adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020ApJ...888L...9N (fulltext)
6 are heavily driven by the differential abundances of the most volatile species, such as C, CH, O, and N (i.e., T Cond 200 K). In fact, the number of volatiles is much smaller than the number of refractory elements, as is visible in Figure 1 . In addition, the chemical abundances of volatile elements are often more uncertain than those of refractories. In the case of HIP 34407/HIP 34426, the chemical anomaly is extremely large compared to all the other pairs. The elements with an intermediate condensation temperature, such as Na, S, and Zn (i.e., 500 T Cond 1000 K) are well aligned by the Δ[X/H]– T Cond relation plotted in Figure 1 . This neat linear relation between elemental abundances and condensation temperature for this system may suggest that the anomaly was caused by a planetary engulfment event. Similar results were independently obtained by Ramirez et al. ( 2019 ). Interestingly, the HIP 34407/HIP 34426 system was determined to be the most chemically inhomogeneous system found to date among other pairs in binary systems or clusters, that show similar trends between abundances and condensation temperature (Tucci Maia et al. 2014 , 2019 ; Biazzo et al. 2015 ; Spina et al. 2015 , 2018 ; Teske et al. 2015 , 2016 ; Saffe et al. 2016 , 2017 ; Oh et al. 2018 ). Its median differential abundance in the refractory elements is 0.19 dex. In addition, we note that the results from the HIP 34407/HIP 34426 system involve similar but not identical volatile elemental abundances. Out of the four most volatile species measured (i.e., ), only one is consistent with zero, leading to the hypothesis that the slope is due to the engulfment of a gas giant. This is because such planets are capable of causing abundance changes in both volatiles (due to their gaseous outer layers) and refractories (due to their rocky cores and metallic inner layers). This hypothesis has been also proposed to explain a similar anomaly observed in the chemical composition of the 16 Cyg binary system (Tucci Maia et al. 2014 , 2019 ). 4. Conclusions The occurrence of chemically anomalous stars at the 0.01 dex precision level can be deduced from line-by-line differential analysis of twin stars in binary systems. Out of the 14 systems measured using UVES and HDS, 6 were found to exhibit chemical inhomogeneities (i.e., σ χ ), rendering chemical tagging on these systems inaccurate. However, only two pairs were chemically inhomogeneous at the precision level typical of large spectroscopic surveys (i.e., 0.05 dex). Of special note is that the HIP 34407/HIP 34426 system was determined to be the most chemically inhomogeneous system found to date. For this pair, the trend between differential abundances and condensation temperature is neat, and it may suggest that rocky material has polluted the atmosphere of HIP 34407. We speculated that the planet engulfed by the star was a giant gaseous planet, as HIP 34426 is also anomalously rich in the volatiles. The planet population around the
Paper: 2019MNRAS.488.5651E (acknowledgments)
ACKNOWLEDGEMENTS We thank the referee for constructive and valuable comments, which increased the scope of our work significantly and improve the overall quality even in some details of our paper. We thank Artem Tuntsov, Oleg Yu. Tsupko, and Shude Mao for interesting discussions. XE is supported by National Nature Science Foundation of China Grant No. 11473032 and No. 11873006. AR wishes to acknowledge the contribution of the Brandon University Research Committee.
Paper: 2016A&A...588A..69D (acknowledgments)
We thank the referee for the interesting comments. We are grateful to Emmanuel Bertin for many enlightening discussions. F.D. acknowledges long-term support from CNES. I.M. acknowledges financial support from the Spanish Ministry of Economy and Competitiveness through the grant AYA2013-42227P.
Paper: 2017ApJ...847...93C (acknowledgments)
This work was carried out through the National Solar Observatory Research Experiences for Undergraduate (REU) site program, which is co-funded by the Department of Defense in partnership with the NSF REU Program. The National Solar Observatory is operated by the Association of Universities for Research in Astronomy, Inc. (AURA) under cooperative agreement with the National Science Foundation. S.C. is grateful to Dr. Peter Foukal for reading the paper and providing useful comments, and to Dr. Odele Coddington for interesting discussions about the NRL reconstructions.
Paper: 2015MNRAS.448..895S (acknowledgments)
JS thanks Rob Simcoe, Kate Rubin, Laura Sales, Vicente Rodriguez-Gomez, and Dylan Nelson for their helpful comments. VS acknowledges support by the European Research Council under ERC-StG EXAGAL-308037. LH acknowledges support from NASA grant NNX12AC67G and NSF grant AST-1312095.
