adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016ApJ...824...18H (fulltext)
and mid-IR emission by Li Draine ( 2001b ). Figure 8. Schematic of allowable parameters for silicate nanoparticles for which the rotational emission and polarization do not violate observational constraints (white area). The orange shaded region represents the parameter space where the polarization violates the observed AME polarization, and the blue shaded area depicts the space where rotational emission violates the AME and the polarization by nanosilicate violates the UV polarization of starlight for the ISM. 6.4. Comparison with Previous Spinning Dust Studies Previous spinning dust models ( DL98 ; Ali-Haïmoud et al. 2009 ; Silsbee et al. 2011 ; HDL10 ; HLD11 ) dealt with spinning PAHs, because they are a well-established dust population in the ISM (see Tielens 2008 ). The last spinning dust model ( HDL10 ; HLD11 ) treats all known important physical effects, including grain wobbling due to thermal fluctuations within the grain, transient spin-up by single-ion collisions. In particular, the model can be applied to spinning dust grains of arbitrary shape and arbitrary temperature ( HLD11 ). Since the physics of spinning silicate (iron) is essentially analogous to that of spinning PAHs, it is natural to use our advanced spinning dust model for modeling emission from spinning non-PAHs. Finally, the spinning dust model developed in HDL 10 and HLD11 is the unique model that can predict self-consistently the polarization level of spinning dust emission (see also Hoang et al. 2013 , 2014 ); the spinning models from other groups only provide rotational emissivity. Therefore, our spinning dust model can be used to constrain the dipole moment and magnetic properties of nanoparticles using the AME polarization data. 7. SUMMARY In this paper, we have obtained the principal results as follows: 1. We have quantified rotational emission from spinning ultra-small silicate grains for different grain size distribution parameters, various fractions of total Si abundance contained in ultra-small grains , and a wide range of the dipole moment per atom β . 2. The polarization fraction of spinning silicate emission is found to increase with decreasing value of β . The polarization fraction is below for the dipole moments , but it can reach for assuming K. 3. We have identified that the presence of silicate nanoparticles with and the dipole moment does not violate the UV polarization of starlight and the observed polarization of the AME. With this realization (), rotational emission from spinning nanosilicate can adequately reproduce the observed AME from the ISM. 4. Our quantitative results suggest that rotational emission from spinning silicate nanoparticles may be an important source of AME. Future observations searching for signatures of nanosilicates from the regions with prominent AME would be valuable in understanding the carrier of AME. There are several outstanding questions on the problem of spinning nanosilicates, including the dipole moment and
Paper: 2016A&A...593A..21M (fulltext)
the Small and Large Magellanic Clouds ( Crawford et al. 2001 ; Ridley et al. 2013 ); but also non-detections towards, for example, dwarf spheroidal galaxies ( Rubio-Herrera Maccarone 2013 ). In addition, several efforts have been made to capture periodic as well as single pulse signals from nearby galaxies, with different telescopes. Unfortunately none of these searches discovered new sources. For the deepest of such past surveys, we list the frequencies and sensitivities in Table 1 . These frequencies range from 328–1440 MHz. Based on the facts that at lower frequencies pulsar beams get wider and pulsar fluxes get higher ( Stappers et al. 2011 ), there is a possibility that deep, lower-frequency surveys could find pulsars that these past efforts have missed. Table 2 LOFAR Observations of nearby galaxies M 33, M 81, and M 82. Notes. For tied-array rings (TARs) only the coordinates of the central tied-array beam (TAB) are provided. The LOw Frequency Array (LOFAR, van Haarlem et al. 2013 ) is a radio telescope capable of tracking several nearby galaxies, at long wavelengths. The LOFAR high-band antenna’s (HBA, 120–240 MHz) frequency range approximately coincides with the peak of pulsar flux density distribution (100–200 MHz, Stappers et al. 2011 ), which is an advantage for a pulsar search. Compared to previous low-frequency pulsar searches, further improvements such as the much increased bandwidth (), the high core gain (), and the relatively low antenna temperature (, see Eq. (3) from van Leeuwen Stappers 2010 ) mean that LOFAR can, on the one hand, find many new interesting pulsars (see Coenen et al. 2014 ), and on the other hand, better investigate their fundamental emission peculiarities (see Stappers et al. 2011 ). In general, pulsar beams are thought to be wider at lower frequencies, giving LOFAR the advantage in capturing radio pulses over higher-frequency surveys. Finally, the LOFAR multi-beaming allows for efficient, deep integrations at a sensitivity and field of view unparalleled in the world. The main downside of searching for pulsars with LOFAR is that dispersion and scattering degrade the inherently sharp pulsar peaks. In this paper, we describe the searches we have performed with LOFAR for pulsars in spiral Triangulum Galaxy M 33 (distance ), Bode’s Galaxy M 81 (), and starburst Cigar Galaxy M 82 (). Given their northern positions (see Table 2 ), these three galaxies can be well targeted with LOFAR, as the projected effective area of LOFAR’s fixed dipoles, and thus the sensitivity, is the highest close to zenith (see van Leeuwen Stappers 2010 ). The origin and current environment of a galaxy inevitably affect its star-formation rate and mass-energy distribution. As a result, the pulsar population in nearby galaxies can be different from that of our Milky Way, and a comparison between this population and that of our Milky Way is interesting. Furthermore, measuring a dispersion measure (DM) toward an extragalactic pulsar
Paper: 2015ApJ...798...53K (acknowledgments)
This work was supported by NASA grant NNX10AD78G. 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. We thank the referee, Tim Kallman, for his careful review of the paper and constructive comments. We thank A. Maeder, M. Catalan, and E. Behar for useful suggestions. We also thank G. Ferland and associates for their continuing maintenance of cloudy .
