adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019MNRAS.482.5542J (fulltext)
to a symmetry property of the solution to the transfer equation. To solve this problem, some specific ‘disambiguation’ techniques have been developed. The authors point to one special case where the ambiguity is resolved by the data when combined with knowledge of the state of excitation of the radiating atoms. A purely spectroscopic disambiguation method has also been devised (Landi Degl’innocenti Bommier 1993 ) based on the observation of the Stokes parameter profiles in resonance lines originating from transitions between polarized atomic levels . In this case, the radially streaming radiation from the solar atmosphere introduces a ‘symmetry breaking’ in the physical conditions that allows one, in some cases, to recover the magnetic field vector without ambiguity. The problem remains, even here, that one must know the state of atomic populations of the Zeeman-split M states within the atomic levels. Such conditions exist only for particular radiative transitions. Most polarimetry is performed on photospheric lines formed where collisions tend to enforce equality of M-state populations within local thermodynamic equilibrium (LTE) levels, negating the possibility of any atomic polarization and of symmetry breaking through the radiation field. More worrying, the ‘disambiguation’ methods inflict prior assumptions on solutions to produce ‘inverted’ data compatible with both the assumptions and the data themselves. Especially worrisome are studies seeking to minimize part of the energy of a system, and/or those seeking some kind of minimal discontinuity in the magnetic structure sampled at the photosphere. Such constraints cannot be theoretically supported, the latter, for example, explicitly reject classes of solutions available to magnetohydrodynamics (MHD). ‘Weak’ MHD solutions (e.g. Courant Hilbert 1962 ) exist under conditions encountered on the Sun. Weak solutions solve integral forms of the governing equations in which discontinuities are permitted. Such phenomena not only are expected to pervade the Sun’s atmosphere, but they are expected to harbor much of the free energy in the form of current sheets (e.g. Parker 1972 ; Parker 1994 ). It is precisely this free energy that is so important to the dynamic changes in radiation, particles, and magnetic fields ejected from the Sun. Rapid reconnection associated with current sheets are important for the operation of the large-scale solar dynamo. Recent work has re-assessed the disambiguation problem using ‘realistic’ MHD model calculations of the solar atmosphere, in a hare-and-hound exercise (Fleishman et al. 2017 ). Both successes and failures were found by the authors, conditions within strongly magnetized regions being more reliable than weaker regions. But such methods can never replace more observationally constrained methods, such as those proposed here. They remain dependent on the reality of models, and upon the essential assumptions of the ‘disambiguation’ methods used. The ambiguities
Paper: 2016A&A...589A..59M (acknowledgments)
We thank the anonymous referee for useful suggestions that helped to improve the paper. This work was supported under NASA Contract NNG08FD60C, and it made use of data from the NuSTAR mission, a project led by the California Institute of Technology, managed by the Jet Propulsion Laboratory, and funded by the National Aeronautics and Space Administration. We thank the NuSTAR Operations, Software, and Calibration teams for support with the execution and analysis of these observations. This research made use of the NuSTAR Data Analysis Software (NuSTARDAS) jointly developed by the ASI Science Data Center (ASDC, Italy) and the California Institute of Technology (USA). A.M., A.C., and S.P. acknowledge support from the ASI/INAF grant I/037/12/0-011/13. M.B. acknowledges support from NASA Headquarters under the NASA Earth and Space Science Fellowship Program, grant NNX14AQ07H. We acknowledge support from CONICYT-Chile grants Basal-CATA PFB-06/2007 (F.E.B., C.R.), FONDECYT 1141218 (F.E.B., C.R.), “EMBIGGEN” Anillo ACT1101 (F.E.B., C.R.), and the Ministry of Economy, Development, and Tourism’s Millennium Science Initiative through grant IC120009, awarded to The Millennium Institute of Astrophysics, MAS (F. E. B.). W. N. B. acknowledges support from NuSTAR subcontract 44A-1092750.
Paper: 2017MNRAS.467.1874C (acknowledgments)
Acknowledgments We thank the anonymous referee for his/her very helpful suggestions on the manuscript. This work is supported by the Natural Science Foundation of China (Nos 11422324, 11521303, 11390374), by Yunnan province (Nos 2012HB037, 2013HA005) and by the Chinese Academy of Sciences (No. KJZD-EW-M06-01).
