adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019MNRAS.485..708V (fulltext)
distribution ranging from 0° to 10°. Asteroids which were initialized at the beginning of the simulation with two different eccentricity distributions depending on the simulation. The first is circular asteroids, and the second are asteroids with eccentricities chosen between 0.3 and 0.7. We emphasize that we are not attempting to reproduce realistic exo-debris discs in these systems (which would require a more detailed Yarkovsky model), but rather are placing bounds and observing trends. The evolution of most initially eccentric asteroids that we simulated are not shown, unless they provide a revealing physical trait. Asteroids which were initialized at the beginning of the simulation with orbital angles chosen from a random uniform distribution across their entire ranges. Yarkovsky prescriptions according to the following values of : Our choices for Models A–C arise from our intention to place bounds on the motion by considering only extreme cases. We approximate these extreme cases by focusing on and from the analytic limits in equation ( 25 ). In terms of semimajor axis, Model A pushes asteroids outwards, Model B pushes asteroids inwards, and Model C does not push them outwards or inwards. Alternatively, Models A and B have only a minor effect on asteroid inclination evolution, whereas Model C has a relatively large effect. We actually ran additional simulations with other combinations of entries, but found that they represent intermediate cases to Models A–C, supporting the analytics and our choices. 4 SIMULATION RESULTS The asteroids in our simulations are accelerated by three major effects: (i) mass-loss from the star, (ii) perturbations from the planet, and the (iii) radiation-driven Yarkovsky effect. 4 Mass-loss always pushes the asteroids away from the star (the orbital pericentre is always increasing, even in non-adiabatic motion; Veras et al. 2011 ), whereas the planet and the Yarkovsky effect may perturb the asteroids in either direction. Although both mass-loss and planets can increase e ast to unity (causing escape; e.g. Veras et al. 2011 ; Adams, Anderson Bloch 2013 ), Yarkovsky acceleration cannot. Veras et al. ( 2015 ) investigated the relative magnitudes of stellar mass-loss and the Yarkovsky effect, but did not include a planet nor run numerical simulations. The Yarkovsky drift varies in a complex manner, and is a function of all orbital elements, even in our simple approximation where the matrix elements of remain constant over time. However, equations ( 25 )–( 26 ) reveal that for small inclinations, the key parameters are and . Although the Yarkovsky acceleration drops roughly as , the acceleration increases linearly as a function of L ⋆ ( t ). The time dependence of L ⋆ ( t ) is, in turn, non-linear, and dominates changes in the Yarkovsky acceleration. Mass-loss is largely adiabatic within about 10 3 au (Veras et al. 2011 ), meaning that within this region it feeds back into the Yarkovsky acceleration only through an
Paper: 2020MNRAS.494.1784A (fulltext)
the motivation for the selection of the volume for LASr. Next, we require a galaxy parent sample highly complete in terms of galaxies sufficiently massive to host an AGN, which can then be used to select AGN from. We will see that current local galaxy samples do not fulfil this criterion so that we have to assemble our own galaxy parent sample. Finally, we describe the assembly of the galaxy properties relevant for this work, namely the coordinates, redshifts, and distances, allowing us to find the MIR counterparts of the galactic nuclei and compute their luminosities. 2.1 Selection of the volume We wish to construct a highly complete census of SMBH growth in the local Universe. The choice of volume to be used for this purpose is motivated by several factors. In order to obtain a census that is representative for the whole AGN population, the volume needs to be representative of the larger scale, low redshift Universe. It is estimated that cosmological isotropy is reached for length scales of ∼200 h −1 Mpc with h = H 0 /100 km s −1 Mpc −1 and H 0 the Hubble constant (Sarkar, Pandey Khatri 2019 ). The volume should also be large enough to sample rarer AGN sub-populations in sufficient numbers to yield statistically robust conclusions on their relevance. Here particular emphasis should be on the high luminosity AGN regime because these may dominate the integrated black hole growth and AGN feedback (e.g. Aird et al. 2010 ; Fabian 2012 ). However, high-luminosity AGN have a low space density. For example, current estimates of the AGN luminosity function in X-rays, e.g. Aird et al. ( 2015 ), let us expect a space density of Mpc −3 for AGN with an intrinsic X-ray luminosity of , e.g. ∼20 objects within a sphere of 200 