adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018A&A...617A.109O (fulltext)
this exercise is not to make a complete analysis of the origin of the spiral arm that we detect with our observations, but to test the viability of a scenario. We investigated the effect of each of the aforementioned parameters, and inspected the results visually. Figure 8 shows the time evolution for a given simulation, over a span of several hundreds years. For this example, we took t 0 = 2 yr and δt = 0.3 yr. Shortly after t = t 0 a spiral, devoid of particles, appears in the disk (where the particles originally were), but its width decreases for each orbit owing to Keplerian shear. On the other hand, the grains that experienced the wind are set on an elliptical orbit once the wind has stopped (and provided that β wind is not too strong), with their apocentre farther than the original radius of the disk. All these particles tend to travel all-together, therefore, a spiral arm appears in the image at two distinct moments per orbit: when the group of particles is entering or leaving the birth ring (middle and rightmost panels of Fig. 8 ). In our simulations, given that collisions are not taken into account, this phenomenon will persist over time. Nonetheless, if the optical depth is low enough, the train of particles may not collide too often with other particles of the birth ring, and thus the spiral could be long-lived. A movie of the simulation can be found online 4 . Fig. 8 N-body simulation of the effect of anisotropic stellar winds on an ensemble of massless particles, creating a spiral arm in the disk. Nonetheless, the δt timescale is far too long compared to the stellar rotation period for the CME to stay in one preferential direction (0.3 yr compared to ~5 days; Watson et al. 2006 ). The stellar wind would most likely sweep across the entire disk multiple times. If we require δt to be much lower than a typical stellar rotation period, or of the order of the typical duration of the flaring event reported by Uzawa et al. (2011) , then the corresponding β wind value becomes much higher. As an example, for δt = 0.5 days, we find that a similar spiral arm requires β wind = 7500, a value that seems unrealistically high. Indeed, β wind is directly proportional to stellar mass loss rate and inversely proportional to grain sizes following the relation ( Augereau Beust 2006 ): with C D a factor close to 2, Ṁ ⋆ the stellar mass loss rate, v sw the speed of the stellar wind, G the graviational constant, and ρ the dust density. Even though TWA 7 is younger than AU Mic, and therefore potentially more active, a β wind = 7500 value seems rather improbable, as it would require extremely small dust grains (which would not scatter the stellar light efficiently in H -band) or an extremely large mass loss rate. For AU Mic, Augereau Beust (2006) found Ṁ ⋆ ~ 47 Ṁ ⊙ in quiescent state, ~ 2450 Ṁ ⊙ during flares (leading to β wind ~ 40−50), which averaged to ~ 300 Ṁ ⊙ (assuming flares occur 10% of the time). This means that the flares of TWA 7 should be
Paper: 2017ApJ...834...72L (fulltext)
it is difficult to assess the probability that such candidates will be confirmed as pulsars, because confirmation strategies differ between surveys and usually limit the number of reobservations n REOBS to a handful because of constraints on telescope time. As a result, in an extreme case like PSR J1929+1357, the probability of confirming a discovery is approximately , so that the probability of making a confirmed discovery is . In 2013, with and a reasonable value of , the probability of making a confirmed discovery of a pulsar was 3 × 10 −4 . We note that, ideally, reobservations should also be made on a specifically designed set of timescales in order to capture pulsars with the wide range of switching timescales that we now see to be possible in this class of objects. In the case of PSR J1929+1357, it was fortunate that the pulsar was ON during the second attempted reobservation; in the next 93 observations, it was OFF. Had the first 5 reobservations been unsuccessful, it is possible that even such a strong pulsar would remain unconfirmed. Similar pulsars, but with one tenth of the flux density, must surely exist and would be clearly detected in the survey observations, particularly with the high sensitivity of the Arecibo Telescope used for the PALFA survey, but the case for extended reobservation efforts would be even less compelling: unconfirmed detection would be attributed to radio-frequency interference or to the detection of a normal pulsar in a distant sidelobe. For these reasons, there may be as many as several thousand strong pulsars like PSR J1929+1357 in the sky, which happen to be OFF when surveyed or, if ON, are OFF during confirmation observations. Similar but less severe selection effects preventing the discovery of objects like other long-term intermittent pulsars also contribute to what must be a population of neutron stars of