Paper: 2016A&A...590A..48K (fulltext)
in the inner jet of PKS 1502+106 – is about half that used by Pushkarev et al. (2012) . 4. Discussion 4.1. Localizing the <inline-formula specific-use="simple-math"><italic>γ</italic></inline-formula>-ray emission Our ultimate goal of pinpointing the -ray emission region is reached by combining the findings of the present study with those of Fuhrmann et al. (2014) , who deduce a relative distance between the -ray active region and the 86.24 GHz unit-opacity surface of about 2.1 pc (cf. Ramakrishnan et al. 2015 ). Here, based on the opacity-driven time lags across the eleven observing frequencies, the distance of the 86.24 GHz core from the jet base is pc. From that combination it follows that the -ray emission region is best constrained to a distance of pc away from the jet base. In a similar study, Max-Moerbeck et al. (2014) obtain a time lag of d between the leading rays and the lagging 15 GHz radio emission. Following their reasoning, this time lag translates into a relative distance of pc between the 15 GHz unit-opacity surface and the -ray site. Combining our at 15 GHz (Table 4 ) with the aforementioned value, we obtain a separation of pc between the jet base and the -ray active region, comparable with our previous result based on the 86.24 GHz time lag. We reiterate that in the present work we use the VLBI kinematical parameters of the knot connected to the 2008/10 flare of PKS 1502+106 (C3, see Sect. 3.4 ). Finally, our results are in agreement with the upper limit of pc reported by Karamanavis et al. (2016) , based on mm-VLBI imaging. At pc from the jet base, the high-energy emission originates well beyond the bulk of the BLR material of PKS 1502+106, placed at pc ( Abdo et al. 2010 ). A -ray emission region placed so far away from the BLR almost negates the notion that BLR photons alone can be used as the target photon field for inverse-Compton up-scattering to rays, and as a result other or additional seed photon fields (e.g., torus, synchrotron self-Compton, SSC) need to be involved in the process. 4.2. A shock origin for the 2008/10 flare Overall, the slopes extracted from the multi-wavelength light curves agree well with the expectations of the shock-in-jet model ( Marscher Gear 1985 ), indicating a shock origin for the 2008/2010 flare of PKS 1502+106. In this section, we discuss the observed light curve parameters (flare amplitudes and cross-band delays) in conjunction with the results of analytical shock-in-jet model simulations ( Fromm et al. 2015 ). The dependence of flare amplitude on frequency is shown in Fig. 4 and the cross-frequency delays in Fig. 5 . Flare amplitudes rise with frequency until they culminate at a frequency of about 43 GHz, after which the amplitude of the flare drops. The rise and decay wings follow a trend that is described well by a broken power law, in very good agreement with the shock model expectations. The slopes are for the rising part of the flare amplitude and for the decaying part. The
Paper: 2020MNRAS.493.1130R (fulltext)
of 3.6 . The adopted width variation at each step corresponds to considering one more point at each side of the line profile, i.e. the minimal possible difference when the profile width is varied symmetrically around the centre. For each considered profile width, we performed a linear regression over the 50 synthetic spectra to obtain the optimal value of that gives the best results to determine H eff through equation ( 3 ). Note that it is not possible to obtain separately the values λ 0 and g 0 , but only their product. The results are shown in Fig. 2 . In the upper panel, we show the mean absolute percental error (MAPE) obtained by comparing the original values of H eff and the ones derived by the regressions, 1 while the lower panel shows the respective fitted values of , both as a function of the integration limits (width profiles). Figure 2. Mean absolute per centual error (upper panel) and normalization values (lower panel) as a function of the profiles width. In the right Y -axis of the lower panel, the values are normalized to the case when the profile width is 39.6 . The results were obtained analysing a sample of 50 synthetic spectra. The first remark of this test is that for all considered profile widths, it is always possible to fit a value of that allows us to infer very accurately H eff : the MAPE remains inferior to 1.0 per cent in the big majority of the cases. This result is quite unexpected since even underestimating the width of the profiles up to the extreme case in which the profiles consist of only five central points (from −3.6 to 3.6 ), one can obtain very precise estimations of H eff . Analogously, the same behaviour is obtained when the profiles are highly overestimated, with very small MAPE values. The fact that it is possible to consider deliberately only a part of the profiles to infer H eff can be useful in some practical applications, as, for example, in binary systems or in stars surrounded by circumstellar envelopes with strong stellar winds that can generate shocks visible as bumps. The bump produced by the shock is in turn blended with