adsabs/WIESP2022-NER huggingface dataset:
Paper: 2021A&A...649A..91H (fulltext)
red giant clump (RGC), with its known de-reddened color and magnitude, in the CMD serves as a reference for the color and magnitude calibration. In the first step of the method, we estimated the combined (instrumental) flux from the source stars, F S, p = F S 1 , p + F S 2 , p , and the companion/primary flux ratio, q F, p , by fitting the KMTC photometry data set processed using the pyDIA code. Here the subscript “ p ” denotes the passband of observation. The measured values are ( F S, I , F S, V ) = (0.07751 ± 0.00060, 0.00909 ± 0.00032) and ( q F, I , q F, V ) = (0.0471 ± 0.0023, 0.0110 ± 0.0084). We note that the value of q F, I , which is derived from the pyDIA reduction, is slightly different (less than 1 σ ) from the value presented in Table 3 , which is derived from the pySIS reduction, because they come from different reductions of the data. Then, the flux values from S 1 and S 2 were estimated by respectively. From the measured flux values in the I - and V -bands, we estimated the colors and magnitudes of S 1 and S 2 to be ( V − I , I ) S 1 = (2.289 ± 0.043, 20.827 ± 0.010) and ( V − I , I ) S 2 = (3.868 ± 0.831, 24.143 ± 0.053), respectively. In Fig. 9 , we mark the locations of S 1 and S 2 with respect to the RGC centroid in the instrumental CMD that was constructed using the pyDIA photometry of the KMTC data (gray dots). Fig. 9. Locations of the primary and companion source stars with respect to the centroid of the RGC in the instrumental CMD (gray dots). The determinations of the source positions and the construction of the CMD are based on the pyDIA photometry of the KMTC data set. We also present the Hubble Space Telescope CMD ( Holtzman et al. 1998 , brown dots) to show the source locations on the main-sequence branch. Although the V -band flux of S 2 has a relatively large fractional (magnitude) error, it is strongly constrained to be faint in an absolute sense. In particular, we find (i.e., a 4.4 σ difference). This serves as a second line of evidence that the 2L2S solution is correct. If, for example, we had somehow missed a 3L1S solution, and the derived 2L2S solutions were merely mimicking it, then q F, I − q F, V should be consistent with zero because there is only one source with just one color. However, according to Eq. ( 4 ), this possibility is excluded at 4.4 σ . In the second step, we calibrated the color and magnitude. With the measured instrumental color and brightness of the source, ( V − I , I ), and the RGC centroid, ( V − I , I ) RGC = (2.473, 16.918), together with the known de-reddened values of the RGC centroid, ( V − I , I ) RGC, 0 = (1.060, 14.509) ( Bensby et al. 2013 ; Nataf et al. 2013 ), the reddening and extinction corrected color and magnitude of the source were estimated by where Δ( V − I , I ) denote the offsets in the color and brightness of the source from the RGC centroid measured on the instrumental CMD. This results in In Table 5 , we summarize the values of ( V − I , I ) RGC , ( V − I , I
Paper: 2017A&A...599A..11M (fulltext)
HWHM versus albedo. The modeled HWHM for 67P is located close to satellites of Mars, Phobos and Deimos, suggesting a similarity in the optical properties and structure of their surfaces, such as size of particles and porosity. The variation of the enhancement factor, against geometric albedo does not follow a recognizable trend (lower panel of Fig. 5 ). However, it shows two collections of data points, the values of the enhancement factor for all bright bodies studied in Rosenbush et al. (2002) are lower than 1.6, while for all dark objects they do not go beyond 1.8. It is notable that Phobos and Deimos including 67P do not resemble any group of data points. Another comparative study can be done for 67P and existing data for Centaurs and Kuiper belts objects (KBOs) ( Belskaya et al. 2008 ). Since these bodies are observed in the small phase angle range, for the comparison we only adopt the local phase curve of 67P at nm in the same phase angle range as those objects. The best-fit value of the phase coefficient in mag/deg for 67P is plotted together with the measured phase coefficients of KBOs and Centaurs (Table 1 of Belskaya et al. 2008 and references therein) with respect to the albedo (see Fig. 6 ). Fig. 6 Phase coefficient versus albedo for Centaurs, classical Kuiper belt objects (KBOs), and trans-Neptunian objects in band together with comet 67P/CG at nm. Figure 6 shows that 67P with the phase coefficient, , is located in Centaurs regions. The two particular Centaurs with similar phase coefficient to 67P are (54 598) Bienor and 1999 TD10. Centaurs are believed to have a greater steepness in their phase curve than other solar system bodies ( Bauer et al. 2003 ; Rousselot et al. 2005 ). 