adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019MNRAS.490.2692K (fulltext)
cases for toroidal magnetic field configuration combined with the rotation. Fig. 2(a) shows the density contour with the uniform angular frequency Ω = 0.0628 rad s −1 with kinetic to gravitational energy ratio KE/GE ∼3.58 × 10 −6 . Since the angular frequency is small, it does not affect the star considerably, resulting in a prolate star. On the other hand, Fig. 2(b) illustrates a star with angular frequency Ω = 3.6537 rad s −1 with KE/GE ∼ 1.33 × 10 −2 , and due to this high angular velocity, the low-density region is affected by the rotation more significantly than the high-density region, resulting in an overall oblate-shaped white dwarf. Here, in both the cases, ρ c ∼ 2.2 × 10 10 g cm −3 , and magnetic field at the centre of the white dwarf B max ∼ 2.7 × 10 14 G. Indeed, a few white dwarfs are observed with the surface magnetic field of ∼10 9 G (Heyl 2000 ; Vanlandingham et al. 2005 ; Brinkworth et al. 2013 ); hence, central field might be much larger than 10 9 G. In fact, it has already been argued in the literature that the central field could be as large as 10 14 –10 15 G (Franzon Schramm 2015 ; Shah Sebastian 2017 ). This is similar to the magnetic field in the case of the Sun, where it is known from observations that the surface field is ∼1 G. However, the central field could be ∼10 4 –10 7 G, indicating an increase of four to seven orders of magnitude (Parker 1979 ). Now, in time, Sun-like stars will become white dwarfs and they may possess similar field profile as earlier, as argued by Das Mukhopadhyay ( 2014 ). Hence, a white dwarf with B max considered here might have surface field of 10 9 G, which observed data have already confirmed. As a result, magnetic to gravitational energy ratio ME/GE is ∼0.1. The surface of a white dwarf is determined, when the density decreases at least up to seven to eight orders of magnitude compared to its central density, i.e. ρ c ∼ 10 7–8 ρ surf (ideally zero), where ρ surf is the density at the surface. The barcode shows the density of the white dwarf at different radii. The typical isocontours of magnetic field strength are shown in Fig. 3 . It is confirmed herein that the surface magnetic field can decrease up to ∼10 9 G even if the central field is ∼10 14 G. However, GW astronomy may also help in identifying magnetized white dwarfs with surface fields higher than 10 9 G, as argued later. Figure 2. Density isocontours of uniformly rotating white dwarf with toroidal magnetic field. Figure 3. Isocontours of magnetic field strength for uniformly rotating white dwarf with toroidal magnetic field. The black solid line represents the surface of the white dwarf. All the parameters are same as in Fig. 2(a) . Table 1 shows different h 0 for various ρ c . In the table, M represents the mass of compact object, R E is the equatorial radius, R P is the polar radius, and ν is the linear frequency defined as ν = Ω/2. It is observed that for a given ρ c , h 0 increases with the increase in rotation because h
Paper: 2016MNRAS.455.3312G (fulltext)
and started observations in two polarization filters 60 s after notice time and 79 s after trigger time at 2015-03-01 19:39:23 ut . The very first frame showed a bright (15.3 m) optical source with the coordinates and an error of 1 arcsecond (Buckley et al. 2015 ). The Swift XRT X-ray telescope and UVOT ultraviolet telescope also detected X-ray and optical emission, respectively, from GRB 150301B 82 and 85 s after the BAT trigger (Lien et al. 2015 ). Later, 5.12 h after the burst, the Very Large Large Telescope (Paranal Observatory, Chile) and X-shooter measured the redshift of this burst, which was found to be z = 1.5169 (de Ugarte Postigo et al. 2015 ). MASTER observations. MASTER robotic telescope observed this gamma-ray burst in the alert mode in two polarization planes with variable exposures (see Section 2.2 ). As a result of our observations, the following light curve was obtained (see Fig. 1 and Table 1 ). Figure 1. GRB 150301B MASTER-SAAO light curve in two telescope tubes with different polaroid orientations (45° and 135° ). Table 1. Photometry data for GRB 150301B by MASTER in the unfiltered band with two orthogonal polarizing filters. MASTER-SAAO telescope observations of GRB 150301B lasted from 2015-03-01 19:39:23 ut through 2015-03-01 20:48:11, i.e. for about 1 h beginning with the 79th second after the trigger. Observations were then interrupted because of heavy clouds. We observed well-defined optical emission from GRB 150301B up until 2000 s after the trigger while the source remained brighter than the limiting magnitude on our frames. Unfavorable weather conditions prevented us from extending the light curve by obtaining deep stacked frames. Throughout the entire time interval from 79 to 2000 s the source faded in accordance with the power law F ∼ t −1.16 ± 0.05 which, in general, is typical of GRB that time (Mészáros 2006 ). 