adsabs/WIESP2022-NER huggingface dataset:
Paper: 2021ApJ...911L..15Y (fulltext)
SMBH. The forward shock region is shown as the purple area. The cocoon is not depicted. On the other hand, within the duration of these two short-term processes, e.g., t m and t vis , the disk wind radius may reach v d ( t vis − t m ) ∼ 10 14 − 10 16 cm above the disk, where v d is the disk wind velocity that is of the order of the escape velocity, for the circumbinary disk, and is the radius of the circumbinary disk at the decoupling. In reality, not only the circumbinary disk but also mini-disks around two SMBHs contribute, which would make the wind bubble more complicated. For simplicity, we assume the density profile of the winds at the decoupling to obtain the density distribution of the wind bubble at larger distances,where is the mass accretion rate onto the binary system, χ ∼ 1 is introduced to take into account the contribution of mini-disks, and η w represents the fraction of accreted mass converted to the disk wind. According to the simulations, for SANE (Standard And Normal Evolution) models, the parameter η w may vary from 10 −4 to 10 −1 (Jiang et al. 2019b , 2019a ; Ohsuga et al. 2009 ) when the mass accretion rate changes from sub-Eddington to super-Eddington. In MAD (Magnetically Arrested Disk) models, η w can reach 10 −2 to 10 −1 (Akiyama et al. 2019 ). With v d ∼ v esc ( R d ,dec ), we have , where , β d ,−1 ≡ v d /(0.1 c ), the parameter is defined as the ratio of , and the Eddington value (assuming a radiation efficiency of 0.1). After the coalescence, a powerful jet driven by the spin energy of the newly formed SMBH can appear, subsequently propagating in the pre-merger wind bubble. Considering a sub-Eddington accretion rate with the MAD configuration, we estimate the jet kinetic luminosity to bewhere η j ∼ 0.3–1 is the ratio of the accretion energy converted to the jet energy (Tchekhovskoy et al. 2011 ). Following the standard jet propagation theory (e.g., Bromberg et al. 2011 ; Mizuta Ioka 2013 ), we write down the dimensionless parameter that represents the ratio of the energy density of the jet and the rest-mass energy density of the surrounding mediumwhere θ j is the jet opening angle, is the isotropic-equivalent luminosity. Since the quantity lies in the regime , we expect that the jet is “uncollimated” for our fiducial parameters. 6 6 However, jet collimation, which was assumed in Yuan et al. ( 2020 ), would be achievable for the super-Eddington accretion accompanied by disk winds with η w ∼ 0.1–0.3. This situation is similar to that in choked jet propagation in the circumstellar material (Senno et al. 2016 ; Nakar 2015 ), and β h is evaluated from . In the relativistic limit, the jet head Lorentz factor is (Senno et al. 2016 ), and we have Γ h ∼ 2 in our fiducial case with . Note that the jet head radius is , and is introduced to represent time measured in the central engine frame, which can be converted to the observation time T via (that is in the relativistic limit) for on-axis observers. Furthermore, to ensure
Paper: 2016MNRAS.458.2916C (fulltext)
This leads to a fraction of ∼30 per cent of the nova progenitor systems which harbour evolved secondaries. Given that the nova progenitor systems with evolved secondaries have relatively higher mass transfer rates compared with nova progenitor systems with MS donors, nova progenitor systems with evolved secondaries should have more frequent outbursts. Therefore, the contribution of novae with evolved donors to the total nova rate should be larger than the fraction of corresponding binary systems, 30 per cent. Recently, Williams et al. ( 2016 ) conducted a more accurate statistical analysis of their preceding results and came to the conclusion that of nova eruptions in M31 galaxy are RG-novae. 4.5 Correlation between mass-specific nova rate and morphological type of galaxy Observations give contradicting results regarding the dependence of the mass-specific nova rate on the Hubble type of the galaxy. Some observational studies (e.g. Ciardullo et al. 1990 ; Shafter et al. 2000 ; Ferrarese et al. 2003 ; Williams Shafter 2004 ) claimed that there is no strong dependence of mass-specific nova rate on the Hubble types of galaxies: the majority of galaxies have around 2 ± 1 × 10 −10 L ⊙, K −1 yr −1 . However, there are several galaxies which may have a higher mass-specific nova rate e.g. the SMC, LMC, M33 and others (Della Valle et al. 1994 ; Della Valle 2002 ; Neill Shara 2005 ; Alis Saygac 2014 ; Mróz et al. 2016 ; Shara et al. 2016 ). The