adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016MNRAS.461.3847G (acknowledgments)
DKG acknowledges the support of an Australian Research Council Future Fellowship (project FT0991598 ). This paper utilizes preliminary analysis results from the Multi-INstrument Burst ARchive (MINBAR), which is supported under the Australian Academy of Science's Scientific Visits to Europe program, and the Australian Research Council's Discovery Projects funding scheme. This research has made use of data and software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC), which is a service of the Astrophysics Science Division at NASA/GSFC and the High Energy Astrophysics Division of the Smithsonian Astrophysical Observatory.
Paper: 2018ApJ...868..147P (fulltext)
rates and substellar velocities. Figure 13. Mid-tropospheric atmospheric temperature ( p = 658 hPa). The temperature reference in the lower right corner of each pane indicates the value of the highest temperature contour, with successive cooler contours at 2 K intervals. The central column (tidally locked) phase-curve examples are shown in Figure 12 . At this height in the atmosphere, , there is no frictional damping. In the stratified model, we find a more complicated relationship than in the shallow-water study. At the surface, the thermal response is tightly coupled to the forcing, and at all rotation rates, the peak integrated temperature is lagging the motion of the substellar point. However, at altitude, from where observed infrared emission will originate, the temperature distribution is sensitive to the speed of the diurnal cycle. Above the boundary layer, momentum and temperature are less strongly damped, thermal advection is efficient compared to friction, and the hot spot is advected by the wind field. Figure 13 shows the horizontal temperature structure in the mid-troposphere; for both eastward- and westward-propagating substellar points, eastward and westward hot spots are observed, depending on the rotation rate of the planet. As previously demonstrated in the hot Jupiter studies of Showman et al. ( 2015 ), a quickly moving substellar point, or rapidly rotating system results in a reduction in zonal variability. At the mid-troposphere example plots shown in Figure 13, there is an ∼65 K gradient between substellar and antistellar points in the equilibrium temperature T eq ; in contrast, the atmospheric temperature varies little, with an efficient thermal transport from dayside to nightside. The efficient heat transport and zonal redistribution with a rapidly moving substellar velocity predicts relatively warm nightside temperatures and a largely isothermal distribution of temperature in the upper atmosphere; this is perhaps expected from our intuition of Earth, which has a very rapid diurnal cycle relative to atmospheric radiative timescales, . The reduction in the meridional temperature gradient is also a result of the short diurnal timescale, providing an effective relaxation profile, as shown in Figure 7 and discussed above. The phase-curve offset is found by calculating the normalized phase curve relative to the substellar point using Equation ( 22 ) and then solving for the longitude of maximum integrated thermal emission. The panels of Figure 14 show the phase-curve offset as a function of substellar velocity near the surface and at several levels in the troposphere. Phase curves near the surface are a strong function of substellar velocity, with little influence from rotation rate; in general, the faster the substellar point moves, the further the thermal hot spot has lagged behind the point of maximal heating. This is due to the short timescales of both radiative and frictional damping in the bottom boundary of the
Paper: 2017MNRAS.471..337B (fulltext)