Paper: 2017ApJ...850..159E (fulltext)
to better than 1/ ω for values of ω with a significant spectral component. If Δ l is by hypothesis less than the duration of the undispersed pulse, τ , which is of the order of 1 ms, then the spread in the lensing delays is only of the order of ( R s / R E ) 2 Δ l ( R s / R E ) 2 τ , where R s and R E are respectively the apparent source radius and the Einstein radius of the lens. (That the delay is only second-order in ( R s / R E ) follows from Fermat’s principle, namely that the propagation time is a local minimum relative to all other neighboring trajectories, e.g., Narayan Bartleman 1996 ). If FRBs are at cosmological distances, then, as the apparent source size R S is limited to the FRB pulse width (∼10 −3 c s), and R E 2 is of the order of , it follows that the spread in delays, which is of the order of , is indeed much less than 1 ns. Similarly, the difference in the dispersion time t d ∼ 1 along the two light paths, if the intergalactic medium is smooth, of the order of δθt d , where δθ , the angular separation of the images, obeys δθ 2 / H ∼ 2 Δ l . If Δ l ≪ 1 ms, then δθ ≲ 10 −11 . Conceivably, the intervening medium is clumpy on a much smaller scale than c / H , so the difference in dispersions—in this case governed by the sharp density gradients of the clumps—is larger. This would not destroy the effect; the delay is nonetheless well-defined. It would be due to dispersion differences rather than the lens, but the existence of the multiple paths—and hence the existence of the lens—would be demonstrated. A related question is whether the delay is constant over the course of the FRB. While the apparent source size of an FRB is only about 1 milli-lightsecond, the bulk Lorentz factor Γ of the emitting region must be at least of the order of 10 3.5 (Lyubarsky 2014 ), so the emitting region may move relative to the observer with an apparent velocity of ≳10 3.5 c . Now, for a source at a cosmological distance c / H , the Einstein radius of a lens of mass m is [( c / H )(2 Gm / c 2 )] 1/2 ≃ [10 16 ( m / M ⊙ )] 1/2 cm. So the apparent time to cross the Einstein radius is ∼10 2 [10 3.5 /Γ] [ m / M ⊙ ] 1/2 s, and over the 1 ms duration the change in the source position could be at most 10 −5 [10 3.5 /Γ] [ m / M ⊙ ] −1/2 R E . The change in the delay Δ l due to the motion of the emitting region would then be less than 10 −10 [10 3.5 /Γ] −2 [[ m / M ⊙ ] −1 Δ l ≃ 10 −15 [Γ/10 3.5 ] 2 s, which, for imaginable values of Γ, is much less than the baseband period. The importance of condition ( 3 ) over the full frequency range of significant G ( ω ), together with the broadband requirement ( 7 ) on G , is emphasized. The effect suggested here is not apparent in any formalism that assumes a monochromatic wave because adding a monochromatic wave to a delayed version of itself merely shifts the phase, and changes the amplitude by a modest factor (e.g., Deguchi Watson 1986 , Stanek et al. 2016 ). This is insufficient to reveal to the observer
Paper: 2016ApJ...816...43S (acknowledgments)
We thank A. Heger, M. Limongi, and K. Nomoto for providing progenitor models, M. Tanaka for fruitful discussions, and S. Veith for proofreading. The numerical computations in this study were partly carried out on XT4 and XC30 at CfCA in NAOJ and SR16000 at YITP in Kyoto University. This study was supported in part by the Grant-in-Aid for Scientific Research (Nos. 25103511, 26870823, 23540323, 23340069, 24103006, 26707013, and 24244036), JSPS postdoctoral fellowships for research abroad, MEXT SPIRE, and JICFuS.
Paper: 2015MNRAS.453.3375H (acknowledgments)
SH acknowledges support from an STFC-funded studentship. CD acknowledges support from an STFC consolidated grant (ST/L000768/1), an STFC Advanced Fellowship, an EU Marie-Curie IRG grant under the FP7 and an ERC Starting (Consolidator) Grant (no. 307209). The authors would like to thank Roberta Paladini, Simon Casassus and Tim Pearson for helpful discussion and comments. The authors would also like to thank Yvette Perrott and the MRAO AMI group for providing the AMI SA observation of LDN 1622.