3.1 Spectrum from the optical to X-ray Observations of the gamma-ray burst with MASTER telescopes were performed synchronously with observations on the Swift /XRT X-ray telescope (Fig. 2 ). Optical data corrected for absorption N H = 6.2 × 10 20 cm −2 (Maselli et al. 2015 ) which is consistent with the Galactic value (Willingale et al. 2013 ). Note that variability observed in X-rays in the form of three local maxima in the 88, 191 and 282 s does not occur in the optical wavelength, that has already been observed previously (for example, Ziaeepour et al. 2008 ; Li et al. 2012 ). Figure 2. Optical, X-ray and gamma observation light curve of GRB 150301B. The Swift /XRT 0.3–10 keV and Swift /BAT 15–150 keV light curves are available from the Swift Burst Analyser (Evans et al. 2010 , http://www.swift.ac.uk/burst_analyser/ ). 3.2 Polarimetric measurements The technique of polarimetric measurements used on MASTER network telescopes allows detecting the optical emission polarization at a level of 5 per cent or higher for objects brighter than 16 m or estimating a lower limit for polarization (if the object
Paper: 2017ApJ...851...12R (fulltext)
continuum from decay of the metastable 2s level of H i , since that would peak at around 1450 Å and drop toward zero as the wavelength approaches Ly α , which is not observed. Rather, it is dust-scattered galactic background starlight, as also seen with HUT (Raymond et al. 1995 ). That continuum was attributed to dust-scattered light from B stars based on a private communication from J. Murthy, whose UV background observations showed that this area of the sky is unusually bright. 4. Analysis 4.1. Proper Motion We have used H α images for six epochs from 1998 to 2016, as listed in Table 1 , to measure the proper motion of the Balmer filament that delineates the bow shock. All the images were first placed on a common world coordinate system using a few hundred stars from the Gaia First Data Release (Gaia Collaboration et al. 2016 ). We then extracted a 1D profile for each epoch from a section 8′′ long, oriented normal to the shock front at the bow shock position. For each epoch pair separated by ∼4 yr or more, we carried out a fitting procedure to determine the proper motion over the intervening interval—a total of 14 independent epoch pairs. Since the 2015 and 2016 images had significantly better seeing than those at the earlier epochs, it was necessary to smooth the sharper images with an appropriate Gaussian to obtain acceptable fits. Figure 2 shows the bow shock region at three of the epochs, displayed in different colors. All the epoch pairs gave reasonably good fits and results ranging from 0314 ± 0019 yr −1 to 0357 ± 0023 yr −1 , with most of the pairs ranging from 0336 yr −1 to 0349 yr −1 . We took a simple average of all 14 measurements to obtain our final result for the proper motion of bow shock filament: 0341 ± 0010 yr −1 , where the uncertainty should include both statistical errors and possible systematic ones due to misalignment of images from different epochs. This corresponds to −0245 ± 0008 yr −1 in R.A. and +0238 ± 0008 yr −1 in decl. This value is 22% faster than the proper motion of 0280 yr −1 obtained by Winkler et al. ( 2003 ) for the brighter main portion of the NW filament in SN 1006, located a few arcminutes to the NE. It is hardly surprising that the bow shock region is moving faster, since the shock is apparently being driven ahead here by an ejecta fragment. Indeed, it was for this reason that we selected it for study with COS—to study the fastest shock that was also bright enough to enable us to obtain an ultraviolet spectrum in a reasonable amount of time. Combining our proper motion with the distance of 1.84 ± 0.14 kpc from the proper motion and shock speed of the main NW filament, we obtain a shock speed of 3030 ± 250 for the bow shock. Our long sequence of images will enable a more complete study of the proper motions of optical filaments in SN 1006, which will be reported in a separate publication. 4.2. Optical Spectrum We extracted the spectrum of a 15′′ section of the IMACS slit centered on the HST /COS
Paper: 2019MNRAS.489.2732I (fulltext)
between the two populations is clear: RQ AGNs occupy only the top-right region of the plot, meaning that they have a weak and steep X-ray emission. On the other hand, most blazars have a stronger and flat emission and they are located in the bottom left-hand region. Based on this distinction, we set two thresholds to differentiate blazars and non-blazar AGNs. In particular, as shown in Fig. 5 , we adopt the values = 1.8 and = 1.355 as thresholds to separate the two populations. These limits include all the confirmed high-z blazars. We then apply these criteria to the high-z AGN in the CLASS sample (Fig. 6 ). In particular, we plot here the 14 objects with a reasonable estimate of the photon index (error 0.4). The remaining 10 will be discussed further below. The sources of our sample which have been already confirmed as blazars in the literature are highlighted by a black circle. In addition, in the plot it is also included the classification