the sources H ii 1, 2 and 6 are the extrapolated thermal flux density estimated using H emission. For the sources H ii 2 and 6, comparing the best-fitting parameter m to equations ( 1 ) and ( 2 ), we estimate the thermal freefree emission to be optically thick ( ff 1) below 0.220.03 and 0.410.05GHz, respectively. Recently, Hindson etal. ( 2016 ) in a study of Galactic H ii regions, found evidence of a turnover in the freefree spectrum typically with turnover frequencies in the range 0.31.2GHz. We estimated 8 the EM to be (1.20.3)10 5 and (4.6 1.2) 10 5 pccm 6 for H ii 2 and 6, respectively which in turn is related to the average thermal electron density n e as (Berkhuijsen, Mitra Mller 2006 ): where, f is the filling factor and h HII is the size of the H ii region along the line of sight. Assuming a typical f 5percent for the clumpy star-forming disc (Ehle Beck 1993 ) and h HII 50pc, i.e. the spatial resolution of our observations, we estimate n e to be 11 and 22cm 3 for H ii 2 and 6, respectively, which are typical values for H ii regions (Hunt Hirashita 2009 ). Deeg etal. ( 1993 ) pointed out that such values of EM and n e are necessary to explain the radio continuum spectra of star-forming blue compact dwarf galaxies. To better constrain n e and the sizes of the H ii regions, high-resolution radio continuum observations at even lower frequencies with LOFAR will be necessary. The thermal emission independently estimated using extinction-corrected H emission well represents the emission in the three H ii regions (shown as black dotted lines in Fig. 6 ). This suggests that the extinction-corrected H emission is a good tracer of the thermal freefree emission on scales below 100pc. Since, the total radio continuum emission in these regions are already consistent with 100percent thermal emission, it is difficult to estimate the contribution of the non-thermal component. We have therefore blanked these pixels in our future calculations. 4.2.2 Non-thermal bubble An interesting feature observed in the maps of and nt lies towards the south-eastern edge of IC10 marked as the non-thermal bubble in Fig. 3 . The bubble was first identified in the radio continuum observations of Yang Skillman ( 1993 ). The sharp boundary of this region is distinctly visible only in the spectral index maps (see Fig. 4 ). The total intensity emission is merged with the bright H ii region H ii 1 and does not show the bubble distinctly. In Fig. 7 , we show a zoomed-in view of the spectral index map. We mark the sharp boundary of the bubble and determine its centre to be at RA = 00 h 20 m 29 s and Dec. = 591639.5. The non-thermal bubble extends 300pc in the north-east to south-west direction and 100pc in the north-west to south-east direction. Its north-western edge, where the spectrum flattens from being non-thermal with 0.6 to thermal 0.1, is bound by GMCs as observed by Leroy etal. ( 2006 ), shown as the black circles in Fig. 7 . This suggests that the GMCs likely confine
Paper: 2018A&A...616L...2K (acknowledgments)
This work has made use of data from the European Space Agency (ESA) mission Gaia ( https://www.cosmos.esa.int/gaia ), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium ). This research has made use of the SIMBAD data base and the ALADIN applet, operated at CDS, Strasbourg, France. D.B. was supported by FONDO ALMA-Conicyt Programa de Astronomía/PCI 31150001.
Paper: 2020ApJ...905...26L (fulltext)
2019 ). Here, the uncertainty in the wavelength calibration in Doppler units is expected to be about 1 km s −1 . Information of the two target lines and their associated calibration lines is listed in Table 2 . After the wavelength calibrations, the Si iv and Mg ii k lines have redshifts of 2.3 km s −1 and 3.1 km s −1 , respectively, in the quiet Sun region. Here, the Doppler shift of Mg ii k line is obtained using the central absorption at k3, and unrelated to the spectroscopic results of coronal rain. Figure 4. Spectral information of the coronal rain observed by IRIS. Maps of intensity (a1)–(a2), Doppler shift (b1)–(b2), and line width (c1)–(c2) of Si iv (1394 Å) (a1)–(c1) and Mg ii k (2796 Å) (a2)–(c2) lines for the IRIS raster scan #3. Like in Figure 2 (a), the blue rectangles and diamond separately indicate the positions of northern and southern parts of the coronal rain, which is enclosed by the blue dashed–dotted lines. The FOV is denoted by the pink rectangle in Figure 2 (a). See Section 4.1 for details. Table 2 Lines of Interest Note. Listed are the lines, the rest wavelengths of the lines, the Doppler shifts (Δ v ) of the rest wavelengths of the lines to