Paper: 2016A&A...585A..79F (acknowledgments)
The authors thank Michael Dopita and Stephanie Juneau for very useful discussions, and the anonymous referee for in-depth reading and helpful comments. P.M.W. received funding through BMBF Verbundforschung (project MUSE-AO, grant 05A14BAC). E.Z. acknowledges funding from the Swedish Research Council (project 2011-5349). This research made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.
Paper: 2018A&A...609A..10V (fulltext)
respect to the location of the analogous peak observed for S Mon. Sung Bessell (2010) examined the median ages and cumulative age distributions of PMS stars in the various NGC 2264 subregions, to derive some information on the star formation processes within the region. The picture they deduced from their analysis is overall consistent with the scenario we outlined here: a picture of sequential star formation, where objects that populate the Halo and Field regions were formed first, followed by stars in S Mon and Cone (H), then sources in Cone (C) and, finally, those in the Spokes subcluster. The separate analysis we conducted here for disked vs. non-disked (and accreting vs. non-accreting) objects as a function of age allowed us to: i) confirm the model-based indication of an age spread by the association with measurable quantities, such as the presence of disks or accretion; ii) obtain a more detailed overview of the dynamical evolution of the cluster; iii) explore the mechanisms and characteristic timescales of evolution of PMS objects across the region (see Sects. 5.1 and 5.3 ). 5.3. Impact of environmental conditions on disk evolution In their investigation of the star formation history of NGC 2264, Sung Bessell (2010) showed that, while the age distribution of the S Mon population exhibits a significantly different behavior from those of the Spokes or Cone (C) populations (in the sense that the probability that they are drawn from the same parent distribution is very low), the populations of S Mon and of Cone (H) exhibit very similar distributions in age. However, some differences between the two regions appear when we restrict our analysis to disk-bearing or accreting objects (see Table 2 ). Namely, while the median ages associated with Class III objects in S Mon and in Cone (H) are similar to each other, the median age of disk-bearing objects in S Mon is noticeably lower than that of disk-bearing objects projected onto Cone (H). The difference is more marked when only CTTS are considered: a K-S test applied to the age distributions of accreting objects in S Mon and in Cone (H) returns a probability of 0.03 that they are drawn from the same population. This difference in median age between the two populations might be understood if objects in S Mon were formed at a later time than objects in Cone (H). However, the fact that S Mon hosts a significant fraction of Class III objects at any given age, and the fact that the number of Class II objects located in S Mon decreases sharply after 2.5 Myr (lower right panel of Fig. 11 ), would rather suggest that the characteristic timescales associated with disk accretion and disk evolution are shorter in the northern half of NGC 2264 than elsewhere within the region. This may result from non-uniform environmental conditions across the cluster. The S Mon region shown in Fig. 10 is distinguished by the presence of the massive binary S Mon (the primary component is an O7 V star and the secondary
Paper: 2018MNRAS.476.4520K (acknowledgments)
Acknowledgements This research has made use of NASA's Astrophysics Data System Bibliographic Services. We thank the European Southern Observatory staff at Paranal for their support during the observations. We acknowledge support from a Science and Technology Facilities Council Rutherford Fellowship (ST/J004030/1), Rutherford Grant (ST/K003445/1) and European Research Council Starting Grant (Grant Agreement No. 639889).