Mpc radius. On the other hand, the volume should be small enough so that the depth of the all-sky surveys, used to identify and characterize the AGN, is sufficient to probe the lower parts of the AGN luminosity range. This is particularly important in the X-rays where extinction is large for obscured AGN. For example, the final all-sky maps of eROSITA and ART-XC are expected to have depths of and at 2–10 keV, respectively (Merloni et al. 2012 ; Pavlinsky et al. 2018 ), which corresponds to a distance of 150–250 Mpc for an observed X-ray luminosity of . However, CT AGN are suppressed by easily a factor of 10 to ∼100 at these wavelengths. The MIR is much less affected by extinction, but sensitivity is the key restricting factor, i.e. the WISE all-sky maps have an average depth capable of detecting an AGN with a 12 luminosity up to a distance of 220 Mpc with ≥3σ in band 3 (W3∼11.6 mag; WISE documentation 1 ). Another factor to take into account is that the completeness of our parent sample of galaxies directly restricts the completeness of our AGN search. According to a recent estimate, our all-sky redshift completeness is only for galaxies with a redshift z 0.03 (Kulkarni, Perley Miller 2018 ), and the completeness is quickly
Paper: 2017ApJ...849L...4C (fulltext)
(Figure 4 ). Furthermore, we collected emission line fluxes of SLSN host galaxies from the literature (Lunnan et al. 2014 ; Leloudas et al. 2015 ; Perley et al. 2016 ; Chen et al. 2017a , 2017b ) and corrected for foreground and internal dust extinction given by the Balmer decrement. SLSN host galaxies are located predominantly in the high ionization region with log([O iii ]/H β ) > 0.5 for any given [N ii ]/H α . This region is populated by extreme emission line galaxies as Leloudas et al. ( 2015 ) pointed out. The positions of SN 2017egm and PTF 10uhf are in a distinct region of the BPT diagram to most other SLSN hosts. This may indicate that SLSNe extend out to large metallicities than previously believed, and may cover a similar region to gamma-ray burst (GRB) host galaxies (see Figure 8 in Krühler et al. 2015 ). Improved completeness of low-redshift SN samples should indicate if SN 2017egm (and PTF 10uhf) are outliers or at the extreme end of a continuous distribution. 3.4. Stellar Ages and Progenitor Masses of GRBs and SLSNe We used the EW of H α as a tracer of the stellar population age (e.g., Leloudas et al. 2011 ; Kuncarayakti et al. 2016 and references therein). In general, a higher EW H α corresponds to a younger age, though the relation between the EW and age is dependent on the star formation history, initial-mass function, metallicity, and binary or single stellar populations (e.g., Eldridge Stanway 2009 ). We collected the EWs of H α at the explosion sites of SLSNe and GRBs from IFU and resolved long-slit spectroscopy (for references see Table 1 ), and estimated the stellar population ages using consistent models. We applied the Binary Population and Spectral Synthesis (BPASS 11 11 http://bpass.auckland.ac.nz version 2.1 models (Stanway et al. 2016 ; Eldridge et al. 2017 ) in combination with the photoionization Code CLOUDY (e.g., Ferland et al. 2013 ). These models will be described in L. Xiao et al. (2017, in preparation), and have been used to study the ages of SNe in Xiao et al. ( 2017 ). Table 1 Physical Properties Inferred from IFU and Resolved Long-slit Spectroscopy at SLSN and GRB Explosion Sites Note. For consistency, we re-calculate the stellar population age using the BPASS model. References are: (a) this work, (b) Cikota et al. ( 2017 ), (c) Thöne et al. ( 2015 ), (d) Krühler et al. ( 2017 ) (GRB 980425/SN 1998bw), (e) Izzo et al. ( 2017b ) (GRB 100316D/SN 2010bh), (f) Thöne et al. ( 2014 ) (GRB 060505/SN-less), (g) Tanga et al. ( 2017 ) (GRB 111005A/SN-less). To calculate the ages of the stellar populations, we select models that have a [O/H] value closest to that measured at the explosion site using the O3N2 calibration (Table 1 ). For each of the SLSNe we then provide two ages, one assuming the stellar population is comprised of single stars only and the second of binary stars. We see that there is a significant difference in the stellar population ages that we derive depending on the BPASS model used. The
Paper: 2018ApJ...866...56H (fulltext)