as blazar/non-blazars (flat/peaked) based on the radio spectrum and discussed in C19 (blue points = peaked, red squares = flat, and purple diamonds = uncertain). Figure 5. Photon index as a function of the index for the comparison samples. In orange we report the BZCAT blazars observed by Swift-XRT , with red squares the few confirmed blazars at high-z and with blue points the RQ AGNs at high-z. The red star represent the z = 5 blazar DESJ014132.4-542749.9, Belladitta et al. ( 2019 ). The continuous black line represents the dependence of the photon index with a variation of the X-ray intensity () of the jet due to beaming effects considering a coronal emission with = 1.55 and = 2, while for the jet emission we assume = 1.6. The black cross represents the critical angle assuming that the jet seen at θ = 0 is 50 times more intense than the corona at 10 keV. The plot is divided in four areas by a vertical line at = 1.355 and a horizontal one at = 1.8, which correspond to the thresholds assumed for the classification. Figure 6. Photon index as a function of the for the high-z objects in the CLASS sample with an error on the photon index lower than 0.4. The objects are plotted with different colours and markers depending on the radio spectral classification reported in C19 (‘flat’ i.e. good blazar candidates, ‘peaked’ i.e. probably non-blazars and ‘uncertain’) and the black circles represent the few confirmed blazars at z > 4 in the literature. As in the previous figure, the plot is divided in four areas by a vertical line at = 1.355 and a horizontal one at = 1.8. Considering the objects plotted in Fig. 6 , there is only one source whose and are not consistent with a blazar nature (GB6J012126+034646), meaning that its X-ray spectrum is too steep and too weak to be produced by an oriented jet (grey region). On the other hand, as expected, the majority of the sources (13) are in the bottom left-hand region (green), meaning that they are strong and flat enough to suggest that they are bona fide blazars.
Paper: 2020MNRAS.492.3396S (fulltext)
impossible by using an encryption algorithm and allowing the specification of side constraints to be met. Section 5.6 computes the shift of parameters to determine whether blinding succeeded. Finally, the physical units are restored, and the output is a purposefully biased covariance matrix which leads to the requested bias in physical parameters, with the origin of the bias being untraceable due to the intermediate encryption and side constraints. 3.3 Finding sensible target parameters for blinding At the outset of the blinding strategy, the blinder has to pick an origin of the posterior shift, and target parameters which are preferred after shifting. Typically, shifting the yet unknown posterior by two to three standard deviations is the sought aim. Having never computed the full posterior, its standard deviations are however not known yet, so we effectively wish to shift by the multiple of a yet unknown quantity. We thus require an abstract prediction of the shift’s magnitude. To this aim, we exploit scaling relations: For a multivariate Gaussian posterior, the best-fit will occur at the minimal chisquared, . The associated 90 per cent credibility contour can then be chosen to run along an isocontour which lies by Δχ 2 above this minimum. The more parameters are estimated, the larger Δχ 2 has to be, since more parameters will widen up the joint posterior. The values of Δχ 2 where the 90 per cent credibility contour lies above the minimum are known (they are integrals of χ 2 -distributions), and we tabulate them as a function of free parameters in Table 1 . Table 1. Δχ 2 -values where the 90 percent credibility contour lies above the minimum χ 2 , as a function of number of parameters. If the blinder chooses target parameters which differ from the initial parameters by more than Δχ 2 shown here, then a posterior shift of more than three posterior standard deviations will ensue. This is not advised. The blinder thus has to know how many parameters are to be inferred, and has to pick initial parameters and target parameters which differ approximately by Δχ 2 -values as given in Table 1 . If the blinder has no physical intuition for which parameter values are likely to be preferred by the data, then the linearized best-fitting estimator of equation ( 7 ) can be evaluated, which will yield parameter values close to the full non-linear best fit . We found that the values do not need to be picked with too much care, as long as they are within about two posterior standard deviation from the true best-fit . We provide a public code 2 for the algorithm, which assists the blinder via equation ( 7 ) and Table 1 in finding sensible parameters for the shift origin, and for the shift destination . 3.4 Data transformation The general astronomical data set will come in ‘natural’ units, which might depend on estimator choice or the adopted (physical) units of measurements, such as parsec or mega-parsec. To gain generality, we thus standardize the data set.