5.2. Comparison with laboratory measurements of the phase curve at small phase angles We also compared our results with laboratory measurements that study the dependence of the photometric characteristics of particulate surfaces on the surface properties, that is, albedo, grain size distribution, and porosity. There are not many experimental studies at very small phase angles. The measurements that are made in the opposition-effect region were carried out by Jost et al. (2016) for icy particles with a high-albedo close to unity and by Psarev et al. (2007) for low- and high-albedo samples. We found that the laboratory reflectance data from carbon soot at the wavelength of 630 nm in the phase angle range of 0.008–1.5 ( Psarev et al. 2007 ) show a behavior that is very similar to the measured local phase curve from the Imhotep-Ash region of 67P at nm. The local phase curve we extracted was normalized at to make it comparable with normalized laboratory measurements (see Fig. 7 ). In Fig. 7 two samples, the ultra-dispersed quartz and the carbon soot, behave similarly for the phase angles >0.2 (the limit we determined for the local phase curve of 67P from OSIRIS close-flyby images). However, light scattering by quartz sample is defined by its very special
Paper: 2019ApJ...870...90B (fulltext)
taken with the Broadband Filter Imager, and the chromosphere, using the H α 6563 Å line obtained with the Visible Imaging Spectrometer (VIS). The passband of the TiO filter is 10 Å, centered at 7057 Å, while its temporal resolution is about 15 s with a pixel scale of 00343. Concerning VIS, a combination of 5 Å interference filter and a Fabry–Pérot etalon is used to get a bandpass of 0.07 Å at the H α line. Its field of view (FOV) is about 70′′ with a pixel scale of 00323. To obtain more spectral information, we scan the H α line at 11 positions with a 0.2 Å step following this sequence: ±1.0, ±0.8, ±0.6, ±0.4, ±0.2, 0.0 Å. The time used in each scan is 23 s. Both high-order adaptive optics (Cao et al. 2010 ) and a speckle reconstruction postprocessing method (KISIP speckle reconstruction code; Wöger von der Lühe 2007 ) are employed to achieve diffraction-limited resolution images. IRIS data are taken in a very large, coarse 64-step raster mode, with a step size of 035, step cadence of 31.8 s, and a raster cadence of 2036 s. The exposure time at each step is 29 s. Several strong emission lines are recorded, such as Si iv 1402.77 Å, Si iv 1393.7 Å, C ii 1334.53 Å, and Mg ii k 2796.35 Å. The cadences of the SJI in the passbands of 1400, 2796, and 2832 Å are all 112 s. The spatial resolution is about 033, and the FOV is 224 × 175′′ and 175′′ × 175′′ corresponding to the 64-step raster mode and the SJI. All of the spectra and images used in the analysis are level 2 data, including dark current subtraction and flat-field and geometrical corrections (De Pontieu et al. 2014 ; Tian et al. 2014 ). Hinode/SP data are acquired in a fast mode with an FOV of 81′′ × 81′′, a step size of 0297, and a raster cadence of 1080 s. Additionally, in order to analyze the corona response to our event, we have used SDO data, including the EUV and UV passbands from the AIA (Lemen et al. 2012 ) with cadences of 12 s and 24 s, respectively. The spatial register between the GST and SDO is first done by coaligning the AIA 1600 Å images with the GST/TiO data, and then coaligning the TiO data with the H α images at different wavelength positions. We use the AIA 1600 Å, IRIS 2832 Å, and SP continuum images to align the SDO , IRIS, and SP data. The uncertainty of the coalignment is about one AIA pixel (06). Figure 1 contains the context image of the LBs and fan-shaped jets on the sunspot of AR 12127 that we analyze in the subsequent section. The figure shows data from GST, IRIS, and SDO /AIA after the alignment process. Figure 1. Context images of the LBs and fan-shaped jets on the sunspot of AR 12127 obtained on 2014 August 1 around 17:27 UT. The different panels show (a) the photosphere through TiO images from GST, (b) the chromosphere via Ha LOS velocity obtained with GST/VIS, (c) the TR through SJI 1400 Å images from IRIS, and (d)–(i) the corona response observed with the different filters of SDO /AIA. R1 illustrates the LB region, to be analyzed in Figure 3 . L1 represents
Paper: 2016A&A...594A.115S (fulltext)