the Si iv (upper) and Mg ii k (lower) lines, and the absolute Doppler shifts of the lines in the spectrum averaged over a quiet Sun region after the wavelength calibrations. Positive (negative) values of the Doppler shifts correspond to redshifts (blueshifts). The rest wavelengths of the lines are obtained from the line list of Tian ( 2017 ). Similar spectroscopic results of coronal rain are obtained for the four middle raster scans of IRIS, i.e., from scans number two to five. Among them we take the results for the third raster scan for example, and display them in Figure 4 . The left and right columns of Figure 4 show the maps of intensity, Doppler shift, and line width of the Si iv and Mg ii k lines, respectively. Here, the instrumental line width of about 26 mÅ is subtracted from the Gaussian line width (De Pontieu et al. 2014 ). In these maps, the line fit parameters outside the locations of the coronal rain are not shown as they are not well-fitted because of low count rates. Therefore, we only concentrate on the coronal rain region enclosed by the blue dashed–dotted lines in Figure 4 . Same as in the IRIS 1400 Å SJIs (see Figure 2 (a)), two substructures of the coronal rain are identified, marked separately by the blue square and diamond signs in Figure 4 . This demonstrates that in our observations in the coronal rain, the 1400 Å channel is indeed dominated by the transition region Si iv line. Comparing the Si iv and Mg ii k intensity maps, we find that the coronal rain seen in the Mg ii k line is located mostly at the same locations as the Si iv coronal rain; see Figures 4 (a1)–(a2). At the north (south) coronal rain, we measure the intensity, Doppler shift, and line width, and obtain the mean values of 46 (18) DN pixel −1 , 7.5 (5) km s −1 , and 8.6 (7.3) km s −1 for the
Paper: 2017MNRAS.465.4650K (fulltext)
models that terminate at values in agreement with the inferred luminosity and temperature for SN 2016gkg (as discussed in Section 3.4.2 ). The best-fitting model has an initial stellar mass of M 15M with a 1.5-M companion. The initial period is 1000d and the primary star explodes with M 5.2M . Two additional examples with initial masses 12M (8.4-M initial mass companion, 160-d period) and 16M (14.4-M initial mass companion, 6.3-d period) are shown with dotted and dashed lines, respectively. All of these models agree with the inferred luminosity and temperature of SN 2016gkg. We find that it is extremely unlikely that SN 2016gkg originated from a single star. Woosley Heger ( 2007 ) and Sukhbold etal. ( 2016 ) have found that, for stars with M ZAMS 30M , the pre-SN iron core is too large for an SN to be successful. Moreover, mass-loss is sufficiently strong so that most of these stars lose their entire hydrogen envelopes and are thought to end their evolution as WolfRayet stars, implying that the subsequent SN would be Type Ib or Ic. SNe IIb require progenitor stars with extended low-mass hydrogen envelopes (Podsiadlowski 1993 ; Woosley etal. 1994 ; Elmhamdi etal. 2006 ), and any single-star model for such a system would require finely tuned mass-loss that would otherwise fail to reproduce the observed range in SN IIb light curves, spectra, and progenitor stars. While the single-star scenario could describe a minority of SNe IIb, it is likely that the majority of these systems come from binary-star systems such as the one observed towards SN 1993J (Maund etal. 2004 ; Fox etal. 2014 ). 3.4.2 Binary-star models We examine evolutionary tracks involving binary stars in order to assess the plausibility of these systems as possible progenitor stars for SN 2016gkg. We obtained our binary-star evolutionary tracks from the Binary Population and Spectral Synthesis ( bpass ) code as described in Eldridge Stanway ( 2009 ). These models provide a range of metallicities ( Z 0.0010.040), primary-star masses ( M /M 0.1300), mass ratios ( q 0.10.9), and initial periods [log( P /1d)04]. We fixed the metallicity of the binary-star models to Z 0.010 in order to provide the best match to the observed metallicity of NGC 613. Otherwise, we examined the full range of parameters provided by bpass . For our fitting scheme, we looked for binary-star