adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016A&A...592A.116S (fulltext)
which fall within of the HRD position of both stars and have equal composition. Fig. 5 Chi-squared distribution of central hydrogen mass fraction for the same models as in Fig. 4 . The models for the primary are indicated by the dark blue points, while the models for the secondary are indicated by the light blue points. So far, we have only taken into account the mean of the observed -mode period spacing, neglecting the effect of rotation and the information that is held in the spacing morphology. In the next step, we therefore calculate the adiabatic frequencies of our models with GYRE and compare their seismic properties to the observations. 3.2. Period spacing with GYRE We calculated the zonal dipole and quadrupole modes with GYRE for the coeval models with the lowest . As we clearly see the effect of rotation in the observed frequency spectrum (see Fig. 1 ), we apply Ledoux splitting to the zonal modes to obtain the theoretical prograde and retrograde modes and the rotational frequencies near the core for both components. We derive and and a negligible difference between the models with exponential and those with step overshooting. For these rotation rates and the co-rotating dipole-mode frequencies we find and . The comparison between the calculated modes of Models 2 and 3 and the observed period spacings is illustrated in Fig. 6 , while Fig. 7 shows the comparison of the -modes. Our main focus lies in comparing the mean period spacing values and the structure of the period spacing pattern, rather than individual frequencies. We find a satisfactory fit for both models and cannot distinguish between exponential or step overshooting. Furthermore, we are able to assign the series (yellow stars in Fig. 1 ) to the primary, as there is a clear overlap with the retrograde sectoral modes of both models, while there is a gap for the models of the secondary. From Eq. ( 3 ), we expect that the ratio of the asymptotic period spacing of the quadrupole modes to the asymptotic period spacing of the dipole modes is . We use the derived to shift the observed quadrupole sectoral modes to their zonal counterparts, and find s and . For the secondary and we find s and . These results support that the series originates in the primary. Fig. 6 Comparison of theoretical (empty symbols) to observed (filled symbols) period spacing for the primary ( top panels ) and the secondary ( bottom panels ). Ledoux splitting has been applied to the theoretical zonal modes to fit the retrograde and prograde modes. The uncertainties of the observed period spacings are smaller than the symbols. The radial orders are indicated near selected modes. Dipole modes of radial order are shown for the primary and for the secondary, while the radial orders of the quadrupole modes are and , respectively. Fig. 7 Comparison of the theoretical zonal -modes (empty symbols) to the observed modes (filled symbols) as a function of degree . Modes of the primary are shown in the top panels and
Paper: 2019MNRAS.482L..46V (fulltext)
conceivably due to dynamical mass ejecta. Colour coding (blue-to-yellow) is proportional to amplitude defined by butterfly output ρ of time-symmetric chirp-like template correlations to data. Fig. 2 shows a continuation of GW170817 with a long-duration descending chirp during GRB170817A. It can be fitted by an exponential track ( Supplementary Information ) with s, t s = 1843.1 s, Hz, and f 0 = 98 Hz. Crucially, s shows the descending chirp to start in the 1.7 s gap between GW170817 and GRB170817A, satisfying the aforementioned causality condition. A Gaussian equivalent level of confidence greater than 3.3σ obtains for significance to the central engine of GRB170817A based on causality over 1952 s of LIGO data. Improved estimates obtain upon including the statistical significance of the strength of the signal ( Supplementary Information ). The estimated initial frequency Hz at the time of coalescence inferred from ( 2 ) is below the orbital frequency at which the stars approach the Inner Most Stable Circular Orbit (ISCO) of the system as a whole, i.e. Hz at km according to the Kerr metric (Kerr 1963 ; Bardeen, Press Teukolsky 1972 ; Shapiro Teukolsky 1983 ). At this point, a binary system of two equal mass neutron stars would have a rotational energy and a dimensionless specific angular momentum . While this allows prompt collapse to an Kerr black hole (Kerr 1963 ) any gravitational-radiation from remaining debris orbiting about the ISCO would be above 2 kHz. Instead, the 1kHz descending chirp in Fig. 2 points to radiation of from a long-lived rapidly rotating hypermassive neutron star or magnetar with a dimensionless quadrupole moment of , where R is the radius of the star, induced