significant size compared to that of normal pulsars. As we noted earlier, RRATs also suffer similar selection effects in one-pass surveys. It is likely that UTMOST (Caleb et al. 2016 ) and upcoming new projects, like CHIME (Bandura et al. 2014 ) and MeerTRAP (B. W. Stappers et al. 2016, in preparation) on MeerKAT, will be useful for finding more such objects as they will make many searches of the same piece of sky on various timescales for single-pulse and periodic sources. The discovery of two new long-term intermittent pulsars, PSRs J1910+0517 and J1929+1357, significantly expands the known population of such objects, whose properties are summarized in Table 2 . Although their number is still small (only five such pulsars), we are now in a position to make a few general remarks regarding their properties. They seem to have a rather narrow range of spin periods, from about 0.3 to 0.9 s. Furthermore, there seems to be a positive correlation between the spin period and its derivative, as we can see from their ON positions in the P – diagram (Figure 7 ). This correlation is similar to that observed
Paper: 2018MNRAS.476.1741G (acknowledgments)
Acknowledgements The authors would like to thank Saleem Zaroubi and Adi Nusser for providing useful suggestions on this work. KKD would like to thank the University Grant Commission (UGC), India for support through UGC-faculty recharge scheme (UGC-FRP) vide ref.no. F.4-5(137-FRP)/2014(BSR). SM acknowledges the financial support from the European Research Council under ERC grant number 638743-FIRSTDAWN.
Paper: 2018MNRAS.474.3067S (fulltext)
off free electrons (Heitler 1954 ; Chen Kamionkowski 2004 ), and at high enough energies undergo electron–positron pair production (PP). We here distinguish the cross-section for PP off of the CMB (Agaronyan, Atoyan Nagapetyan 1987 ; Ferrigno, Blasi De Marco 2005 ), atomic and ionized hydrogen and helium, as well as free electrons (Joseph Rohrlich 1958 ; Motz, Olsen Koch 1969 ; Zdziarski Svensson 1989 ). Photons also undergo photon–photon scattering where the injected photon transfers part of its energy to a CMB photon (Svensson Zdziarski 1990 ); however, this process is highly subdominant in the redshift range considered here. The mean free paths (mfp) at mean gas density for selected processes undergone by injected electrons, positrons, and photons are outlined in Fig. 2 for a neutral 10 7 M ⊙ halo at redshift 40. Solid and dot–dashed lines show interactions for the leptons while the dashed show those for photons. The dashed red, magenta, and orange lines show photoionization, Compton scattering, and pair creation off of the gas field, respectively. Electroionization and excitation are shown in green and blue, IC scattering in black, and annihilation via positronium for positron in purple. For a fully ionized halo, the yellow line shows the mfp for Coulomb interaction. For each process, the lines indicate the mfp at the average density of the halo while the shading either side of the curves shows the mfp at r vir and r vir/100 . Figure 2. mfpin units of the virial radius for the various interactions undergone by injected particles within a neutral gas 10 7 M ⊙ halo at redshift 40. Solid lines show interactions for charged particles and dashed for photons. The grey line indicates the virial radius of the halo. Processes shown are photoionization (red), Compton scattering (magenta), and pair creation off of the gas (orange) for photons and ionization and excitation (green and blue) for electrons, as well as IC scattering (cyan) and annihilation via positronium for positrons (purple, dot–dashed line). In all cases, lines show the mfp for the process at the average density of the halo, while the shaded regions either side indicate the mfp at r vir and r vir /100. For reference, the yellow curve shows the mfp for Coulomb scattering in an equivalent, fully ionized halo. The grey line is indicative of the halo's virial radius. Particles with energies such that their interaction mfp are no longer smaller than or comparable to the virial radius will readily escape the halo without either interacting with the gas and/or depositing energy. For the DM annihilation products considered here, the primary interaction of the injected electrons and positrons is IC scattering (injected photons first undergo electron/positron pair creation off of the gas field). The actual energy transfer process occurs via the secondary particle produced in those interactions, in this case, the upscattered IC photons. Therefore, the energy spectrum of the secondary cascade
Paper: 2018ApJ...854...19R (acknowledgments)
The authors would like to thank the anonymous reviewer for constructive comments that improved the manuscript. We also thank Claire Cousins and Clara Blättler for useful discussions. This work was supported by a grant from the Simons Foundation (SCOL awards 339489 to SR and 290357 to LK). This work has made use of the MUSCLES M dwarf UV radiation field database.