O 2 and O 3 are also central to the design of instruments for other future ground- and space-based telescopes (Domagal-Goldman et al. 2014 ; Harman et al. 2015 ; Meadows 2017 ; Meadows et al. 2017 ). Here, we argue that O 2 and O 3 are reliable bioindicators under certain conditions. We outline what those conditions are, and discuss the secondary measurements and constraints necessary to demonstrate the presence of such conditions on another world. 2. False Positives in the Literature For the purposes of this paper, a “false positive” for life is defined as any abiotically derived O 2 concentration that exceeds that estimated to follow the GOE (Harman et al. 2015 ). If the low estimates by Planavsky et al. ( 2014 ) are correct, then that level is at or below 0.1% PAL. Possible mechanisms by which that abiotic O 2 level might be achieved have been recently reviewed by Meadows ( 2017 ) and Meadows et al. ( 2017 ). Broadly speaking, these scenarios can be divided into two categories: (1) false positives driven by changes in the redox budget of a planet’s combined atmosphere/ocean system (as defined in Catling Kasting 2017 , Ch. 8), and (2) false positives driven by photochemistry within the atmosphere. Examples of the redox-driven false positives include planets that experience substantial water loss because they are located inside the inner edge of the habitable zone (Kasting 1988 ; Kasting et al. 1993a ), or their host (M) stars are relatively bright during their pre-main sequence lifetimes (Ramirez Kaltenegger 2014 ; Luger Barnes 2015 ; Tian 2015 ), or they lack non-condensable gases like N 2 that help keep water vapor contained in the lower atmosphere (Wordsworth Pierrehumbert 2014 ). In each of these cases, hydrogen is irreversibly lost to space, oxidizing the atmosphere and oceans and, ultimately, the planet itself. The ultimate fate of this oxygen is uncertain but it could potentially be drawn down to undetectable concentrations by absorption into the mantle (Wordsworth et al. 2018 ). Other types of redox-driven false positives essentially correspond to hypothetical planetary scenarios that lack a volcanic source of reduced gases (e.g., Hu et al. 2012 ; Domagal-Goldman et al. 2014 ; Gao et al. 2015 ). If volcanic outgassing is assumed to be nearly zero, or the recombination of CO and O 2 is inefficient, or there are no surface sinks for O 2 , then O 2 can build up in the atmosphere. If reduced volcanic gas emissions are entirely neglected, O 2 can and must accumulate as H 2 O is photolyzed and the resulting hydrogen escapes to space. But we argue that a false positive driven by such low outgassing rates is unlikely if the planet is habitable, so that liquid water can facilitate reactions of O 2 with its crust, and if the planet remains volcanically active for long time periods, as the Earth has done. (We return to this last point in Section 6 .) The false positive scenario described by Hu et al. ( 2012 ) is more complicated in that it has
Paper: 2021MNRAS.504.1355V (fulltext)
Plummer profile reads while the normalized projected number of stars for the same model is where φ( X ) is the angle corresponding to the effective circular section where we analyse the data (see Fig 1 ), and whose analytical expression for small cone apertures (i.e. R max ≪ 1 radian) is where R max is the maximum radius of the original cone search (usually two degrees) and d is the distance between the fitted centre and the centre from the original cone search (), set as the source centre on SIMBAD 2 by the automatic Gaia advanced query. The projected radius R is defined, in spherical trigonometry, as where () is the centre of the galactic object. The likelihood function is therefore written as Figure 1. Geometry of the centre estimation: The original cone search, centred in () is shown as the grey circle of radius R max , while the new fitted centre is (). The angles φ 1 and φ 2 represent the effective circular sections (of respective radii R 1 and R 2 ) where we consider circular symmetry. The distance between the two centres is labeled as d , and we consider this value to approach zero for the cone searches around the centres from the SIMBAD data base. We minimize with the differential_evolution routine from the scipy.optimize method and find the centres that best fit the data, later displaying them in Table C1 . For simplicity, since we expect the quantity d to approach zero, given the reliable previous measurements of the centres in SIMBAD, one can assume the case where , and thus derive Notably, for more general cases, the BALRoGO routine allows to use the more general representation of φ( X ), and thus to account for a more complicated expression for , presented in Appendix A . 2.2 Surface density The next step of our algorithm is to fit the surface density of the galactic object plus interlopers once again, using a maximum likelihood estimation (MLE), but this time with fixed centres from the previous step. It may seem as an unnecessary step given the previous one, but it actually allows the fitting routine to better explore the other parameters ranges like the scale radius and the interloper fraction, and thus derive more robust results. In this step, we also reduced the maximum projected radius whenever there was a parasite galactic object on the field or when the MW contamination was too intense, disturbing the fits. In this step, we not only tested Plummer profiles, but also Sérsic models (Sérsic 1963 , 1968 ) that can be useful for core-collapsed clusters such as NGC 6397, and the Kazantzidis model that is motivated from dynamical simulations of repeated tidal encounters (Kazantzidis et al. 2004 ). Equations ( 2 ), ( 6 ), and ( 7 ) remain valid for these two other models, while the normalized surface density and projected number of stars become for Sérsic, where is the lower incomplete gamma function and X = R / R e , R e being the effective projected radius. And for Kazantzidis, where K 0 and K 1 are modified Bessel functions of