Paper: 2018MNRAS.478.1818G (fulltext)
and adds it to the envelope. We see that even with the large amount of energy that we add to the envelope as it expands to twice its original radius in a short time, the basic structure stays similar. For example, there is a density inversion in the outer part of the envelope and the convection speed stays below the sound speed. This implies that convection can carry even more energy than it carries now. Figure 3. Profiles of four quantities of our AGB stellar model in the outer layers of the envelope at t = 0 (the beginning of the plunge-in phase). The right edge of both panels is at the photosphere of the star. Upper panel: the temperature (black) and the density (magenta) in a logarithmic scale. Lower panel: the sound speed (blue) and the convective velocity (red). The orange, green and purple dotted vertical lines mark the zones of 90 per cent, 50 per cent and 10 per cent ionization of hydrogen, respectively. Figure 4. Like Fig. 3 but at from the beginning of the plunge-in phase. Figure 5. Like Fig. 3 but at the end of the plunge-in phase at . We next calculate the energy transport time from radius r to the surface of the star, R , by photon diffusion, as given in equation ( 1 ), and by convection, as given in equation ( 4 ). We present these energy transport times at the three evolutionary stages in Figs 6 – 8 , respectively. The convection velocity drops to very low values in the very outer part of the envelope, and so we calculate the convection time to the radius of 1 per cent hydrogen ionization fraction instead of the photosphere. This change is of no significance since in the outer region photon diffusion carries most of the energy. Figure 6. Energy transport times from radius r to the surface of the star at radius R for t = 0 when we start the energy injection. Since the convection velocity drops to very low values in the very outer part of the envelope, we calculate the convection time to the radius of 1 per cent hydrogen ionization fraction instead of the photosphere. This radius is also the right boundary of the graph. We present the photon diffusion time according to equation ( 1 ) by the red line, and the convection time according to equation ( 4 ) with the blue line. The diffusion time from R ion, 50 is . Note that the photon diffusion time becomes much shorter than the convection time in the outskirts of the envelope. Figure 7. Like Fig. 6 but at from the beginning of the plunge-in phase. At this time . Figure 8. Like Fig. 6 but at the end of the plunge-in phase at . At this time . From the figures we learn the following about the energy transport times in the inflated envelope. Convection can carry energy out from the entire hydrogen recombination zone very efficiently, as the convection transport time from 90 per cent hydrogen ionization fraction to the surface is shorter than the plunge-in time, in our case. The convection cells can move even faster, up to the sound speed that is larger than the convective speed of the
Paper: 2018ApJ...852..140W (fulltext)
FRB repeater exhibits several features commonly found in earthquakes. In fact, nonlinear dissipative systems always show self-organized criticality (SOC) behaviors. With a solid crust or stiff equation of state (EOS) of a pulsar, a star can build up stresses that make the crust crack and adjust the stellar shape in order to reduce its deformation. The characters for these processes of statistical independence, nonlinear coherent growth, and random rise times are consistent with an SOC system (Aschwanden 2011 ). According to the SOC theory, NS quakes are giant catastrophic events like earthquakes, and are probably accompanied by global seismic vibrations or oscillations. Hence, starquakes in a pulsar share similar statistical distributions with earthquakes. Here we present two possible scenarios. One scenario involves a normal NS with a solid crust and a superfluid core, and with a strong toroidal magnetic field (i.e., magnetar). An NS can form a solid crust quickly after its birth. The stellar shape changes from oblate to spherical configuration, and thermal and dynamic responses will induce stresses in the crusts. When stress buildup in the dense solid crust extends beyond a yield point a starquake occurs, with a sudden energy release that supports FRBs. This process also brings a slight change in the moment of inertia, with an abrupt jump of angular frequency that is the so-called pulsar glitch (Ruderman 1969 ; Link Epstein 1996 ). For a highly