Paper: 2018MNRAS.475L..52S (fulltext)
arise from a multiphase ISM. This is also supported by the maximum velocity of the CO (2–1) emission (FWZI/2 ∼ 1000 km s −1 ; Fig. 1 b), which is consistent with the maximum velocity of a warm molecular outflow traced by blueshifted OH absorption (∼1200 km s −1 ; Veilleux et al. 2013 ) and H α emission (≥1000 km s −1 ; Heckman, Armus Miley 1990 ). As seen in other LIRGs (e.g. NGC 1068; García-Burillo et al. 2014 , NGC 3256; Sakamoto et al. 2014 , and NGC 1614; Saito et al. 2017 ), molecular outflows are often spatially extended (a few kpc) and concomitant with (or entrained by) ionized gas outflow. Considering all pieces of evidence described above and some similarities with other LIRGs, we suggest that the four peaks of the broad CO (2–1) components trace molecular outflows in NGC 6240. We derive physical parameters of the molecular outflows found in NGC 6240. The spatially resolved map (Fig. 3 c) allows us to estimate the mass and projected distance of the line width peaks from the launching points. We assume the launching points are the double nuclei, that is, the northern and eastern (southern and western) components of the molecular outflow come from the northern (southern) nucleus (see grey arrows in Fig. 4 ). This spatial configuration is supported by radio continuum observations with very long baseline interferometers (Gallimore Beswick 2004 ; Hagiwara, Baan Klöckner 2011 ), showing that the northern nucleus has an east–west bipolar structure. The direction of those bipolar structures is similar to our assumed morphology of the molecular outflows. We also assume that the inclination (α), CO (2–1)/CO (1–0) line intensity ratio, and CO (1–0) luminosity to H 2 mass conversion factor of the molecular outflows in NGC 6240 are 45°, unity, and 0.8 M ⊙ (K km s −1 pc 2 ) −1 , respectively, for the sake of simplicity. Figure 4. Peak velocity map of the broad component. The velocity field in colour scale ranges from 6850 to 7350 km s −1 . Data points around the four peaks in Fig. 3 c are shown. To estimate the mass outflow rate (), we employ the expression, where v out, proj is the projected velocity of the outflow, is the gas mass of the outflow, R out, proj is the distance from the launching point to the outflowing gas, and α is the inclination of the outflow. This equation assumes a uniformly filled cone geometry (Maiolino et al. 2012 ). All derived parameters related to are listed in Table 1 . v out, proj of the northern and eastern (southern and western) outflows is derived by using the projected velocity of the outflowing gas (Fig. 4 ) and the systemic velocity of the northern (southern) nucleus of 7122 (7164) km s −1 in the radio LSRK velocity frame (Hagiwara 2010 ). Table 1. NGC 6240 molecular outflow properties. The derived mass of each broad component is ∼10 7.9–8.2 M ⊙ (∼10 8.7 M ⊙ in total, which is consistent with the value derived from unresolved CO data; Cicone et al. 2014 ). Since the ionized gas mass of the butterfly
Paper: 2016A&A...586A.135P (fulltext)
magnetic field and the brightness ridges on the sky. 2. Data sets Planck observed the sky polarization in seven frequency bands from 30 to 353 GHz ( Planck Collaboration I 2014 ). In this paper, we only use the data from the High Frequency Instrument (HFI, Lamarre et al. 2010 ) at the highest frequency, 353 GHz, where the dust emission is the brightest. This is the best-suited Planck map for studying the structure of the dust polarization sky ( Planck Collaboration Int. XIX 2015 ; Planck Collaboration Int. XX 2015 ). We use the Stokes and maps and the associated noise maps made with the five independent consecutive sky surveys of the Planck cryogenic mission, which correspond to the DR3 (delta-DX9) internal data release. We refer to previous Planck