the intensity profile of the star (e.g. Sabin, Wade Lèbre 2015 ), so to consider only a fraction of the intensity profile of the star could be of interest. Another important result of this test is that it shows that the value of is very sensitive to the integration range, see lower panel of Fig. 2 . The fitted values of start at 329 nm (profile width of 7.2 ) and they increase very quickly to reach a maximum of 918 nm (profile width of 21.6 ), to then decrease following a likely exponential-type curve, finishing at 286 nm for the broadest profile width of 97.2 . Additionally, to illustrate the relative changes in the values of , we take as reference a width of 39.6 (from −19.8 to 19.8 ), which seems a plausible selection by visual inspection of the profiles in Fig. 1 . In the right Y -axis of the lower panel in Fig. 2 are shown the percentage variations of : as example, if
Paper: 2018MNRAS.478..425B (fulltext)
Lind ( 2017 ) predict for Al a correction for dwarf and giant stars of ∼−0.1 dex at solar metallicity for the line at 669.6 nm. For Mg, we do not expect NLTE effects to have a strong influence on the abundances. Zhang et al. ( 2017 ) calculate corrections of the order of ±0.01 dex for stellar parameters similar to our NGC 6633 sample. For the same stars, Zhang et al. ( 2016 ) predict corrections of the order of −0.03 (RGB) and 0.00 dex (MS) for Si. The latter, however, has , i.e. the offset is relatively large and cannot be explained by NLTE effects. Since also in the case of M67, we found that the offset in Si between the upper MS and RGB is larger than predicted by the models, this could mean that indeed for Si there is a bias in the analysis of dwarf and giant stars. 5.4 APOGEE DR14 The recent fourteenth data release of the Apache Point Observatory Galactic Evolution Experiment (hereafter APOGEE DR14; see Abolfathi et al. 2017 ; Majewski et al. 2017 ) contains very important results concerning the abundances of M67 stars. In APOGEE DR14, stars in every evolutionary stage of M67 have been observed and analysed, from the MS to the RC. We decided to be as conservative as possible in the choice of the stars to be taken into consideration and we selected only those with STARFLAG, ASPCAPFLAG, and the ELEMFLAG of the element under study equal to zero. By doing so, we aim at excluding as many possible biases due to unreliable results as possible. APOGEE DR14 contains the abundances determined by the APOGEE Stellar Parameters and Chemical Abundances Pipeline (ASPCAP) (see Holtzman et al. 2015 ; García Pérez et al. 2016 ) as well as calibrated abundances. These are calculated under the assumption that abundances of open cluster members should be homogeneous and that therefore any trend with temperature must be corrected for. Since for our purposes it is important to take into consideration any trend of the chemical abundances as a function of temperature, we decided to use the uncalibrated abundances. We present the results in the form [X/H]. For the elements that were calculated as [X/M], we add the uncalibrated [M/H] of the star. The error bars only represent the errors on the fit of the uncalibrated abundances presented in the APOGEE DR14 catalogue (for the uncalibrated [M/H] no errors are given). These are very small and are not to be considered realistic errors. Fig. 5 shows the CMD of the sample (not corrected for reddening) selected after a membership analysis based on radial velocity, PM, photometry and metallicity, and after all stars with the flags listed above not equal to zero were excluded. The stars are colour coded based on their iron abundance. It is already clear from this plot that [Fe/H] on the TO is lower than on the RGB and on the RC. Since no calibrated log g is available for dwarf stars in APOGEE DR14, we plotted in Fig. 6 the abundances of several species as a function of the effective temperature together with the models
Paper: 2015ApJ...811...32P (acknowledgments)
This research was supported by NSF Grant AST-0708079, the Louisiana Space Consortium and NASA through Grant NNX10AI40H, as well as the Kathryn W. Davis Postdoctoral Scholar program, which is supported in part by the New York State Education Department and by the National Science Foundation under grant numbers DRL-1119444 and DUE-1340006. A.U.L. acknowledges support from NSF Grant AST-0803158. K.L.P. and J.P.O. acknowledge support from the UK Space Agency. G.H. acknowledges partial financial support from the Austrian FWF grant P20526-N16 and encouragement from Patrick Woudt. We heartily thank all members of the USCO2010 collaboration, whose observations were critical to our successful campaign. We acknowledge with many thanks the variable star observations from the AAVSO International Database contributed by observers worldwide and used in this research, as well as the observers of the Center for Backyard Astrophysics. This publication makes use of data products from the Wide-field Infrared Survey Explorer , which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. This research has made use of the NASA/IPAC Infrared Science Archive, which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.