by dynamical and secular instabilities (Owen et al. 1998 ; Kokkotas 2008 ; Corsi Mészáros 2009 ) that may include magnetic fields (Cutler 2002 ; Abbott et al. 2017d ). Magnetar spin down indicated by the descending chirp may include magnetic interactions with surrounding matter from dynamical mass ejections from the preceding merger, in addition to gravitational radiation losses alone. These ejecta are commonly found in aforementioned numerical simulations. The interactions may result from magnetic coupling (Gosh, Pethick Lamb 1977 ; Gosh Lamb 1978 , 1979 ) and/or tidal stresses (Hotokezaka et al. 2013 ) that may include magnetic outflows from open field lines (Lovelace, Romanova Bisnovatyi-Kogan 1995 ; Parfrey, Spitkovksy Beloborodov 2016 ) and gravitational-wave emission from quadrupole moments in orbiting debris. While the descending chirp identifies the central energy reservoir of GRB170817A to be a rotating hypermassive neutron star or magnetar, its connection to GRB170817A remains uncertain. Perhaps the relatively soft second gamma-ray pulse of GRB170817A (Pozanenko et al. 2018 ) derives from outflows from debris orbiting the star, while the short-hard pulse derives from an initial outflow from the star at birth. More likely, the complex spectral evolution of
Paper: 2016A&A...593A..69C (acknowledgments)
We are sincerely grateful to an anonymous referee for instructive advice and productive suggestions that greatly helped us to improve the manuscript. This work is funded by the NSFC of China (Grant No. 11333006, 11521303, and 11403094) and by the foundation of Chinese Academy of Sciences (Grant No. XDB09010202 and Light of West China Program). We gratefully acknowledge the computing time granted by the Yunnan Observatories, and provided on the facilities at the Yunnan Observatories Supercomputing Platform. We are also very grateful to J.-J. Guo, G.-F. Lin, Q.-S. Zhang, Y.-H. Chen, and J. Su for their kind discussions and suggestions.
Paper: 2016ApJ...831...57E (acknowledgments)
This work has been supported by a grant from the Brazilian agency FAPESP (#2013/10559-5). Raissa Estrela acknowledges a CAPES fellowship.
Paper: 2018ApJ...863....6S (acknowledgments)
The authors express their thanks to Christina Ciardullo for her assistance with the graphics. M.S. acknowledges support from DFG project RA 714/9-1. M.G. acknowledges support from DFG project GO 2610/1–1. F.S. acknowledges support from DFG project SCHR 1125/3-1. Software: GARLIC (Schreier et al. 2014 , 2018a , 2018b ), HITRAN2012 (Rothman et al. 2013 ).
Paper: 2018MNRAS.481.3761G (acknowledgments)
ACKNOWLEDGEMENTS We would like to thank Lucy Heil for useful discussions and for providing comparison data to check our power-colour estimates, and Rudy Wijnands and Jeroen Homan for useful discussions. We also thank the anonymous referee for constructive comments. DWG acknowledges funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 617199, and support from the Netherlands Institute for Radio Astronomy (ASTRON) and the Netherlands Foundation for Scientific Research (NWO). This research has made use of data obtained through the High Energy Astrophysics Science Archive Research Center Online Service, provided by the NASA/Goddard Space Flight Center. chromos makes use of astropy v1.0.3 (Astropy Collaboration et al. 2013 ), ftools (Blackburn 1995 ), numpy, pyx , and scipy .
Paper: 2016A&A...596A..95S (acknowledgments)
This work was partially supported by Consejo de Investigaciones Científicas y Técnicas (CONICET) and Secretaría de Ciencia y Técnica de la Universidad Nacional de Córdoba (SecyT). We want to thank the anonymous referee, whose very useful remarks helped us to improve this paper. This research has 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: 2019ApJ...874..136S (acknowledgments)
This paper makes use of the following ALMA data: ADS/JAO.ALMA#2015.1.00773.S. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. Y.-L. W. is grateful to the support from the Heising-Simons Foundation. J.T. would like to acknowledge support from the Homer L. Dodge Endowed Chair. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under grant No. 2012115762. This work was supported by NSF AAG grant 1311910. The results reported herein benefitted from collaborations and/or information exchange within NASA’s Nexus for Exoplanet System Science (NExSS) research coordination network sponsored by NASA’s Science Mission Directorate. The computing for this project was performed at the OU Supercomputing Center for Education and Research (OSCER) at the University of Oklahoma (OU). Software: pdspy (Sheehan 2018 ), CASA (McMullin et al. 2007 ), RADMC-3D (Dullemond 2012 ), emcee (Foreman-Mackey et al. 2013 ), matplotlib (Hunter 2007 ), corner (Foreman-Mackey 2016 ), GALARIO (Tazzari et al. 2018 ).