a kinematical distance of 2.0 kpc. An uncertainty of 0.5 kpc is assumed, adopting a velocity dispersion of 2.5 km s for the interstellar molecular gas. We report molecular line observations of the IRAS source using tracers of low and high density regions with the aim of studying the molecular gas content of the source, identifying dense gas clumps, finding massive young stellar objects (YSOs) linked to the clumps, and identifying possible outflows. 2. Molecular line observations IRAS 085894714 was observed with the 12 m Atacama Pathfinder EXperiment (APEX) telescope 1 , located in Llano de Chajnantor, in the Puna de Atacama, Chile. We carried out observations in the CO(32), CO(32), CO(32), HCO(32), and HCN(32) molecular lines using the On-The-Fly mapping technique. These observations were made on 2014 June 16, 19, and 21. The CO isotopes were observed with the receiver APEX2 in the spectral range of 343.8347.8 GHz and in the range 328.6332.6 GHz with a half-power beamwidth of 18, while the HCO and HCN molecules were observed with the receiver APEX1 in the spectral range of 265.6269.5 GHz with an HPBW of 22 ( Vassilev et al. 2008 ). Fig. 1 Spectra of the CO(32), CO(32), and CO(32) lines indicated in black, red, and blue, respectively. Each spectrum is the average of the profiles within a field of 25.̋5 25.̋5. The total area is 150 150 for three molecules. The locations of sources 1 (S1) and 3 (S3) are labeled. In each panel the velocity ranges from 4 to 15 km s and scales from 2 to 18 K. We mapped an area of 150 150 covering the central region of the IRAS source and the 1.2 mm emission zone detected by Beltrán et al. (2006) . The APEX1 system temperature is 150 K and 300 K for APEX2. The data reduction was performed according to the standard procedure of the CLASS software, Gildas 2 . The antenna temperature, , was transformed to main-beam brightness-temperature (), using a main beam efficiency for APEX1 and APEX2 ( Vassilev et al. 2008 ).The data were obtained with a velocity resolution of 0.11 km s. The final rms is 0.3 K. 3. Identification of YSOs To investigate the presence of YSOs coincident with the IRAS source in the Wide-field Infrared Survey Explorer (WISE) catalog ( Wright et al. 2010 ), we applied the following criteria ( Koenig et al. 2012 ). Class I objects are those that satisfy and , whereas Class II objects have and , where , , , and are the magnitudes in the four WISE bands at 3.4, 4.6, 12, and 22 m, respectively, and and are the combined errors of and , respectively 3 . Three sources with colors of Class I/II were identified. Their coordinates and correlation with 2MASS sources are indicated in Table 1 . Sources 1 and 3 are projected onto the dust clump detected by Beltrán et al. (2006) . 4. Molecular line analysis 4.1. The <inline-formula specific-use="simple-math"><sup>12</sup></inline-formula>CO, <inline-formula specific-use="simple-math"><sup>13</sup></inline-formula>CO, and C<inline-formula
Paper: 2016MNRAS.461..402T (fulltext)
the outermost regions of clusters. For example, Fig. 8 shows a snapshot of the plane ( J z , R ) for model KF05, with the potential escapers highlighted in green. It is evident that almost all of the outer cluster stars beyond approximately 0.5 r J are potential escapers. This result is in general agreement with the findings of Küpper et al. ( 2010 ), who first showed that the behaviour of the surface brightness and velocity dispersion radial profiles are significantly affected by the presence of an outer population of potential escapers. Figure 8. The same as the last panel of Fig. 5 , but with the unbound particles highlighted in green. The fraction of unbound particles as a function of the fraction of the mass remaining in the cluster for all our locked models is illustrated in Fig. 9 . As discussed in Fukushige Heggie ( 2000 ) and Baumgardt ( 2001 ), initial conditions set by sampling, for example, a King model may include a fraction of stars which are unbound when an external tidal field is added. This is the case for our KF1 model. For this model, we show the evolution of the fraction of potential escapers both with and without this population of primordial potential escapers. All the other models do not have any primordial potential escapers. Figure 9. The fraction of unbound particles as a function of fraction of mass remaining in the cluster for all locked models. For KF1, there are two separate lines for including primordially unbound particles and excluding them. Fig. 9 also shows that the fraction of potential escapers increases significantly over time reaching a fraction of the remaining mass equal to about 15 per cent by the end of our simulations. Such a behaviour is qualitatively consistent with the findings reported by Baumgardt ( 2001 ), in which tidally perturbed models (initialised as critically filling King model W 0 = 3, i.e. characterized by a much higher fraction of primordial potential escapers, about 15 per cent) possess approximately 20 per cent of potential escapers during the final stages of evolution. We have examined the evolution of the fraction of prograde and retrograde particles within the populations of bound and unbound particles in models KF1 and KF025, as representative of the two filling regimes (see Figs 10 and 11 , respectively). The larger fraction of retrograde particles in the population of unbound particles is the result of the two effects discussed in Section 3.2 : the preferential escape of prograde particles and the fact that, in the transition from bound to unbound, some particles move on more eccentric/radial orbits becoming retrograde as they move outwards. Figure 10. The time evolution of model KF1 of the fraction of retrograde stars within the entire system, and within energetically bound and unbound particles. The bottom panel is a zoomed in version. The red line shows the fraction of unbound particles that do not include the primordially unbound stars. Note that the black solid lines