Paper: 2018ApJ...866...82Z (fulltext)
is as follows. The observations and data are described in Section 2 , the methods of analysis are described in Section 3 , and the results are discussed in Section 4 . 2. Observations The X-Ray Pulsar Navigation -I ( XPNAV -1) satellite is the first mission operated by the China Academy of Space Technology to demonstrate navigation using X-ray pulsars. This small (270 kg) satellite was launched on 2016 November 10, by the Long March 11 rocket at the Jiuquan satellite launch centre to the 500 km LEO orbit. It operates in the three-axis stabilization mode with the ability to quickly point to any inertial position with an accuracy within 2 arcmin according to demand, and to provide up to 90 minutes sustained observation on any target (see Zhang et al. 2017 ; Huang et al. 2018a ). The X-ray instrument used for this Crab pulsar glitch observation is the time-resolved soft X-ray spectrometer (TSXS). This instrument uses a grazing incidence focusing lens composed of four nested mirror shells with a collecting area of 30 cm 2 to focus X-ray photons within a 15 arcmin field-of-view onto a silicon drift detector. The effective detecting area of the instrument is 2.4 cm 2 at 1.5 keV. A GPS-calibrated Rb clock is included to provide accurate timing and a quasi-parallel optical star is used to assist the inertial pointing. The TSXS has the ability to provide 1.5 μ s time resolution. The observations used in this work were obtained from the period between UTC 2017 October 10 and 2018 April 28. A total of 627 observations of duration more than 1500 s were selected. Of these observations, 71 were collected pre-glitch, and 556 post-glitch. 3. Data Processing 3.1. Data Analysis Software System for XPNAV-1 The X-ray data are processed by the Data Analysis Software System (DASS; Zhang et al. 2017 ), which is illustrated in Figure 1 . Figure 1. Data flow of the Data Analysis Software System (see Zhang et al. 2017 ). In the DASS, data from XPNAV -1 are first unpacked to extract the GPS data, the satellite attitude data, the satellite status flag data, and the X-ray photon data. Then the X-ray photons are selected as described by Huang et al. ( 2018a ). The top-level timing formula is based on Edwards et al. ( 2006 , Equation (7)). The timescale transformation from the local time to the barycentric coordinate time and the time delays associated with the Earth’s and satellite’s orbital motion are considered, so that the Roemer delay, the Shapiro delay, the parallax delay, the Einstein delay, and the vacuum propagation delay are calculated to correct the photon arrival time at the satellite to that at the solar system barycenter (SSB) (see Edwards et al. 2006 ; Hobbs et al. 2006 ). The satellite position at each single photon’s arrival time is propagated from the on-board GPS data. With the photon arrival time at the SSB, we fold the pulse profiles into 256 bins per period. Pulse times of arrival (TOAs) are calculated by cross-correlation between the folded profile
Paper: 2021A&A...647L...3C (fulltext)
, which were obtained using a density functional theory level of theory (M05/6-31G(d)). An analysis of the observed intensities through a rotational diagram provides a rotational temperature of 9 ± 1 K. We performed a model fitting directly to the observed line profiles as described by Cernicharo et al. (2021a) , with the result that the best match between the computed synthetic spectrum and the observations was obtained for T r = 7 K and N(H 2 CCCHCCH) = (1.2 ± 0.2) × 10 13 cm −2 . Figure 1 shows the synthetic spectrum. Only the transition 9 19 − 8 1, 8 required a correction intensity by a factor of 0.8, while for all the other lines the model matches the observations perfectly. Using the H 2 column density derived by Cernicharo et al. (1987) , the abundance of H 2 CCCHCCH relative to H 2 towards TMC-1 is 1.2 × 10 −9 . This abundance is similar to that of vinyl acetylene ( Cernicharo et al. 2021a ), about ∼3 below that of propylene (CH 3 CHCH 2 ; Marcelino et al. 2007 ), and a factor of ten below that of methyl acetylene (CH 3 CCH; Cabezas et al. 2021 ). Hence, allenyl acetylene is one of the most abundant hydrocarbons in TMC-1, and probably, together with CH 3 C 4 H (see Sect. 3.2 ), the most abundant compound containing five carbon atoms. It is interesting to compare the abundance of allenyl acetylene with that of cyano allene (H 2 CCCHCN). This species has been recently analysed by Marcelino et al. (2021) , resulting in a rotational temperature of 5.5 ± 0.3 K and a column density of (2.7 ± 0.2) × 10 12 cm −2 . Consequently, the abundance ratio of H 2 CCCHCCH over H 2 CCCHCN is ∼4.5, that is to say the acetylenic derivative of allene is slightly more abundant than the cyanide one. A similar value (∼1.8) was obtained for the abundance ratio between CH 2 CHCCH and CH 2 CHCN ( Cernicharo et al. 2021a ). The measured frequencies of the lines observed in TMC-1 can be used to improve the rotational and distortion constants of H 2 CCCHCCH. We used the fitting code FITWAT described in Cernicharo et al. (2018) . Table 1 provides the results obtained by fitting the laboratory data of McCarthy et al. (2020) alone, and those obtained from a fit to the merged laboratory plus the TMC-1 frequencies. A significant improvement in the uncertainty in the rotational and distortion constants was obtained. The fit to the laboratory data alone results in exactly the same constants as those obtained by McCarthy et al. (2020) . The merged fit is recommended to predict the frequency of the rotational transitions of this species above 50 GHz. Predictions could be accurate enough up to 150 GHz to allow for a search of this species in the 3 mm domain. Table B.1 provides the observed and calculated frequencies and their differences. Table 1. Rotational and distortion constants of H 2 CCCHCCH. Notes. (a) Laboratory frequencies from McCarthy et al. (2020) . 3.2. Methyl diacetylene, CH<sub>3</sub>C<sub>4</sub>H This C 5 H 4 isomer was found in TMC-1 by MacLeod et al.