Paper: 2020MNRAS.497.4733L (fulltext)
at 200 pc. We retain the functional form of the Bovy model’s bulge, ρ( r ) = ρ s ( r / r 1 ) −α exp [−( r / r c ) 2 ], but with revised parameters α = 2.0, r c = 1.0 kpc, ρ s = 6.58 × 10 8 M ⊙ kpc −3 , and r 1 = 1 kpc. This yields a total bulge mass of 7.33 × 10 9 M ⊙ . The model roughly matches the observed circular velocity data collected in Sofue ( 2013 ), for both large and small radii. It does not match this data’s prominent peak at R ∼ 500 pc and subsequent decline out to 2.5 kpc, but Chemin, Renaud Soubiran ( 2015 ) argue that this feature is likely an artefact of perturbations from the Galactic bar. The axisymmetry of our potential is clearly an approximation, as orbits on scales of a few kpc are strongly affected by the bar. However, at smaller radii, the observed physical components are close to axisymmetric and the potential contours generated in physical models such as Bissantz, Englmaier Gerhard ( 2003 ) are more rounded. Thus, axisymmetric models continue to be used to study orbits near the Galactic centre (Molinari et al. 2011 ; Kruijssen et al. 2015 ; Perera et al. 2019 ), and we leave non-axisymmetric refinements to future work. We integrate orbits in this potential using the package galpy 3 (Bovy 2015 ). We assume Sgr A* lies fixed at the GC. We adopt a distance to Sgr A* of 8.175 kpc from Gravity Collaboration et al. ( 2019 ), and do not consider in the computation its small observed error. We first define a modified Galactic coordinate system ( l ′ , b ′ ), which uses a slight rotation around the Sun’s position to place Sgr A* exactly at l ′ = 0, b ′ = 0, then shift by the solar distance to obtain Galactocentric coordinates. We choose a solar motion in the Galactocentric frame of v X = −11.0 km s −1 , v Y = 248.5 km s −1 , v Z = 7.8 km s −1 that produces the observed PM of Sgr A*, μ α cos δ = −3.156 mas yr −1 and μ δ = −5.585 mas yr −1 (Reid Brunthaler 2020 ). We use a Galactocentric convention where X points from Sgr A* to the Sun. Fig. B1 shows orbits of the two clusters with a series of initial distances, using our best values of the PM. Orbits starting well on the near side of the GC are highly eccentric. The eccentricity first decreases with the starting distance, then increases again as the orbits become almost radial near the GC. About 20 pc further out, the orbits become retrograde. We note none of the orbits are circular. As noted in Stolte et al. ( 2008 ), circular orbits require , which implies X = ( v X / v Y ) Y , radius R = [1 + ( v X / v Y ) 2 ] 1/2 Y , and circular velocity . For Quintuplet, this implies a velocity V c = 177 ± 4 km s −1 at R = 48 ± 1 pc, where the uncertainties incorporate our estimated PM and RV errors. For Arches, it implies a velocity V c = 168 ± 7 km s −1 at R = 40 ± 2 pc. Both of these circular velocities are comfortably above those implied by our potential, which are 108 and 98 km s −1 , respectively, at these radii. They also lie well above the scatter of different observational
Paper: 2019ApJ...877...29M (fulltext)
by the region of the disk behind the inner rim. Detailed studies have indicated that the picture is somewhat more complicated, with intermediate-temperature components of uncertain origin (e.g., Fischer et al. 2011 ). For the purposes of this study, where we are taking a first look at time variability in the excess, we restrict ourselves to blackbody models of these three basic components, following McClure13 . Each component is defined by a characteristic blackbody temperature and solid angle. We fix the hot component temperature at 7000 K, which is characteristic of accretion shock emission (the exact value is not crucial here because we are seeing only the Rayleigh–Jeans tail). We also fix the cool component to a value of 600 K, which is roughly the equilibrium temperature for dust at the predicted location of the inner edge of the circumbinary disk around DQ Tau (∼2.5 a = 0.35 au). For the warm component, we allow the temperature to vary between 1000 and 1800 K (which spans the range of typical characteristic maximum dust temperatures in TTSs) in increments of 50 K. The solid angles (relative to the stellar value assuming R = 1.5 R ⊙ and d = 