Paper: 2019MNRAS.485.3696C (acknowledgments)
ACKNOWLEDGEMENTS We thank the referee for their useful comments that have gone a long way to improving this manuscript. DK thanks Maria Petropoulou for informative discussions regarding pair processes. RMTC also thanks Javier Garcia for useful discussions. This research has made use of ISIS functions provided by ECAP/Remeis observatory and MIT ( http://www.sternwarte.uni-erlangen.de/ISIS/ ), and data obtained from the High Energy Astrophysics Science Archive Research Center (HEASARC), provided by NASA's Goddard Space Flight Center. This paper has made use of up-to-date SMARTS optical/near-infrared light curves that are available at www.astro.yale.edu/smarts/xrb/home.php . The Yale SMARTS XRB team is supported by NSF grants 0407063 and 070707 to Charles Bailyn. RMTC is thankful for support from NOVA (Dutch Research School for Astronomy), and acknowledges funding from NASA (National Aeronautics and Space Administration) grant no. 80NSSC177K0515. CC acknowledges support from the Netherlands Organisation for Scientific Research (NWO), grant no. 614.001.209. SM, DK, and ML acknowledge support from NWO VICI grant no. 639.043.513. VG is supported through the Margarete von Wrangell fellowship by the ESF and the Ministry of Science, Research and the Arts Baden-Württemberg.
Paper: 2018MNRAS.481...36A (fulltext)
‘s’ in space–time, because for isotropic geodesic motion we have d s = 0 but dΣ ≠ 0. This method has been successfully used to study various non-linear processes occurring in magnetic dipole fields of pulsars and magnetars (Abishev et al. 2016 ), as well as in an electric dipole field (Vasili’ev et al. 2017 ). Calculations have shown that in this case the rays of electromagnetic waves are bent, and the electromagnetic wave itself splits at η 1 ≠ η 2 into two normal modes with mutually perpendicular polarization. These modes propagate along different rays at different speeds. At the present time, another polarization effect of non-linear electrodynamics of vacuum is observed (Taverna et al. 2014 ; Caniulef et al. 2016 ; Mignani et al. 2017 ): polarized thermal emission from X-ray-dim isolated neutron stars (the case of RX J1856.5−3754). Recent papers (Pétri 2013 , 2015 ) assume that neutron stars can also have a quadrupole magnetic field, the intensity of which can reach the intensity of dipole fields. To date, there has not been any study of the non-linear electrodynamic effect of the magnetic quadrupole field on the propagation of pulses of electromagnetic radiation. Therefore, the purpose of this article is to calculate the non-linear effect of the magnetic dipole and quadrupole fields on the propagation of electromagnetic waves. 2 FORMULATION OF THE PROBLEM We place the origin of the Cartesian coordinate system at the point where the pulsar or magnetar is located. Then, the vector of magnetic induction will have the form where B 1 is the vector of the dipole magnetic induction and B 2 is the vector of the quadrupole magnetic induction. In the Maxwellian approximation, we have where m is the magnetic dipole moment of the pulsar or magnetar. The components of the quadrupole magnetic induction vector B 2 in a spherical coordinate system r , θ, φ, as shown in Pétri ( 2015 ), will have the form where R s is the neutron star radius, B is a constant having a dimension of magnetic induction, and χ 1 ∈ [0, ] and χ 2 ∈ [0, 2] are two angles specifying the particular geometry of the quadrupole magnetic field. However, for further calculations it is more convenient for us to use a rectangular Cartesian coordinate system. Redesignating the constants B , χ 1 , and χ 2 in accordance with relations from the expression (8) we obtain where the notations were introduced f 1 = cos ξ, f 2 = sin ξcos χ 2 , f 3 = sin ξsin χ 2 , at that The B 0 constant can be expressed in terms of the magnetic induction of a quadrupole B N at a point θ = /2, φ = /4 on the surface of a neutron star: Suppose that an electromagnetic pulse is emitted from a certain point r = r s = { x s , y s , z s } at time t = t s . We assume that at the point r = r d = { x d , y d , z d } there is an electromagnetic radiation detector. We orient the axes of the Cartesian coordinate system so that the source and the electromagnetic radiation detector lie in the XOZ plane, and the Z - axis is
Paper: 2019ApJ...884..167T (fulltext)