mass-specific nova rate of elliptical-like galaxies at 10 Gyr in our calculation is around (1 − 2) × 10 −10 M ⊙ −1 yr −1 . This is consistent with Williams Shafter ( 2004 ), since the total stellar mass-to-light ratio M ⋆ / L K ∼ 1.0, slightly depending on the colour of the galaxy (Bell de Jong 2001 ). However, for spiral-like galaxies, we obtained a mass-specific nova rate 10–20 times larger. It would seem then that our results are inconsistent with measurements of Williams Shafter ( 2004 ). However, one crucial point to understand this discrepancy is the incompleteness of nova surveys. For example, the nova rate of M31 in the analysis of Williams Shafter ( 2004 ) is significantly lower than the nova rates of Darnley et al. ( 2006 ). As we discussed above, a more reliable value should be ≈97 yr −1 , giving a luminosity-specific nova rate ∼7.0 × 10 −10 L ⊙,K −1 yr −1 , which is a factor of 3–4 larger than the value in Williams Shafter ( 2004 ). In our model for M31, we find a mass-specific nova rate of ≈(7 − 14) × 10 −10 M ⊙ −1 yr −1 , which is consistent with the above number. In our model of spiral-like galaxies, we assume the SFR to be constant, which is almost certainly oversimplified in the general case. As shown in Figs 1 and 2 , if there was an initial spike of SFR, certain fraction of total mass of ‘realistic’ spirals sits in old population which does not contribute much to the current nova rate. This will lead to a smaller value of luminosity-specific nova rate (cf. Table 1 ). 4.6 Novae with short
Paper: 2020A&A...640A..62A (fulltext)
and the radio core is typically within 10%. The apparent displacement vectors of C7 have an anisotropic distribution and show asymmetry in the jet direction with tendency to be longer along the jet axis. These effects are most likely due to resolution-dependent core shift or opacity effects. We developed a statistical tool for estimating the mean and variance of the displacements of the core and C7. We find that the displacements of C7 (isotropic component) and the core (anisotropic component) have an almost commensurate contribution to the apparent displacements of C7. The estimates of statistical characteristics of displacements are close to true values for short observation intervals ( 35 days). The rms of displacements of the core and C7 decreases 1.5−2 times during the stable jet state compared to those during the swinging activity of C7. The contribution of the core and C7 to the apparent motion of C7 remains of comparable importance during both states of activity. The rms of the spatial displacements of the core is a factor of four larger than those of the C7. During the jet stability period, the motion of the C7 on time scales of months is complex, showing swinging motion with reversals of the direction, and superluminal speeds. The trajectories of C7, smoothed over time scales of a few years, show a clock-wise loop motion with mean subrelativistic speed (0.16 ± 0.008) c . Long-term monitoring with high cadence (less than or about a month) VLBA observations at 15 GHz is needed to study the dynamics of the C7. Accurate and low positional uncertainties of the C7 are crucial for identifying the dominant contribution of the intrinsic motions of the core and C7 to the apparent motion of C7. We confirm that the excitation of transverse waves moving along the jet is generated by the motion of the C7, which acts as the nozzle to the jet. The excitation of transverse waves with relatively large amplitudes (≳0.2 mas) are associated with excessively large apparent displacement vectors (> 0.08 mas) of the nozzle. Quasi-sinusoidal stable waves with small amplitudes (≲0.02 mas) are generated by the reversal motion of the nozzle within the angular distance of ≈0.02 mas (0.03 pc), which matches nicely with the amplitudes of the excited waves. The on-sky distribution of flux densities of C7 reveals a statistically significant brightening of the emission upstream and transverse to the jet. The observed brightness asymmetry is not dependent on the epoch and it is, rather, associated with a regular change of the jet viewing angle at the location of the C7 (or the nozzle). The asymmetry of the brightness can be reproduced by a toy model of C7. The model assumes an axisymmetric twisted jet velocity field for the C7 and a jet viewing angle of 8°, while the intrinsic flux density and speed of the jet are unchanged. More sophisticated models are necessary to recover the jet viewing angle of the BL Lac and parameters characterising the velocity field of the jet.