Paper: 2015ApJ...805...12L (acknowledgments)
We thank the anonymous referee for helpful comments and suggestions. Support for A.E.R. was provided by NASA through Hubble Fellowship grant HST-HF2-51347.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS 5-26555. A.E.R., J.E.G., and E.G. thank the Kavli Institute for Theoretical Physics for hosting the 2013 workshop “A Universe of Black Holes,” during which this project began. This research was supported in part by the National Science Foundation under Grant No. NSF PHY11-25915. This research has made use of data obtained from the Chandra Data Archive and the Chandra Source Catalog, and software provided by the Chandra X-Ray Center (CXC) in the application packages CIAO, ChIPS, and Sherpa. 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 NASA. This work has also used observations made with the NASA Galaxy Evolution Explorer. GALEX is operated for NASA by the California Institute of Technology under NASA contract NAS5–98034. This study 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 NASA. We are grateful to Michael Blanton and all who helped create the NASA-Sloan Atlas. Funding for the NASA-Sloan Atlas has been provided by the NASA Astrophysics Data Analysis Program (08-ADP08-0072) and the NSF (AST-1211644).
Paper: 2017ApJ...838..133S (fulltext)
of XMM - Newton and NuSTAR simultaneous data. As a first attempt, we simply adopted this absorbed PLCUT model as a pure phenomenological and statistically acceptable description of the continuum emission. The results from fitting the eight time-resolved 3–78 keV spectra in this way are reported in Table 2 . Table 2 Time-resolved Spectroscopy (3–78 keV), Fitting Only NuSTAR Data of the Flare Peaks Note. a Fluxes (corrected for the absorption) and luminosities are in the energy range 1–100 keV. In some of these spectra, negative residuals appeared at energies between 15 and 40 keV. To account for these absorption features, we modified the PLCUT continuum multiplying it with a cyclotron absorption model ( cyclabs in xspec package). At first, we calculated the line significance by increasing the Δ χ 2 value until the confidence region boundary of the depth (Depth cycl in Table 3 ) of the cyclotron line crosses 0. The significance of these lines was greater than 2 σ in five (of eight) spectra (flare numbers 1, 2, 3, 4, and 6), so we have reported absorption line parameters only for these spectra in Table 3 for clarity. The absorption lines were measured with a significance ranging from σ = 2.3 to σ = 4.4 (with cyclabs model), with the best value obtained during the first flare observed by NuSTAR . The centroid energy was different: in spectra 1, 4, and 6 the feature was in a narrow range around 17–18 keV, while during spectrum 3 it was at ∼33 keV. In spectrum 3, the line at ∼17 keV was undetected: we could place an upper limit (Depth cycl ≲ 0.18) to the depth of the cyclabs line with the centroid energy fixed at 17 keV (and line width of 2 keV). Table 3 Same as Table 2 ( NuSTAR Only), Considering Only Flare Peaks 1, 2, 3, 4, and 6, Where the Inclusion of an Absorption Feature Resulted in a Line Significance Larger than 2 σ Notes. a cyclabs model in xspec . b This line significance was calculated by increasing the Δ χ 2 value until the confidence region boundary of the depth (Depth cycl ) of the cyclotron line crosses 0. In order to test the significance of the absorption line, since the F-test could bring unreliable results (Protassov et al. 2002 ), we used Monte Carlo simulations to confirm the presence of the cyclotron line in spectrum 1 (our best case, Figure 6 ), following the approach described by several authors (Barrière et al. 2015 ; Bhalerao et al. 2015 ; Lotti et al. 2016 ). We used the simftest routine in xspec with 100,000 simulations, 6 6 simftest is a script that tests for the presence of an additional component simulating N fake spectra based on the model without such component. It then fits the spectra with both the models with and without the additional component registering the Δ χ 2 and comparing it with the Δ χ 2 obtained with the real data to obtain the probability of a false detection. fixing the N H to the values reported in Table 3 to speed up the process, and found that the probability of such a line to be required by
Paper: 2020ApJ...888...96H (fulltext)