Paper: 2017A&A...608A.138G (fulltext)
with ) based on their line properties alone. We compare the results from the simulations to what is expected when using the negative image FDR as reference. For the latter, we estimate the probability of an emission line with of being false by taking , where is the number of emission lines with found in the negative data, while is the number found in the positive (“real”) data. This means that for equal numbers, there is a 100% probability that the line is produced by noise. Alternatively, if there there are twice as many positive lines as negative ones, we assume that there is a 50% probability that each positive line is real. A comparison between simulations and negative image FDR probabilities for each cluster is shown in Fig. 4 . We see that using the negative image FDR as a reference for estimating the probability of a line being false returns a much noisier and sharper probability distribution for all of the clusters. At a given S/N value, it can strongly under- or overestimate the probability since it is dominated by small number statistics. Using simulations allows us to more accurately assign probabilities and understand the true detection rate at low . To confirm weaker real emission lines, we investigate the NIR and 1.1 mm counterparts of all of our candidates. Fig. 4 Probability of an emission line with a given of being produced by noise for the five clusters. Solid curves correspond to the probabilities given by the simulations, while dashed curves correspond to the probabilities estimated from the negative data. 3.3. Association with optical/NIR counterparts Clearly galaxies with high SFRs are likely to be detectable both with HST and/or ALMA in continuum and in molecular emission lines. Because of this, we expect that an emission line candidate co-spatial to a NIR detected galaxy should increase the probability of this candidate being real and thus use the NIR images for this purpose. However, the lack of a NIR or 1.1 mm counterpart does not necessarily imply that the emission line is noise. A galaxy that remains undetected both in HST/160 and ALMA continuum at could still have a at and at , based on spectral energy distribution fitting. In such cases, it should still be possible to detect CO, [NII], or [CII]lines. For instance, we find that CO can be detected at from CO lines when a high CO excitation level () is present in combination with strong dust extinction (). Detections of [NII]and [CII]lines can be made to lower SFRs and extinctions () at . Thus, some weak line candidates that lack NIR counterparts could still be real. Unfortunately, in such cases, confirmation and identification of line candidates will only be possible with deeper mm observations, which is beyond the scope of this study. Thus, we restrict our analysis of weak emission line candidates to those with nearby optical/NIR detected sources. Based on the number and spatial distribution of NIR detections in the FFs, a given random position within any of
Paper: 2019A&A...621A.140J (fulltext)
a L ~10 3 L ⊙ low-mass YSO cluster (e.g. Estalella et al. 1993 ; Quanz et al. 2007 ). Four of the YSOs, namely VLA1-4, are known to be associated with thermal radio jets ( Anglada et al. 1994 ). Based on the previous, lower angular-resolution observations of C 18 O (1–0), Umemoto et al. (1999) estimated the enclosed gas mass over the ~ 0.5-pc-scale parent molecular gas structure to be ~120 M ⊙ . Contrasting to the aforementioned OB cluster-forming regions, the bolometric luminosity of L1287 is not contributed by the nuclear burning of OB stars, but instead is contributed by the accretion luminosity of the low-mass protostars, including two known FU Orionis objects 1 RNO 1B/1C( Staude Neckel 1991 ; Kenyon et al. 1993 ; McMuldroch et al. 1995 ; Quanz et al. 2007 ), and a L ~ 600 L ⊙ Class 0/I YSO IRAS 00338 + 6312 ( Anglada et al. 1994 ). Earlier observations resolved bipolar CO outflow(s) aligning in the NE-SW direction ( Snell et al. 1990 ; Yang et al. 1991 ; Fehér et al. 2017 ), although the identification of the powering source(s) remains uncertain. Table 1 SMA observations summary. In this paper, we report the ~ 1′′ (~ 930 AU)-angular-resolution