magnetized NS, the stellar crust couples with the magnetosphere. In this scenario, starquakes induce the magnetic curl or twist ejected into the magnetosphere from the crust in a few milliseconds (Thompson et al. 2002 , 2017 ). Electrons in the magnetosphere are suddenly accelerated to ultra-relativistic velocity by magnetic reconnection (Zhang Yan 2011 ) and move along the magnetic field lines, resulting in the production of curvature radiation. The characteristic frequency of the curvature radiation iswhere R c is the curvature radius with a typical value of ∼10 km, and γ is the Lorentz factor of electrons. With a detected FRB frequency ν c = 4–8 GHz, a γ ≈ 50–100 is required. If generated by such stress-induced reconnections (e.g., Lyutikov 2015 ), the FRB has an estimated duration timescalewhere the scale of the reconnection-unstable zone L ∼ 1–10 km, and the Alfvén velocity is v A ≃ B /(4 πρ c ) 1/2 ∼ 0.01 c , in which ρ c ≃ 10 14 g cm −3 is the average mass density of the crust. The sudden elastic and magnetic energy release in the crustal stress is estimated to bewhere h c ≃ R /30 ≃ 0.3 km is the crustal thickness (Thompson et al. 2017 ), ε is the shear strain, and the total stress including crustal shear stress and Maxwell stress in magnetosphere isin which μ is the shear modulus, B is the surface magnetic field, and B z is the component of magnetic field perpendicular to the direction of plastic flow. Within the crust, the force balance με ≃ BB z /(4 π ) implies that is smaller than ∼10 −2
Paper: 2020MNRAS.492.4409M (fulltext)
must be taken into account when analysing gas observations and comparing it with dust levels. However, if CO is unshielded, its short lifetime (∼120 yr) means that its mass will be set by the present mass-loss rate. Conversely, atomic carbon has a longer lifetime as it will viscously evolve on longer time-scales which will depend on the kinematic viscosity. We used this new numerical code to produce the first population synthesis model for exocometary gas around A stars. Population synthesis studies are ideal to deal with degenerated problems and provide constraints on population properties rather than individual systems. Informed by previous studies that fit the dust evolution, we generated samples of 10 4 stars hosting planetesimal discs with random radius, mass, and stellar properties. We evolved these systems up to a random age between 3–100 Myr and compare the final distribution to the observed distribution by applying the same selection filters to our model population. We found that our model can reproduce the distribution of CO masses well when viscosities are high (α ≈ 0.1), even producing a bimodal distribution with a large population of unshielded CO discs and a small fraction of shielded ones. The shielded population is nevertheless common in our models among systems with bright debris discs, which explains why shielded discs are common among the sample of 17 A stars with bright and cold debris discs. The high-α value implies that gas needs to be lost on time-scales of ∼1–10 Myr. Otherwise, carbon readily accumulates shielding CO and producing a large population of shielded and massive CO discs, even around systems with low planetesimal disc masses, which is inconsistent with observations. Although, we focused on A stars, we also tested our model against observations of FGK stars. While massive and shielded CO gas discs are found around A stars, observations of FGK stars have showed that these have low CO gas masses, with only a few detections. Using our model, we showed that this is consistent with the collisional evolution studies of discs around FGK stars compared to A stars. Their lower initial disc masses means that gas release rates are lower. Our model quantitatively shows that massive CO gas discs should be very rare around FGK stars if they have similar viscosity levels compared to A stars. An important test of viscous evolution models of gas in debris discs, is whether gas is observed to extend inwards and accrete on to the star. In Section 5 , we discussed recent observations of neutral carbon around a few systems which seem to indicate that carbon has not spread inwards forming an accretion disc as expected in a viscous evolution scenario. This might suggest that either gas release started recently or is lost through another mechanism, e.g. radiation pressure. Nevertheless, our modelling constrains the gas loss time-scale to be ∼1–10 Myr (viscous time-scale), which could provide insights into alternative