publications for the data processing, map-making, photometric calibration, and photometric uncertainties ( Planck Collaboration II 2014 ; Planck Collaboration VI 2014 ; Planck Collaboration V 2014 ; Planck Collaboration VIII 2014 ). The and maps are corrected for spectral leakage as described in Planck Collaboration Int. XIX (2015) . As in this first Planck polarization paper, we use the IAU convention for the polarization angle, measured from the local direction to the north Galactic pole with positive values towards the east. For the dust total intensity at 353 GHz we use the model map, , and the associated noise map, derived from a fit with a modified blackbody of the Planck data at GHz, and IRAS at m ( Planck Collaboration XI 2014 ). This map has a lower noise than the corresponding 353 GHz Stokes Planck map. Furthermore, is the dust specific intensity corrected for zodiacal emission, cosmic microwave background (CMB) anisotropies, and the cosmic infrared background (CMB) monopole. The and maps are initially at 48 resolution, and at . The three maps are in HEALPix format 2 with a pixelization . To increase the signal-to-noise ratio of extended emission, we smooth the three maps to resolution using the Gaussian approximation to the Planck beam. We reduce the HEALPix resolution to (71 pixels) after smoothing. To finely sample the beam, we also use the smoothed map with in Appendix A . For the polarization maps, we apply the “” routine of HEALPix that decomposes the and maps into and maps, applies the Gaussian smoothing in harmonic space, and transforms the smoothed and back into and maps at resolution. Most of our analysis is based on the , , and maps, but we also use the maps of the de-biased polarization fraction and angle produced by Planck Collaboration Int. XIX (2015) . The contribution of the CMB polarization to the and maps at 353 GHz is negligible for this study. 3. Structures in the polarization maps We introduce dust polarization (Sect. 3.1 ) and present all-sky images highlighting localized structures in the dust Stokes and maps correlated with corresponding features in intensity (Sect. 3.2 ). Fig. 1 Top : all-sky Mollweide display of the dust emission intensity at 353 GHz after
Paper: 2019ApJS..245...33G (fulltext)
line and the corrected as a dashed line after an overall shift of 0.09 dex; different markers and colors stand for different reporters. The right panel shows the distribution of differences between A (Li) LAMOST and A (Li) H.Res. and the result of the Gaussian fit overplotted with a red solid line. Table 1 Information of the Li-rich Giants Reported by Previous Works 3.3.2. Random Errors In our results, 2746 giants have repeated observations; these could be used to estimate the random errors. We plotted the differences in A (Li) between repeated observations as a function of S/N, T eff , log g , [Fe/H], and A (Li) in Figure 6 . In panel (a), all the 2746 objects with repeated observations are included, which shows that the random errors are sensitive to the S/N decreasing from 0.3 to 0.1 dex with an increasing S/N. In order to avoid the influence of the S/N, only 1118 objects with high-quality data (S/N ≥ 200) were used in the rest panels. Panels (b) and (c) show that the random errors increase from 0.1 to 0.2 dex with increasing T eff or log g , which may be due to the fact that the lithium line at 6708 Å is stronger at low T eff or log g . The random errors have no obvious relation to the [Fe/H], as shown in panel (d), which may be because the strength of the lithium line has no obvious relationship to [Fe/H]. And panel (e) shows that the scatter of the differences of A (Li) remains same when A (Li) goes from 2.0 to 4.5 and is slightly larger in the bin of 1.5 ≤ A (Li) 2.0. Note that the lithium line at 6708 Å is strong enough to