Paper: 2015A&A...577A.145P (acknowledgments)
The authors acknowledge research funding by the Deutsche Forschungsgemeinschaft (DFG) under the grant SFB 963/1 project A18. L.G. acknowledges support from EU FP7 Collaborative Project Exploitation of Space Data for Innovative Helio- and Asteroseismology (SPACEINN). S.H. acknowledges a collaboration with the Max Planck Institute for Solar System Research through a Max Planck Partner Group established at the Tata Institute of Fundamental Research, Mumbai. We thank Robert Cameron for useful discussions and Jesper Schou and Hannah Schunker for useful comments.
Paper: 2020ApJ...904...66L (fulltext)
dispersion relation for the slow mode gives for quasi-perpendicular and perpendicular propagations. The weak perpendicular magnetic power can be associated with the Alfvén mode. In this discussion, it is assumed that the plasma temperature is isotropic. However, the presence of temperature anisotropy can modify the dispersion relation of the MHD eigenmodes and/or excite other wave modes, such as the mirror mode, kink mode and sausage mode (e.g., Hasegawa 1975 ; Huang et al. 1988 ; Wang Hau 2003 ; Schoeffler et al. 2011 ). The modification of eigenmodes and the excitation of other modes can also affect the turbulence and hence alter the observed power relation. 7. Summary This paper presents the turbulence spectra of magnetic and electron density fluctuations in situ measured by Voyager 1 in the local ISM. The results can be summarized as follows: 1. The present magnetic spectra obtained by Lomb–Scargle periodogram show a good agreement with the results by Burlaga et al. ( 2015 , 2018 ). At m k ≤ 10 −8.8 , the magnetic spectrum is close to a Kolmogorov power law with a one-dimensional power-law index −5/3. The magnetic SDFs show a bulge of enhanced magnetic power at m k = 10 −8.8 –10 −8.2 . 2. We extend our previous study of the electron density turbulence spectrum (Lee Lee 2019 ) and spans the data coverage to 2019 June. The composite spectrum of both the present in situ measurements and the earlier remote observations shows the Kolmogorov power law in the inertial range (10 6 –10 18 m) and an enhanced power in the kinetic range (50–10 6 m). 3. The electron density turbulence measured by Voyager 1 in the local ISM shows higher intensity than that of the remote observations in the distant ISM by a factor of 10 1.96 ≈ 91. Such an enhanced turbulent power can be resulted from a combination of the energy sources from both the turbulent interstellar plasma and the turbulent solar wind. 4. The relationship between the outer scale L 0 , and the rms values of magnetic and electron density fluctuations are obtained. In the calculation with only in situ measured data of electron density and magnetic field, we obtain and for L 0 = 3 × 10 14 m. Burlaga et al. ( 2018 ) obtained the same outer scale and interpreted this outer scale as the spatial range of the disturbed local ISM, which is separated by the bow wave or bow shock from the undisturbed local ISM. 5. For the typical interstellar cloud size L 0 = 10 18 m, we obtain from the in situ measured magnetic data and obtain by including both the in situ measurements and remote observations in the calculation of electron density SDFs. These rms values of magnetic and electron density fluctuations are much higher than the in situ measured mean values because the turbulence amplitude becomes larger at a longer wavelength. Chepurnov Lazarian ( 2010 ) measured a high electron density fluctuation power at the scale of an interstellar cloud. A high magnetic strength of tens of nanotesla has been observed at the
Paper: 2016MNRAS.456.3175M (acknowledgments)
The research of JRM is supported through a Royal Society University Research Fellowship. The authors thank Daniel Mortlock for reviewing a draft of the paper and the referee Nancy Elias-Rosa. The authors are grateful to Jason Kalirai, Paul Crowther and Simon Goodwin for their useful discussions during the preparation of this manuscript.