Paper: 2019MNRAS.482.1807K (fulltext)
of K2-140b in Livingston et al. ( 2018 ) was based on simple mass–radius relation. It was not the intention to give accurate mass determinations, rather to select appropriate targets for follow-up observations. This highlights the importance of RV measurements to determine precise planetary masses. The planet mass derived by G18 using RV measurements is in agreement with the presented results within 1σ. The main difference between the subsequent analysis and the parameters for K2-140b from G18 is the orbital eccentricity. An accurate estimate of this parameter is important since it affects the derived argument of pericentre, stellar mean density, semimajor axis, and thus the derived equilibrium temperature. G18 found a non-zero eccentricity for K2-140b of using 12 CORALIE and 6 HARPS RV measurements. The analysis presented in this paper favours in contrast a circular orbit solution. In order to check whether this is a direct result from the additional 13 RV measurements the relation for an expected eccentricity error σ( e ) (Zakamska et al 2011) is used: where K is the radial velocity amplitude, N is the number of RV observations, and σ obs is the average RV error of the observations. The G18 RV data with K = 111.2 m s −1 , σ obs = 23.6 m s −1 , and N = 18 do not constrain the orbit eccentricity better than σ( e ) = ±0.21. The KESPRINT RV data with K = 102 m s −1 , σ obs = 12.8 m s −1 , and N = 13 constrain the orbit eccentricity to σ( e ) = ±0.15. Combining both data sets ( K = 106 m s −1 , σ obs = 19.1 m s −1 , and N = 31), the orbit eccentricity is constrained to σ( e ) = ±0.14. Thus it was concluded that the more accurate KESPRINT RV measurements improved the eccentricity detection. Moreover, a combined fit using the light curve and the RV data achieves better accuracy in the eccentricity. The eccentricity found by G18 might be driven by the uncertainties of the individual RV measurements and their distribution along the RV curve. The significance of their result was here tested statistically by Monte Carlo simulations. One hundred thousand simulated RV data sets were created by sampling a best-fitting circular orbit solution at the timestamps of the CORALIE and HARPS observations. Gaussian noise at the same level of the G18 measurements was added. A least-squares fit to these simulated data also allowed an eccentric solution. There is a probability of ∼12 per cent that an eccentric solution with e ≥ 0.12 may be found if the true orbit is actually circular. The same analysis was repeated by combining the FIES RV data with those from G18 . Once again, simulated data created from the best-fitting circular orbit model can mimic an eccentric orbit with a probability of 6 per cent. The new analysis shows that the previously claimed eccentric orbit is not statistically significant. In contrast, the BIC that distinguishes between an eccentric or circular solution prefers the circular orbit. The results highlight the difficulty in distinguishing
Paper: 2017A&A...601A..70S (fulltext)
younger objects suggests a much shallower gradient: we derive slopes equal to and dex kpc for the SFRs and all the associations younger than 100 Myr (i.e. SFRs + YOCs), respectively, through a linear fit based on the orthogonal distance regression method and taking into account the error bars on both the axes. In other words, comparison with the old clusters analysed by Jacobson et al. suggests a flattening of the gradient at very young ages. The results on the evolution of the Galactic metallicity distribution is still based on a small number of metallicity determinations and limited to clusters covering a range of 2 kpc in around the Solar location, thus they cannot be taken as conclusive. However, it is in agreement with and, crucially, extends to younger ages, previous estimates of the evolution of the radial metallicity gradient based on the study of open clusters ( Carraro et al. 1998 ; Friel et al. 2002 ; Magrini et al. 2009 ; Andreuzzi et al. 2011 ; Cunha et al. 2016 ). On the other hand, this result is at variance with other studies based on observations of field stars (e.g. Nordström et al. 2004 ; Casagrande et al. 2011 ; Anders et al. 2017 ). As mentioned already, however, the main difficulty of using field stars to trace the chemical pattern of the Galaxy and its evolution over time is that their ages and distances are not as well constrained as for open clusters, and that field star samples are normally older than 1 Gyr, thus not allowing the study of the latest phases of disc evolution. Whilst the Gaia mission ( Perryman et al. 2001 ; Gaia Collaboration 2016 ) and asteroseismology are allowing and will continue to allow a big step forward in the determination of the distances and ages of field stars, the second problem still remains a major and intrinsic limitation. Fig. 5 Radial metallicity distribution of all the clusters included in the iDR4 catalogue. Their Galactocentric radii and metallicities are reported in Tables 2 and 4 . Red circles indicate star forming regions, blue circles denote young clusters in the age range between 10 and 100 Myr, while intermediate age clusters are shown as black symbols. 