models that produced a primary star with terminal luminosity and temperature that minimized Overall, we found that 107 out of 5565 bpass models terminated with primary-star luminosity and temperature within our measurement uncertainties for the SN 2016gkg progenitor star. Of these models, the 2 ranged from 0.11 to 4.01 with a median value of 1.05. In Fig. 4 , we show the stellar evolution of the best-fitting binary-star model on the HR diagram along with the inferred luminosity and temperature of the SN 2016gkg progenitor star. The primary star has an initial mass of 15M while the secondary (accreting) star has an initial
Paper: 2020MNRAS.496...36P (fulltext)
in the strong peaks of emission towards the top and bottom of this figure, at distance of 19 arcsec or 1.8 kpc from the nucleus. The spectrum shows complex nuclear structure, with multiple components, including a very rapidly rotating structure, which we interpret as a star-forming nuclear ring. Between the nuclear and bar-end rings, diffuse emission is apparent, particularly in the upper part of Fig. A2 . Thus, in spite of its peculiarity, we do consider this an example of the SFD phenomen, and it is included as such in this paper. Figure A2. Two-dimensional optical spectrum of NGC 3729, centred on the H α and [N ii ] lines. The emission-line clump is indicated by the arrows. Comparison with the bright H ii region towards the bottom of the frame shows the extended nature of the line emission from the clump. The unusual feature seen in Fig. A2 is the peak of emission seen just below the nuclear ring, 5.7 arcsec (560 pc) from the nucleus. At first sight, this resembles an H ii region, but uniquely, in the current data set at least, it shows clear LINER-type ratios. To illustrate this point, Fig. A3 shows the extracted spectrum of this peak in the lower frame, with an H ii region spectrum from the same long-slit observation shown in the upper frame for comparison. The spectra are clearly different, and argue against ongoing SF in the near-nuclear clump. The clump has [N ii ] and H α EW values of 5.63 and 6.73 Å, respectively, similar to or slightly greater than the values for the two SFD regions in NGC 3729 (4.70 and 3.69 Å for [N ii ], 6.76 and 4.50 Å for H α). These values are all at the high end of the EW distributions for line emission from SFD regions, while the [N ii ]/Hα ratio for the clump, 0.837, is entirely consistent with the distribution of ratios for SFD regions (Fig. 1 , lower panel). Figure A3. Extracted H α and [N ii ] emission for the NGC 3729 clump (bottom) and, for comparison, an H ii region in the same galaxy (top). The high [N ii ]/H α ratio in the clump is clearly apparent. One possibility is that the near-nuclear clump could be the nucleus of the tidally shredded companion that has been drawn towards the centre of NGC 3729 through dynamical friction. One test of this is to look for spatial extent. Visual inspection of Fig. A2 indicates that the clump appears moderately extended, e.g. compared with the most compact H ii region (towards the bottom of the image). Measurements confirm this; along the spatial direction, the clump has a full width at half-maximum (FWHM) of 5.3 pixels, or 2.33 arcsec, compared to 3.7 pixels or 1.63 arcsec for the compact H ii region. As the latter may itself be somewhat extended, we also measured the FWHM of the standard star observation taken closest in time to the NGC 3729 spectra, finding values of 3.2 pixels or 1.4 arcsec. Taking either the star or (conservatively) the H ii region as a measure of the seeing broadening the clump FWHM, the true size of the clump is 1.9 or 1.7 arcsec,
Paper: 2018MNRAS.481.4984M (acknowledgments)
ACKNOWLEDGEMENTS Based on observations with the Atacama Pathfinder EXperiment (APEX) telescope. APEX is a collaboration between the Max Planck Institute for radio Astronomy, the European Southern Observatory, and the Onsala Space Observatory. The authors acknowledge support from the UK Science and Technology Facility Council under grant ST/L000768/1. iraf is distributed by the National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under co-operative agreement with the National Science Foundation.