measurement. 4. We claim that VGT–PCA as a modification of the VGT is advantageous in studying the magnetic field morphology and predicting the contribution from the Galactic foreground. Appendix A GALFA-H <sc>i</sc> Data Selection In this work, the ensemble GALFA-H i data is separated into three data sets: East (A), North pole (B), and West (C). Each data set is divided into five individual subregions. The velocity range of each data set is selected, such that the majority of the Galactic neutral hydrogen gas is included. Table 1 gives the description of the GALFA-H i data set used in this work. The uncertainty on the AM is given by the standard error of the mean, i.e., the standard deviation divided by the square root of the sample size. Figures 11 – 16 show the morphology of the POS magnetic fields inferred from Planck polarization and VGT–PCA with resolution ≃1°. Figure 11. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 240 to 480 and decl. from −12 to 371, and (b): R.A. from 480 to 720 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the histogram of the relative orientation between the magnetic field predicted by VGT–PCA and the one inferred from Planck polarization. Right bottom: the variation of the AM with respect to the polarization percentage. Figure 12. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 720 to 960 and decl. from −12 to 371, and (b): R.A. from 960 to 1200 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the histogram of the relative orientation between the magnetic field predicted by VGT–PCA and the one inferred from Planck polarization. Right bottom: the variation of the AM with respect to the polarization percentage. Figure 13. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 2640 to 2880 and decl. from −12 to 371, and (b): R.A. from 2880 to 3120 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the histogram of the relative orientation between the magnetic field predicted by VGT–PCA and the one inferred from Planck polarization. Right bottom: the variation of the AM with respect to the polarization percentage. Figure 14. The morphology of the POS magnetic fields on the sky patch with (a): R.A. from 3120 to 3360 and decl. from −12 to 371, and (b): R.A. from 3360 to 3600 and decl. from −12 to 371. Left: the magnetic field predicted from VGT–PCA (red segments) with resolution ≃1°. Middle: the magnetic fields inferred from Planck polarization (blue segments). Right top: the
Paper: 2017MNRAS.466.4633A (fulltext)
Virial equilibrium (PVE), instead of the usual SVE. The implication, being a single magnitude of the external pressure, P ext , may be insufficient to explain the variations reported by Heyer etal. ( 2009 ). Instead, their data could be reconciled only if different clouds in the sample experienced different magnitudes of pressure in the range 10 4 10 7 K cm 3 . Equivalently, it meant that the sizelinewidth relation would be modified by the magnitude of external pressure, P ext , experienced by a GMC. In an earlier work, Ballesteros-Paredes ( 2006 ) strongly argued against GMCs obeying the SVE because: (i) clouds being the consequence of turbulent fragmentation in the interstellar medium (ISM), the fragmentation process must necessarily induce a flux of mass, momentum and energy between clouds and the ISM, and (ii) clouds often exhibit asymmetries in their respective line-profiles, which is inconsistent with clouds obeying the SVE. Instead, the Larsons scaling relations should, at best, be viewed as evidence for energy-equipartition. The possibility of bound, turbulence-supported clouds as suggested by Krumholz McKee ( 2005 ) is difficult to reconcile, for it is unlikely that there will be no redistribution of mass within such clouds over their lifetime (Ballesteros-Paredes 2006 ). Gas dynamics within a typical GMC is likely governed by collisions between smaller clumps within them (e.g. Anathpindika 2009a , b and references therein), and/or feedback from existing stellar populations (see e.g. Mac Low Klessen 2004 and references therein). In a more recent work, Ballesteros-Paredes etal. ( 2011 ) argued that the variations in the sizelinewidth relation reported by Heyer etal. ( 2009 ) is actually consistent with the scenario of hierarchical fragmentation in which a cloud does not collapse as a whole, but only isolated pockets in it collapse to form stars. In this paradigm, although turbulence in the ISM possibly plays a role in assembling the cloud, post its formation, when the contribution due to self-gravity becomes significant, the cloud no longer needs to be in equilibrium with the external medium. It is therefore unnecessary to resort to mechanisms that can actually hold clouds with complex geometries and density distributions in approximate equilibrium (see also Burkert Hartmann 2004 ). Simulations of unbound clouds leading to inefficient star formation were discussed by e.g. Clark etal. ( 2005 ) and Clark, Bonnell Klessen ( 2008 ). The virial state of GMCs has also been interrogated numerically. Dobbs etal. ( 2008 ) and Tasker Tan ( 2009 ), for instance, reported that clouds forming in a galactic disc typically have a virial coefficient between 0.2 and 10. Furthermore, Dobbs etal. ( 2011 ) argued that intercloud collisions in the disc of a galaxy was a viable mechanism to render clouds unbound. Alternatively, several other authors examined the formation of clouds out of collisions between large-scale flows (e.g. Vzquez-Semadeni, Passot