Paper: 2018MNRAS.476.4932V (acknowledgments)
Acknowledgements MAV acknowledges support from a CONACYT scholarship. Both authors appreciate the support of UNAM-DGAPA, PAPIIT through the grant IN110316. This work has made extensive use of the NASA's Astrophysics Data System Abstract Service. We also thank the anonymous referee for the suggestions that helped improve our work.
Paper: 2018A&A...618A.115K (fulltext)
by l b = ( π b + M b ) modulus 360deg. For CARMENES and the HARPS data sets, the total RV jitter is comparable at ≲ 2 m s −1 , while it is 5.62 m s −1 for the HIRES data. With 1.77 m s −1 , the root mean square of the residuals of the model fits is lowest for the HARPS post-upgrade data, followed by the HARPS pre-upgrade (2.15 m s −1 ) and the CARMENES (2.66 m s −1 ) data. Again, HIRES shows the highest value, with 6.02 m s −1 . Compared to the formal uncertainties of the measurements (see Sect. 3 ), this means a factor of around three for HIRES and the HARPS pre-upgrade, and a factor of two for the HARPS post-upgrade and the CARMENES data. The GLS periodogram of the residuals does not show any significant signals (lower panel Fig. 1 ). However, there is some power at periods around 45 days and its overtones. This can be attributed to the rotation period P rot = 46.04 d of the host star. Moreover, the strongest peak at around P ≈ 190 d nearly reaches the 1% FAP level. The source of this signal is currently unknown, although the activity indicators hint at stellar activity. We also analyzed the residuals for possible long-term structures, but found the results inconclusive. While the entire data set shows only a negligible drift term of 0.03 ms −1 yr −1 , it is more significant for the residuals of the most recent RV measurements. A linear fit to the combined residuals from the HARPS post-upgrade epoch together with the CARMENES data gives a slope of around 0.5 ms −1 yr −1 . This could be an indication for an additional long-term signal, which in the HIRES data might be obscured by the comparably high scatter. In order to investigate the robustness of our fit results against possible contributions from correlated noise and additional RV or activity signals, we studied five additional models, using the concepts of moving averages (MA) and Gaussian process (GP) regression. The results from this analysis and their discussion can be found in Appendix. B . They agree with the orbital parameters reported here. Fig. 2 Unfolded ( left ) and phase-folded ( right ) RV measurements of the individual instruments for HD 180617, together with the best fit overplotted. 4.3 Activity analysis Periodic variability in RV measurements can also be introduced by stellar activity. Chromospheric emission, chromatic dependence of the RVs, and changes in line profiles are indicative of stellar activity. In Fig. 4 we provide GLS periodograms for some of these quantities, derived from the available CARMENES spectra. The H α index, the chromatic index (CRX), and the differential line width (dLW), shown in the three uppermost panels, are derived from the time series of activity indicators directly provided by SERVAL ( Zechmeister et al. 2018 ). While the chromatic index reflects wavelength dependencies of the measured RVs in the different échelle orders, which can result from the temperature surface structure onthe star (spots or faculae), the differential line width