observations with the Submillimeter Array (SMA) 2 , covering the inner ~0.25-pc region of L1287. By examining the resolved 1.3 mm dust continuum emission and various molecular line tracers of dense gas, warm gas, shocks, and outflows, our aim is to elucidate how the gas flows converge from parsec scales (e.g., due to gravitational collapse) down to ~ 1000 AU scales, and how they are dynamically forming the low-mass YSO cluster. We also provide a more definite identification of the powering source of the previously reported molecular outflows. The details of our observations are presented in Sect. 2 . The observational results from the dust continuum and molecular line emission are given in Sect. 3 . In Sect. 4 we present an analysis of fragmentation, dense gas kinematics, and powering sources of the previously reported CO outflows. Our conclusions are given in Sect. 5 . 2 Observations and data reduction 2.1 Submillimeter Array observations We performed five tracks of SMA observations at ~1.3 mm wavelengths towards the inner ~0.25-pc region of L1287 between August 2013 and July 2014, which are summarized in Table 1 . The pointing and phase referencing centers of the observationsare RA(J2000) = 00 h 36 m 46.65 s , Dec(J2000) = + 63°28′57.90′′. The projected baselines of these observations range from ~4 to ~ 140 k λ . The system temperature T sys for all the observations was around 150 K. The observations were obtained with the 230 GHz receiver, with 4 GHz bandwidth in each of the upper and lower sidebands. The correlator consisted of 48 chunks, each with a bandwidth of 104 MHz. The frequency was centered at 231.3 GHz at chunk 35 of the upper sideband (USB). This configured the correlator with the lower sideband (LSB) covering from 216.48 to 220.46 GHz and the USB from 228.46 to 232.43 GHz. These
Paper: 2019A&A...631A..49K (fulltext)
misalignment angles in 3C sources are known to extend up to values of about 12° or more ( Leahy Williams 1984 ). We thus consider the interpretation of the S5 0836+710 large-scale morphology as an FR II radio galaxy at a small viewing angle as realistic. 4.3. Derivation of the jet parameters The total jet power for a relativistic jet is parameterized as (see, e.g., Perucho et al. 2017 ): where is the jet specific enthalpy, Γ j is the jet Lorentz factor, ρ j is the jet rest mass density, v j is the jet velocity, c is the speed of light, B φ is the toroidal field in the observer’s frame, γ j is the ratio of specific heats of the jet gas, and A j is the jet cross-section. The first term in Eq. ( 2 ) includes the kinetic, internal, and rest-mass energy contributions, and the second term stands for the magnetic energy of the jet. We can assume (see Appendix B ) that the jet is kinetically dominated and in the cold regime (i.e., its magnetosonic Mach number is high). Furthermore, taking into account that the advance speed as measured by LOFAR is also so slow, the velocity of the bulk plasma flowing into the hotspot can be assumed to be only mildly relativistic at most (see also Appendix C for the relativistic derivation). Under these conditions, the magnetic and pressure terms can be neglected and Eq. ( 2 ) simplifies to Across a strong shock, the hotspot pressure is (e.g., Landau Lifshitz 1987 ) In this equation, we need to define the jet radius at the hotspot, R j, h , which can be approximated as the hotspot radius. Because we do not know whether the southern radio structure includes the hotspot and part of the lobe or if it is the hotspot, we considered half of the whole region as the jet radius (4.5 kpc) and half of the fitted component, which represents the brightest region within the hypothetical lobe (2.5 kpc). Although the polarization seems to favor the latter interpretation (see the previous section), we study both cases here. Furthermore, we need an estimate for v j at the hotspot, v j, h . As we show in the following paragraphs, any reasonable input value is sufficient because we define an iterative method to derive its convergence value. When the hotspot pressure is obtained, we can use equipartition between the nonthermal particles and the magnetic field, as reported for FR II hotspots (see e.g., Hardcastle Worrall 2000 ), to obtain a value of the magnetic field at the interaction site. The value of the magnetic field prior to the reverse shock can be constrained by assuming conservation of the magnetic flux from the 1.6 GHz jet to the interaction site 3 . Applying the magnetohydrodynamcis (MHD) jump conditions at the reverse shock that give rise to the hotspot, allows us to derive a new estimate for v j, h . Setting a convergence criterion for this parameter at a precision of 10 −3 , we can determine the relevant parameters of the problem. We applied this method to four different sets of hotspot velocity and radius: the possible