al. 2019; Alves et al. 2019). In addition, it is not clear how molecules are processed during the disk formation process and what kinds of molecules are finally inherited by protoplanetary disks and potentially by planets. Understanding these processes is crucial, as they will provide important constraints on the initial physical and chemical conditions for the planetary system formation study. In this context, physical and chemical structures and their mutual relation for disk-forming regions of low-mass protostellar sources have been investigated with the Atacama Large Millimeter/submillimeter Array (ALMA; e.g., Sakai et al. 2014b, 2014a; Oya et al. 2016, 2017, 2018, 2019; Imai et al. 2016, 2019; Jacobsen et al. 2019). These studies reveal that infalling envelopes and rotationally supported disks are not smoothly connected to each other either in physical structure or in chemical composition, unlike previous expectations.
Citation: Kratter et al. 2008
Citation function: Background; Background
For confined flares, the key question is the factor determining their confined character. Wang & Zhang (2007) analyzed eight X-class flares and found that confined events occur closer to the magnetic center and eruptive events tend to occur close to the edge of active regions (ARs), implying that the strong external field overlying the AR core is probably the main reason for the confinement. Similar results have been found by Baumgartner et al. (2018) based on a statistical analysis of 44 flares during 2011–2015. Amari et al. (2018) suggested that the role of the magnetic cage crucially affects the class of eruption—either confined or eruptive. To date, many studies have drawn the consistent conclusion that the decay index of the potential strapping field determines the likelihood of ejective/confined eruptions (Green et al. 2002; Shen et al. 2011; Yang et al. 2014; Chen et al. 2015; Thalmann et al. 2015; Li et al. 2018a). Previous studies showed that the torus instability of a magnetic FR occurs when the critical decay index reaches 1.5 (Bateman 1978; Kliem & Török 2006). Zuccarello et al. (2015) performed a series of numerical magnetohydrodynamics (MHD) simulations of FR eruptions and found that the critical decay index for the onset of the torus instability lies in the range 1.3–1.5. Another factor determining whether a flare event is CME-eruptive or not is the non-potentiality of ARs including the free magnetic energy, relative helicity, and magnetic twists (Falconer et al. 2002, 2006; Nindos & Andrews 2004; Tziotziou et al. 2012). Sun et al. (2015) suggested that AR eruptiveness is related to the relative value of magnetic non-potentiality over the constraint of a background field. However, in the statistical study of Jing et al. (2018), the unsigned twist number of a magnetic FR plays little role in differentiating between confined and ejective flares, and the decay index of the potential strapping field above the FR discriminates them well.
Citation: Shen et al. 2011
Citation function: Background
The bolometric luminosity is then computed as the sum of the disc luminosity and the 2–10 keV X-ray luminosity. The λEdd, given by λEdd = Lbol/LEdd, as a function of the MBH is plotted on the central panel of Fig. 5, while the λEdd distribution is shown in the horizontal histogram. Fig. 12 shows the 2–10 keV X-ray bolometric correction ($\kappa _{\rm 2{\rm -}10\,keV}=L_{\rm bol}/L_{\rm 2{\rm -}10\,keV}$) versus Lbol (left-hand panel) and the λEdd (right-hand panel). Tight correlations between the $\kappa _{\rm 2{\rm -}10\,keV}$ and Lbol (Pearson correlation coefficient r = 0.71) as well as the λEdd (Pearson correlation coefficient r = 0.78) are found in our sample as clearly shown in Fig. 12. A similar trend, that the sources with higher bolometric luminosities have higher bolometric corrections, was found in Lusso et al. (2012). A relation between the $\kappa _{\rm 2{\rm -}10\,keV}$ and λEdd is also found in several previous works (Vasudevan & Fabian 2007, 2009; Vasudevan et al. 2009; Lusso et al. 2012). The tight $\kappa _{\rm 2{\rm -}10\,keV}{\rm -}L_{\rm bol}$ relation shown in Fig. 12 as well as the correlation between $\kappa _{\rm 2{\rm -}10\,keV}$ and λEdd, rather than intrinsic, can however be a natural outcome of our flux-limited sample, which will lead to a correlation between the monochromatic optical luminosity Lmon,opt and the X-ray luminosity $L_{\rm 2{\rm -}10\,keV}$. We tested the significance of the correlation by means of simulations. We generated a sample which the log N − log S of both the X-ray and optical flux follows a power-law form, and has a redshift distribution similar to our AGN sample. We then applied the flux cut-off, f0.5–10 keV > 1 × 10−15 erg s−1 cm−2 and R4681  22 mag, on the simulated sources. Using the Lmon,opt and $L_{\rm 2{\rm -}10\,keV}$ of the simulated data we obtain a Pearson correlation coefficient value r of ∼0.57, which is smaller than the correlation coefficient found in the observed data (r ∼ 0.71). Thus the observed correlations in our sample should not be purely due to the selection bias. This result is also consistent with the conclusion that the strong correlation between the monochromatic UV luminosity at 2500Å and the X-ray luminosity at 2 keV is independent of redshift (Risaliti & Lusso 2015). The distributions of the Lbol and $\kappa _{\rm 2{\rm -}10\,keV}$ are shown in the left-hand panel of Fig. 12 (top panel: Lbol, right-hand panel: $\kappa _{\rm 2{\rm -}10\,keV}$). The $\kappa _{\rm 2{\rm -}10\,keV}$ found in our sample, with a mean value of ∼18, are consistent with the values found in previous works (e.g. Vasudevan & Fabian 2007; Lusso et al. 2012).
Citation: Vasudevan et al. 2009
Citation function: Similarities