be detected when A (Li) is higher than 2.0. The typical value of random errors is 0.2 dex. Figure 6. Differences in A (Li) between multiple observations vs. S/N, T eff , log g , [Fe/H], and A (Li). All the 2746 objects with repeated observations are included in panel (a); only 1118 objects with high-quality data (S/N ≥ 200) were used in the rest panels. The bin sizes are 100, 200 K, 0.3 dex, 0.3 dex, and 0.5 dex, respectively. The red dots are the mean value and the error bars are the standard deviation of the differences in every bin. 4. Results The giants with A (Li) ≥ 1.5 are usually defined as Li-rich giants. In our results, 10,535 Li-rich giants are identified. Their information is listed in Table 2 , including the LAMOST ID, positions, stellar atmospheric parameters provided by LASP, A (Li), and the observed date. Figure 7 shows the histograms of the number of our Li-rich giant sample versus T eff , log g , and [Fe/H], respectively. For the distribution of temperature, there is a peak around 4800 K, and there might be another peak around 5100 K. There are two clear peaks around log g ∼ 2.5 and 3.5 dex, the first is corresponding to the red giant branch and red clump stars. In addition, the distribution of metallicity shows a clear peak around [Fe/H] ∼ −0.15 and a symmetric profile from ∼−0.8 to +0.5 dex. For the stars with metallicity lower than −0.8 dex, there seems to be a second peak in the range of −1.5 to
Paper: 2018ApJ...852...16Y (acknowledgments)
This work is supported by NSFC grants under contracts 41774157, 41231069, 41231068, 41474147, 41574168, and 41421003, and the Specialized Research Fund for State Key Laboratories. The work was carried out at National Supercomputer Center in Tianjin, China and the calculations were performed on TianHe-1 (A). The authors appreciate the invaluable suggestions and comments that were provided by the anonymous reviewer. Special thanks go to Dr. Xiang in our laboratory for the instructive discussions and helpful suggestions to amend the paper.
Paper: 2019A&A...621A..37P (acknowledgments)
Acknowledgements The author acknowledges support from grant MUNI/A/0789/2017. 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. This work is based (in part) on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. 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 work has made use of data from the European Space Agency (ESA) mission Gaia ( https://www.cosmos.esa.int/gaia ), processed by the Gaia Data Processing and Analysis Consortium (DPAC; https://www.cosmos.esa.int/web/gaia/dpac/consortium ). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This research has made use of the SIMBAD database and the VizieR catalog access tool, both operated at CDS, Strasbourg, France. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This paper makes use of data obtained as part of the INT Photometric H α Survey of the Northern Galactic Plane (IPHAS; www.iphas.org) carried out at the Isaac Newton Telescope (INT). The INT is operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias. All IPHAS data are processed by the Cambridge Astronomical Survey Unit, at the Institute of Astronomy in Cambridge. The band-merged DR2 catalog was assembled at the Centre for Astrophysics Research, University of Hertfordshire, supported by STFC grant ST/J001333/1. This research made use of Montage. It is funded by the National Science Foundation under Grant Number ACI-1440620, and was previously funded by the National Aeronautics and Space Administration’s Earth Science Technology Office, Computation Technologies Project, under CooperativeAgreement Number NCC5-626 between NASA and the California Institute of Technology. This research made use of Astropy, a community-developed core Python package for Astronomy ( Astropy Collaboration 2018 ).