196 pc) are varied from 0 to 0.1 for the hot component, 10–50 for the warm component, and 50 to 300 in the cool component. For each set of parameters, the models for all three components are combined and then compared to the observed excess spectra, with the best fit determined via chi-squared minimization. The resulting best fits for each observed spectrum are shown in Figure 20 , with the associated parameters listed in Table 8 . Given the systematic uncertainties in the template matching, these values should be taken as indicative only; however, they provide a useful first look at the gross properties of the material in the inner regions of this system. The best-fit hot component solid angles range from zero at several epochs, where no discernible emission was detected, to 0.06, which is typical for weakly to moderately accreting TTSs. The cool component solid angles range from 90 to 260, roughly as expected for a puffed inner disk rim with a temperature of 600 K. If our assumption of a constant temperature is a reasonable approximation, the variation in solid angle may be indicative of a variable scale height of the inner edge of the putative circumbinary disk. There is a weak correlation with the warm component, but the origin of such a variation is unclear; it could simply be an artifact of our overly simplistic assumptions of the dust temperatures. However, it should be noted that this cooler dust emission is not as well-constrained as the other components because it contributes an appreciable fraction of the total emission only at the long-wavelength end of our spectra. Observations in the 5–10 μ m range are required to test the significance of any variations from this region. Figure 20. DQ Tau excess spectra shown in black, in order of observation time (left to right, top to bottom), with
Paper: 2017A&A...608A..53J (fulltext)
the values. The values are taken from Dunlop et al. ( 1993 , 2003 ). 3.1. Evolution of the bolometric luminosity with time To demonstrate how luminous progenitors of UCDs could have been, we compute the bolometric luminosity, , as a function of time. The dependency is shown in Fig. 3 . The benchmark initial mass is . For the cases of the CAN, SAL, and vDC IMF, the values are proportional to . The MKDP IMF is a function of and therefore we plot also for . The main difference between different MKDP IMFs (for different ) is the slope of the luminosity as a function of time. For a more top-heavy IMF, the decrease of the luminosity with time is steeper. Fig. 4 Time evolution of for all IMFs considered (vDC, SAL, CAN, MKDP). We assume that the system is gas free and that neither stars nor remnants are leaving (the dashed lines show the change of the value if only certain fractions of remnants are kept). The upwards-pointing blue arrow demonstrates that if we would assume more massive remnants (e.g. due to implosion directly to a BH without a SN explosion), then this would lead to larger values of . The models are computed for the case of , however, results are mass independent. The only exception is the MKDP IMF, which depends on initial object mass, , and also contains a large fraction of mass in high mass stars, and is plotted for (, bottom to top) and different fractions of remnants retained (100%, 10%, 0%). Left panel : the evolution for [Fe/H] = 2. Right panel : the evolution for [Fe/H] = 0. The grey band indicates the span of the observed present-day values, approximately five to ten for the majority of UCDs ( Mieske et al. 2008 ; Dabringhausen et al. 2009 ). The scales are identical for both panels. There are several noticeable features in this figure: (i) for the MKDP IMF, UCDs with initial stellar mass are as bright as quasars ( Dunlop et al. 1993 , 2003 ; Souchay et al. 2015 ) for the first few yr. We use low-redshift quasars because for these we were able to find bolometric luminosities, but also absolute magnitudes in the and band. We note, however, that high redshift quasars show very comparable luminosities as shown for example by Mortlock et al. (2011) . This is mainly due to the presence of a large number of O and B stars () in the system. Due to stellar evolution and core-collapse supernova explosions, these UCDs will be variable on a timescale of months. As already suggested by Terlevich Boyle (1993) , such objects might be confused with quasars, especially for example in large photometric surveys. (ii) After less than a Myr, a strong degeneracy between the IMF and appears. That is, for different and different IMFs, similar luminosities comparable to those of observed UCDs occur. (iii) The metallicity is a second-order effect. Fig. 5 Values of the ratio as a function of for three different times . The case of the MKDP IMF is not constant since the MKDP IMF is a function of initial mass. The plotted curves assume all remnants are