5.1. Comparison with literature results and the metallicity distribution at young ages from other tracers In a recent paper Netopil et al. (2016) investigated the metallicity distribution of a sample of 172 clusters, using a homogenised compilation from the literature. They suggested that young clusters (defined in that paper as those younger than 500 Myr) may be characterised by lower metallicities than the older ones, at least in the region between 7 and 9 kpc from the Galactic centre; at the same time, they confirmed the presence of a negative gradient for these clusters. We mention, however, that their sample did not include any clusters younger than Myr located in the inner Galaxy. Fig. 6 Comparison between the metallicity distributions of SFRs and YOCs by our analysis (red and blue dots, respectively) and those of
Paper: 2017A&A...608A..45L (fulltext)
objects, the models were applied to the set of Spitzer , Herschel , and ALMA fluxes. We used the Spitzer and Herschel /PACS flux values as published in Lim et al. (2010) , but updated the Herschel /SPIRE fluxes, accounting for (i) a new reduction pipeline (HIPE version 8.2) and destriping methods ( Fornasier et al. 2013 ) and (ii) the availability of new Makemake observations from June 2010, in addition to the Nov./Dec. 2009 data presented in Lim et al. (2010) . Averaging the two epochs, the new SPIRE fluxes are 12.5 1.3 mJy, 9.5 1.3 mJy, and 4.7 1.5 mJy at 250, 350 and 500 m, respectively. In the first model (“Makemake-alone”), a standard NEATM fit was performed on the 3-band Herschel /PACS and the Spitzer 71.42 m fluxes, ignoring the Spitzer 23.68 m flux, with as the only free parameter. As before, the model was then applied to other wavelengths to determine the corresponding spectral emissivities. The best fit solution, shown in the left panel of Fig. 7 , has 9, but even though the diameter and geometric albedos are fixed, the error bar on is large (; see Table 5 ), a consequence of the strong effect of the phase integral uncertainty for a bright object. Our ALMA flux measurements then imply a 1.03 relative mm emissivity. In a second model (“Makemake + moon”), the two Spitzer and the three Herschel /PACS measurements were fit with the sum of emission from Makemake and its moon. This model had initially four parameters, and (, and ) for its moon, for which we adopted 0.3 (to allow for possible light curve variation). However, the system was somehow degenerate and best fit solutions tended to call for very large values of (3–4), while values larger than 2.7 are unphysical (see e.g., Fig. 4 of Lellouch et al. 2013 ). was then fixed at a maximum value of 2.64. Even then, the problem remained somewhat under-constrained, leading to broad ranges for (, and ) of the moon (Table 5 ). More worryingly but consistent with the previous studies ( Lim et al. 2010 ; Parker et al. 2016 ), the solution range of remained unphysical (0.34) suggesting that Makemake’s moon alone might not entirely explain the 24-m flux. Since the temperatures scale as (), a possible way to alleviate the problem would be to invoke a bolometric emissivity much lower than 1 for Makemake’s moon, but we note that restoring physically reasonable values of (say ) would then require . In any case, with this “Makemake + moon” model, we infer a 1.05 relative mm emissivity for the system. In a third model, the 24 m flux excess from Makemake’s system was attributed to dust emission. For this we adopted the dust absorption coefficients of Li Draine (2001) , giving, for example, m kg at 23.68 m, and specified a dust grain temperature of 54.6 K, which corresponds to the instantaneous equilibrium of a sun-facing surface with zero albedo at Makemake’s 52 AU distance. This choice is somewhat arbitrary as small grains could be poor radiators (hence warmer than the above value), and/or radiating
Paper: 2021MNRAS.504.4015D (fulltext)
We found that the best-fitting soft-excess flux predictions are off by at least a factor of two from the values measured by Tripathi et al. ( 2021 ), except for the extinction curve of Czerny et al. ( 2004 ) with E ( B − V ) = 1.0. In this case, the estimated soft excess flux in the 0.3–2 keV is within the range of the fluxes measured by Tripathi et al. ( 2021 ) from the five AstroSat observations. The best-fitting inner radius and accretion rate are 126 R g and of the Eddington rate, respectively. This suggests that the inner disc in IC 4329A could be covered by a warm, optically thick layer, whose emission is consistent with the optical/UV SED and could also explain the observed soft-excess we detect in this source. 