C of CH 2 and the C atoms can scramble, fractionation will occur. The dominant contribution of reaction ( 8 ) extends from somewhat greater than 10 3 yr to almost 10 5 yr, which is a much longer period than the time range when reaction ( 6 ) is dominant. Moreover, its range of dominance coincides more closely with the age range determined in multi-molecule fits to abundances in dark clouds (Wakelam et al. 2006 ). This reaction should, therefore, contribute to the differences in abundances between 13 CCH and C 13 CH, as mentioned before. Now consider the case of the isotopomer-exchange reaction:which is exothermic, as written from left to right so that the net effect is an increase in the abundance of the 12 C 13 CH isotopomer at the expense of 13 C 12 CH isotopomer. Furuya et al. ( 2011 ) used 1 × 10 −10 cm 3 s −1 as the rate coefficient of the forward reaction of the isotopomer-exchange reaction in their calculation. They also applied 8.1 K to the zero-point energy difference of 13 CCH and C 13 CH. The efficiency of this process depends upon a number of factors, including whether the exothermicity of 8.1 K is sufficient to cause the difference in observed abundance, whether the abundance of atomic hydrogen is large enough, and whether or not a barrier to reaction exists. The differences in abundances between 13 CCH and C 13 CH can be seen even at the early stages (Figure 3 in Furuya et al. 2011 ). This isotopomer-exchange reaction appears to be able to explain, at least partially, the 13 C isotopic fractionation in both L1521B and L134N. In summary, we found that C 13 CH is more abundant than 13 CCH in L1521B and L134N from our observations. This tendency agrees with the previous observations in TMC-1 and L1527 (Sakai et al. 2010 ). The higher abundance of C 13 CH compared with 13 CCH may indeed be common for dark clouds. Both reaction ( 8 ) and the isotopomer-exchange reaction likely contribute to the 13 C isotopic fractionation of CCH both in L1521B and L134N. 4.2. The Dilution of the <sup>13</sup>C Species in Dark Clouds 4.2.1. Comparisons of the <sup>12</sup>C/<sup>13</sup>C Ratios between CCH and HC<sub>3</sub>N among Dark Clouds It is interesting to compare the 12 C/ 13 C ratios of CCH and HC 3 N among the three dark clouds: L1521B, L134N, and TMC-1. Table 3 summarizes the 12 C/ 13 C ratios of CCH and HC 3 N in the three dark clouds and Figure 5 shows the comparisons. In the local ISM, the elemental 12 C/ 13 C ratio has been determined to be 60–70 (e.g., Milam et al. 2005 ), which we indicate as the yellow range in Figure 5 . Figure 5. Comparisons of the 12 C/ 13 C ratios of CCH and HC 3 N in the three starless cores; L1521B, L134N, and TMC-1. The errors indicate the standard deviation. The yellow range ( 12 C/ 13 C = 60–70) shows the values in the local interstellar medium. The values are the same as Table 3 . Table 3 The 12 C/ 13 C Ratios of CCH and HC 3 N in Dark Clouds Notes. a Taken from Sakai et al. ( 2010 ). b Taken from Taniguchi
Paper: 2016A&A...586A..50G (fulltext)
The noise is slightly lower (about 15%) than expected from the online APEX calculator because our noise measurements are made in moderately smoothed maps. 2.3. Baselining The data showed significant baseline structure, leading to large-scale correlated components in the resulting spectra. The baselines were removed over a velocity range km s -1 by the following procedure: 1. identify bright PPV regions in the line using the technique described in Sect. 3 ; 2. mask the regions identified as -bright for each other spectral line data cube; 3. fit a polynomial to the un-masked data; 4. subtract the fitted polynomial. We used a 7th-order polynomial for this process because lower order baseline removal left a significant and patterned residual. A more detailed examination of the baseline removal process is described in Appendix A . 3. Signal extraction and masking We use the method described partially in Ao et al. (2013) and more thoroughly in Dame (2011) to mask the data cubes at locations of significant signal in the brightest line. A noise map was created by computing the sample standard deviation over a 200 km s -1 range in which no signal was present. We use the line, which is the brightest of the lines, to create the mask by the following procedure: 1. Smooth the data with a Gaussian of width two pixels in each direction (spatial, , and spectral, km s -1 ). 