Paper: 2019MNRAS.485.1990R (fulltext)
the rise time of the light curve can be also used to estimate the radius of the progenitor of type IIP supernova through the relation between the progenitor radius and the rise time of the light curve, i.e. log R(R ⊙ ) = (1.225 ± 0.178) log t rise (d) + (1.692 ± 0.490) (Morozova et al. 2016 ). For SN 2017eaw, the rise time is estimated to be t rise = 6.81 ± 0.85 d in the g band, which gives an estimate of the radius as 515 ± 180 R ⊙ . The above two estimates of the progenitor radius agree within 1σ error. Figure 6. Constraining the progenitor radius of SN 2017eaw based on the cooling of the photospheric temperature in the early phase after the explosion. The red dots are the temperatures inferred from the blackbody fit to the observed UV and optical photometry; while the red curve represents the best fit of the radius. The green and black curves show the upper and lower limits of the estimates of the radius, respectively. The blue stars show the temperature evolution of SN 1987A, and the blue dashed line shows the corresponding best-fitting radius using the theoretical model (Rabinak Waxman 2011 ). We also try to fit the observed SED of the progenitor star from the prediscovery HST and Spitzer images with synthesized spectra calculated using the stellar evolution code marcs . 4 However, the best-fitting model spectrum has an effective temperature of only about 2500 K [A similar value of 2600 K was also suggested by Kilpatrick Foley ( 2018 )] with A V = 1.83 ± 0.59 mag by including the Spitzer data (Fig. 7 ), much lower than that inferred for the HST data alone. Given the luminosity, the lower temperature would result in an effective radius of 1330 R ⊙ for the progenitor, which is inconsistent with the estimate either from the rise time or temperature evolution of the shock cooling in the early phase. Despite an overall reasonable fit, the measurements in two Spitzer bands may suffer large contaminations of the nearby red sources due to large aperture photometry and/or the presence of circumstellar dust. In the latter case, the light of the progenitor star is scattered/absorbed by the surrounding dust and re-emitted at longer wavelengths [see also the analysis by Kilpatrick Foley ( 2018 )]. We also derive the F606W-band magnitude in 2004 by assuming that the dimming behaviour in F814W-band is totally due to the CSM dust. Taking into account this speculated F606W-band magnitude and the observed F814W-band magnitude obtained in 2004, the SED of the progenitor inferred in 2004 matches with the theoretical stellar spectra model characterized by an effective temperature of 3550 ± 150 K and a radius of 636 ± 155 R ⊙ (see Fig. 7 ). As an alternative, the dimming behaviour in F814W band could be also due to the intrinsic variation of an RSG star, but this explanation is inconsistent with either the observation taken at one year to a few days before the explosion or the theoretical prediction for its final stage evolution (see discussions in
Paper: 2016A&A...589A..37V (fulltext)
an external cold medium during the slow cooling regime to derive all the micro-physical and dynamical parameters ( Mészáros Rees 1997 ; Granot Sari 2002 ), and subsequently check for consistency with the slow or fast cooling transition times. Both spectral regimes, that is, , are explained and analysed in detail in the following subsection. The former corresponds to the jet in the light curve being associated with a jet break without energy injection, and the latter corresponds to the jet in the light curve associated with either the end of energy injection into the outflow or with a jet break with an ongoing energy injection during the whole evolution of the afterglow (i.e. the ongoing energy injection is still visible until the last observations). Table 4 Closure relations * . was use in the analysis. Notes. When determining the energy-injection parameter , we use the measured and . The equations used for are for the case when , for both spectral regimes. More details in Racusin et al. (2009) . (*) When and it does not depend on or . We did not include this scenario as it is not compatible with our data at any time. (**) Details on the results and implications of the closure relations are discussed in the outlined section. (a) For , . When we have (). (b) For . When we have (). 4.1. <inline-formula specific-use="simple-math"><italic>ν</italic><sub>c</sub> <italic>ν</italic><sub><italic>K</italic><sub>s</sub></sub></inline-formula>: Jet break Using the closure relations for a decelerating spherical blast wave, we find that the measured temporal slope before the break in the light curve is consistent with for both ISM and wind environments. This implies , as . The only plausible scenario consistent with the measured and corresponds to a non-spreading uniform jet propagating into a wind environment. We therefore associate the achromatic break observed in the light curve with a jet break ( Rhoads 1999 ; Wiersema et al. 2014 ). We proceed by including the post-break sub-mm and radio data in our analysis. The first broadband SED contains GROND, XRT, and APEX data. The best fit to this is a broken power law with both Galactic and host extinction and absorption, with (see Table 5 ). The measured value of Hz is a lower limit because the APEX measurement is an upper limit. The second broadband SED contains XRT, GROND, CARMA, and EVLA detections. Two possible spectral sub-regimes in the slow cooling phase give a good fit to the data: the cooling regime where , and the one where . Because there are only a few data points at radio wavelengths, it is difficult to distinguish between these two cooling regimes. Therefore, we analysed both cases. When (i.e. a hard electron spectrum), there is more energy-per-decade in high-energy electrons. This distribution has important implications for the analysis of the physics in the shock region, specifically requiring an additional high-energy cut-off in the electron population. We based our analysis on the