5 DISCUSSION AND CONCLUSIONS We present the results from the analysis of UV images of IC 4329A obtained with AstroSat / UVIT observations. These are the highest resolution and deepest images of IC 4329A ever acquired with any telescope in the near and far-UV bands. The UVIT images enabled us to calculate the galaxy radial profile, and unambiguously separate the AGN emission from the extended emission of the host galaxy by fitting the profiles with the appropriate functions. We derived the intrinsic AGN continuum flux after de-reddening for both the Galactic and internal extinctions, and correcting for the contribution of emission lines. The active nucleus is not detected in the FUV band, and we were able to put a conservative 3σ upper limit on the AGN flux in this band. When combined with the AGN flux in the NUV and 5100 Å (taken from past observations), we found that the far-UV/optical, intrinsic emission of the active nucleus in IC 4329A, requires no disc emission below ∼80–170 R g . The superb spatial resolution of UVIT is crucial in this case, specially in the FUV. If we had performed simple aperture photometry in the FUV image, using a 5–10 arcsec radius (as is typically the case), we would have ended with a flux measurement at least seven times larger than the 3σ upper limit we have determined in this band. Since the host galaxy in most templates is assumed to emit very little at these short wavelengths, this measurement would have been assumed to be intrinsic of the active nucleus, and this false result would have critically altered the shape of the intrinsic AGN SED at short wavelengths. X-ray reflection spectroscopy can independently probe the inner accretion discs via the relativistic iron Kα line near ∼6.4 keV and the strength of the reflection. Using XMM-Newton observations of IC 4329A, Nandra et al. ( 2007 ) derived a low-disc reflection fraction of R f ∼0.3 ( R f is defined as the ratio of the X–ray intensity that illuminates the disc to the intensity that reaches the observer; R f = 1 corresponds to a semi-infinite slab subtending 2π solid angle at the X-ray source). Using NuSTAR observations, Brenneman et al. ( 2014 ) detected a moderately broad iron line with a Gaussian σ ∼0.36 keV in addition to narrow iron Kα,
Paper: 2016MNRAS.461..606K (fulltext)
interact gravitationally and radiative cooling is left on. This density threshold is set to 10 per cent of the star formation threshold, which is ρ SF = 0.13 cm −3 for the arepo simulations and ρ SF = 0.33 cm −3 for the Sherwood simulation. By looking at volume-weighted spherically averaged density profiles of haloes, we estimate that these density thresholds correspond to an average distance of 0.7 R vir for the arepo simulations and 0.4 R vir for the Sherwood simulation. There is of course some scatter between individual haloes, however. The Illustris, HVEL and FAST simulations all include AGN feedback, but the Sherwood simulation does not include black holes. We do not however expect this to change our results significantly [see, for example, Tescari et al. ( 2011 ) and Suresh et al. ( 2015 ), who find that AGN are not very important for metal enrichment at high redshift]. 2.1.3 UV background Illustris, HVEL and FAST were all run using the Faucher-Giguère et al. ( 2009 ) model of the UV background. A correction for the self-shielding of gas from the UV background is also incorporated into these simulations, based on the Rahmati et al. ( 2013 ) model; however, this is only included below z = 6. The Sherwood simulation was run using the Haardt Madau ( 2012 ) UV background, which turns on at z = 15. Note that throughout this work, unless specified, we used the Haardt Madau ( 2012 ) model of the UV background for computing the ionization state of the gas. The original UV background of the simulations will still be important when considering, for example, the temperature of the gas in the simulations. We do investigate the effect of changing the shape and amplitude of the UV background on the metal-line absorbers we model in Section 4.2 . Ideally, we would use a more realistic inhomogeneous UV background, such as in Finlator et al. ( 2015 ), but it is reassuring in that work they find that there is only a factor of ∼2 difference between the neutral fractions calculated using their model and the Haardt Madau ( 2012 ) background. 2.2 Feedback and the high-<italic>z</italic> IGM/CGM Galactic feedback is generally invoked to reconcile the shapes of the dark matter halo mass function and galactic stellar mass function (e.g. White Frenk 1991 ). For our purposes, the feedback is important both as a means of regulating the number of stars produced (and hence the amount of metals) and also for distributing these metals throughout the IGM. In the left-hand panel of Fig. 1 , we show the galaxy stellar mass function of the different simulations at z = 6 for haloes resolved by at least 100 dark matter particles. Here we compare to observations of the stellar mass functions at z ∼ 6 (Stark et al. 2009 ; González et al. 2011 ) but note that the Illustris run has already been compared with observations across a wide range of redshifts z = 0–7 in Genel et al. ( 2014 ). The HVEL model shows an increase in galaxies with low stellar masses, as the constant fast