Paper: 2016MNRAS.463.3563T (fulltext)
at a distance of 1 arcsec (140 au) from the star. 5.6 Orientation in space The envelope thickness at y = 0, measured by an FWHM of ∼0.55 in λ (Fig. 10 , left) meaning ∼0.7 arcsec, is consistent with the value quoted in Section 3.1 from which an upper limit of ∼22° was placed on a possible tilt θ 2 between the disc plane and the ( y , z ) plane about the y -axis. The observed ∼10° tilt θ 1 about the z -axis of the map of 〈 V z 〉 that was mentioned in Section 3.2 and illustrated in Fig. 4 deserves some comments. As remarked then, such a tilt is also seen in the integrated flux for distances from the star exceeding ∼3 arcsec, not only in the present data (Figs 1 and 3 , left), but also in infrared observations (Tobin et al. 2008 ). The difference of inclination of the central part of the envelope, as measured from the integrated flux, and of the outer part, including the outflow, is not due to some trivial geometric effect but is real. Many factors may play a role in this context, such as magnetic field (see for example the review of Li et al. 2014 ) or binarity (Loinard et al. 2002 ). 6 SUMMARY In summary, the main original contribution of the present analysis to our understanding of the formation process of L1527 is the presentation of a simple 3D parametrization of the morphology and kinematics of the gas envelope based solely on the observation of the C 18 O (2–1) line emission from regions that are not dominated by absorption. In the explored range, the model, which uses eight relevant parameters, reproduces observations significantly better than earlier attempts. This was made possible by assuming central symmetry and axisymmetry about the x (west–east) axis and by excluding from the analysis Doppler velocities between 0 and 0.32 km s −1 and a band of the sky map of ±0.675 arcsec about the x -axis. Moreover we have reduced the radial dependences of the temperature and density to a single quantity, the effective emissivity. We have presented arguments showing that such assumptions are indeed reasonable. The main conclusions of the analysis are as follows. Rotation : the model uses successfully trajectories spiralling down towards the disc on paraboloids coaxial with it. We give evidence for the dominance of rotation over the explored range and confirm that the rotation curve is as expected from a transition from an inverse distance law to a Keplerian regime. The rotation velocity decreases from ∼1.66 to ∼0.34 km s −1 when r increases from 1 to 5 arcsec. However, the range explored is too distant from the star to allow direct observation of the disc. In-fall velocity : we measure a mean in-fall velocity of 0.43 ± 0.10 km s −1 over the explored range, smaller than free-fall velocity, with no evidence for a significant r -dependence, in particular no evidence for the sudden jump to ∼1.5 km s −1 required by Ohashi et al. ( 2014 ) to describe the absorption-dominated central region. Central mass : using simple arguments of energy conservation, we
Paper: 2018A&A...619A.153R (acknowledgments)
Acknowledgements This work was supported by CONICYT through its grants CATA Basal PFB06, QUIMAL project 140002, ALMA 31150012 and Fondecyt 11140428, ESO-Chile Joint Committee for Development of Astronomy, and NL NOVA ALMA RD project. We thank Xilinx Inc. for the donation of FPGA chips and software licenses.
Paper: 2015MNRAS.454.1132T (acknowledgments)
The author wishes to thank the anonymous reviewer for useful comments that lead to significant improvement of the paper.
Paper: 2018MNRAS.477..894A (acknowledgments)
ACKNOWLEDGEMENTS The authors express thanks to Aniruddha Kembhavi for a careful reading of the manuscript and comments. S.A. acknowledge the use of IUCAA cluster Sarathi for the computational work. A.K.A. would like to thank the Square Kilometre Array South Africa (SKA SA) for funding the research project. This research has been conducted using resources provided by the Science and Technology Facilities Council (STFC) through the Newton Fund and the SKA Africa. Funding for the SDSS IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org . SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional / MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.
Paper: 2015MNRAS.446.3502L (acknowledgments)
LL would like to thank Robert Beswick for fruitful discussion and helpful comments. We thank an anonymous referee for constructive comments, which helped improve the manuscript. KKK acknowledges support from the Swedish Research Council.
Paper: 2017A&A...598A..15S (acknowledgments)
J.V. would like to acknowledge the availability of computing resources on the Occigen super computer at CINES (France) to perform the computations required for modeling the theoretical meteoroid streams. Special acknowledgement also goes to all members of the Croatian Meteor Network for their devoted work on this project.