2. Create an inclusive mask of all pixels with brightness in the smoothed map. 3. Grow the mask from the previous step by one pixel in each direction (this is known in image processing as binary dilation). The mask was then applied to the and cubes created with the same PPV gridding. There is some overlap between the line and the line in PPV space, so we shifted the mask to the velocity of the line in the cube and excluded those pixels expected to contain emission. However, inspection of the cube revealed that significant chunks of the signal were excised by this masking, so all further analysis excludes the line. Integrated intensity maps are shown in Fig. 2 a for the map masked with the above method and in Fig. 2 b for the map using the mask created from the data. Fig. 2 Integrated intensity (moment 0) maps of the a) and b) lines. The cubes were masked prior to integration using the method described in Sect. 3 . Selected region names are labeled. The thin black contours are at a column from the Herschel SED fit maps. 3.1. Ratio maps We have created ratio maps as a first step toward building temperature maps. In general, a higher indicates a higher temperature, and therefore the ratio maps are a good proxy for relative temperature. We display four different varieties of ratio map in Figs. 3 and E.1 . Figure 3 shows maps produced by creating ratio cubes, in which each voxel has the value , then averaging across velocity with constant weight for each voxel in Fig. 3 a and with the weight set by the brightness value in Fig. 3 b. In both cases, the mask described in Sect. 3 was applied to the
Paper: 2017ApJ...840..102K (fulltext)
( MK; Maggio et al. 2000 ). The abundances during the flares F1 and F2 are found to enhance ∼9 and ∼2 times more than those of the minimum values observed. During other superflares, abundances were found to increase between two to three times more than that of the quiescent level (Favata Schmitt 1999 ; Favata et al. 2000 ; Maggio et al. 2000 ). However, in the case of the superflare observed with Swift in EV Lac, the abundances were found to remain constant throughout the flare. From Figure 3 , it is evident that the abundance peaks after the temperature and luminosity peaks, which is consistent with a current idea in the literature (see Reale 2007 ). This could be due to the heating and evaporation of the chromospheric gas, which increases the metal abundances in the flaring loop. For both flares, the temperature peaked before the EM did. A similar delay was also observed in many other solar and stellar flares (e.g., Sylwester et al. 1993 ; Favata Schmitt 1999 ; Favata et al. 2000 ; Pandey Singh 2008 ). The temperature increases due to beam driven plasma heating and later subsequent evaporation of the plasma into upper parts of the coronal loop that increases its density, and therefore EM (). Later coronal plasma cools down by thermal conduction and then via radiative losses (e.g., Cargill Klimchuk 2004 ). 4.2. Coronal Loop Properties The derived loop lengths for the flares F1 and F2 are larger than previously observed flares by Crespo-Chacón et al. ( 2007 ) on CC Eri. The loop lengths are also in between the loop lengths derived for other G–K dwarfs, dMe stars, and RS CVn type binaries (e.g., Favata Micela 2003 ; Pandey Singh 2008 , 2012 ). Instead of ∼3 times larger peak luminosity in flare F1 than that of the flare F2, the derived loop length for flare F2 is two times larger than that of flare F1, which might be interpreted as a result of an ∼1.4 times more sustained heating rate in the decay phase of flare F1 than that of flare F2. The heating rate during flare F1 is also found to be ∼49% of the bolometric luminosity of the CC Eri system, whereas during flare F2 the heating rate is only ∼35% of the combined bolometric luminosity. The derived heating rate is also found to be more than the maximum X-ray luminosity for both flares. This result is compatible with X-ray radiation being one of the major energy loss terms during the flares. Present analysis allows us to make some relevant estimation of the magnetic field strength that would be required to accumulate the emitted energy and to keep the plasma confined in a stable magnetic loop configuration. Under the assumptions that the energy release is indeed of magnetic origin, the total non-potential magnetic field involved in a flare energy release within an active region of the star can be obtained from the relationAssuming that the loop geometry does not change during the flare, is estimated to be >12 and >2 kG for the flares F1 and F2, respectively. Bopp Evans ( 1973 ) also estimated a