Paper: 2019MNRAS.482.2670B (fulltext)
by cutting the first 10 multipoles. Figure 6. We plot the SNR for the optimistic Euclid cluster survey (Eu_cl_opt) as a function of l min (top left), the maximum redshift probed by the survey (top right), the area of the sky survey (bottom left), and the minimum observed mass as over the redshift range 0.2 ≤ ≤ 2 (bottom right). Dashed line represents the expected SNR for the Eu_cl_opt specifications. All the SNR take into account of the contribution from CMB E-mode polarization according to equation ( 21 ). Bottom left-hand panel of Fig. 6 shows the SNR as a function of the observed sky fraction, which does not affect just equation ( 21 ) as SNR, but it changes also the amount of total clusters observed, i.e. the shot-noise error. The SNR is sufficiently robust to a reduction of max ; the forecast SNR remains above a detection for max ≳ 1.4 for the optimistic Euclid cluster survey when the CMB polarization is added. We finally study the dependence of the SNR when changing M min . We vertically shift a redshift independent selection function around 8 × 10 13 M ⊙ , as representative of the selection function from (Sartoris et al. 2016 ) for the photometric Euclid cluster survey. The results in Fig. 6 (bottom left-hand panel) show that the expected selection function for Euclid would be optimal in terms of SNR. We can conclude that for the ISW detection is more important to have wide surveys, covering a large fraction of the sky, than deeper ones, since the surveys analysed are already signal dominated on the scales relevant for the ISW. We now briefly discuss the dependence of the SNR on the underlying cosmology. The cross-correlation power spectrum is sensitive to the total matter density Ω m and to the dark energy equation of state 0 . They both change the amplitude of (since for a flat universe an increased amount of matter density corresponds to have a smaller amount of dark energy density). Moreover, the peak of is shifted according to a different matter-dark energy equivalence. We show the dependence of the SNR on these two parameters in Fig. 7 by keeping fixed all the other cosmological parameters (note that we change σ 8 according to the variation of Ω m and 0 ). The SNR varies less than when we change Ω m up to away from the Planck best fit (Aghanim et al. 2016 ). We find a stronger effect on the dark energy parameter of state 0 . Even a small shift of Δ 0 ≃ 0.2 would lead to a difference larger than on the SNR. In particular, by assuming a fiducial cosmology with a smaller value of 0 leads to a higher SNR. Figure 7. Top panel: dependence on Ω m of the SNR for the ISW detection with clusters (optimistic Euclid cluster survey, blue line) and with galaxies (photometric Euclid galaxy survey, grey line). Bottom panel: dependence on the dark energy equation of state 0 of the SNR for the ISW detection. 5.2 Combining clusters with galaxies Different LSS surveys can be combined to increase the significance of the ISW detection. The
Paper: 2019MNRAS.483.1737K (acknowledgments)
ACKNOWLEDGEMENTS The authors thank the reviewer for a thorough review and highly appreciate the comments and suggestions, which significantly contributed to improving the content. RK is thankful to the Council of Scientific and Industrial Research, New Delhi, for a Senior Research Fellowship (SRF). RK would also like to thank Miss Alessia Garofalo for helping her with the Gaia data during VOSS 2018. DM gratefully acknowledges support provided by the BASAL Center for Astrophysics and Associated Technologies (CATA) through grant PFB-06, and the Ministry for the Economy, Development and Tourism, Programa Iniciativa Científica Milenio grant IC120009, awarded to the Millennium Institute of Astrophysics (MAS), and from project Fondecyt No. 1170121. HPS and RK thank the Indo-US Science and Technology Forum for funding the Indo-US virtual joint network centre on ‘Theoretical analyses of variable star light curves in the era of large surveys’. RK and DM are also very grateful for the hospitality of the Vatican Observatory, where this work was started.
Paper: 2018ApJ...860...57A (acknowledgments)
We thank the referee for helpful comments that have helped us to improve the presentation of the paper. This work was supported by the National Basic Research Program (973 Program) of China (grant No. 2014CB845800), the National Key Research and Development Program of China (grant No. 2017YFA0402600), the National Natural Science Foundation of China (under grant Nos. 11722324, 11725314, 11603003, 11633001, 11690024, and 11573014), and the Strategic Priority Research Program of the Chinese Academy of Sciences (grant No. XDB23040100).