adsabs/WIESP2022-NER huggingface dataset:
Paper: 2021MNRAS.502.1253J (fulltext)
trials. There are nine pulsars in our sample that have had RMs measured for the first time. These are listed in Table 3 . PSR J1643−4505, once the high RM is taken into account, joins the ranks of pulsars with high and very high linear polarization fraction. In contrast, the linear polarization fraction for the high pulsar PSR J1055−6028 remains low even after the RM correction. We note the extremely high value of RM uncovered for PSR J1114−6100, described in more detail in the subsection below. We have found a substantial number of pulsars for which our value of RM is more than 10 rad m −2 away from the published values as given in v1.63 of the ATNF pulsar catalogue (Manchester et al. 2005 ). 1 These pulsars are listed in Table 4 . The published value of PSR J1413−6141 was seriously in error, applying the correct value reveals that this pulsar has only a moderate linear polarization fraction. For PSR J0857−4424, the published value from 20 yr ago of −75 rad m −2 is erroneous; we measure +162 rad m −2 , a difference of more than 200 units. Table 3. Pulsars without previous RM measurements. The uncertainty is given in brackets and refers to the last digit. Table 4. Pulsars with derived RMs that differ by more than 10 rad m −2 from the published values, RM cat . The uncertainties, σ and σ cat , are also listed. Note . References: (1) Crawford, Manchester Kaspi ( 2001 ), (2) Hamilton Lyne ( 1987 ), (3) Han et al. ( 2006 ), (4) Han et al. ( 2018 ), (5) Han, Manchester Qiao ( 1999 ), (6) Johnston Weisberg ( 2006 ), (7) Johnston et al. ( 2007 ), (8) Noutsos et al. ( 2008 ), (9) O’Brien et al. ( 2008 ), (10) Rand Lyne ( 1994 ), (11) Taylor, Manchester Lyne ( 1993 ), (12) Weltevrede Johnston ( 2008 ). We observe that there are sometimes significant differences between the RMs returned by the two methods as can be seen in Fig. 7 . Karastergiou ( 2009 ) pointed out that the effects of interstellar scattering can lead to erroneous measurements of RM, and that the method of Noutsos et al. ( 2008 ) was best to use in the case of scattered profiles. In addition, Ilie et al. ( 2019 ) showed the presence of (apparent) RM variations across the pulse profile that meant that different RMs can be obtained depending on the method used. The most extreme example of this is PSR J1600−5044 for which we obtain an RM of 90 and 135 rad m −2 using the two methods. At low frequencies, the pulsar is heavily scattered, at high frequencies the position angle of the linear polarization has a very steep swing across the pulse profile. This is the scenario pointed out by Karastergiou ( 2009 ) as being the most detrimental to measuring correct values of RM. 6.1 PSR J1114−6100 We measured a value of −6729 ± 2 rad m −2 for the RM of PSR J1114−6100. This is the fourth highest value of |RM| for any known pulsar, beaten only by the Galactic centre magnetar PSR J1745−2900 (Shannon Johnston 2013 ), and two other pulsars near the Galactic centre, PSRs J1746−2849 and J1746−2856
Paper: 2016MNRAS.463.3637R (acknowledgments)
We thank the referee for constructive comments which helped to improve the manuscript. This work was granted access to the PRACE Research Infrastructure resource Curie hosted at the TGCC (France). FR acknowledges support from the European Research Council through grant ERC-StG-335936 . BF acknowledges the financial support from the Programme Investissements d'Avenir (PIA) of the Initiative d'Excellence (IdEx) programme from Université de Strasbourg.
Paper: 2020MNRAS.492.4858H (fulltext)
massive star clusters (or OB associations) is a power-law with slope ξ ≃ −2 ± 0.5 (Rosolowsky 2005 ; Hopkins 2012 ): where, assuming ξ = −2 (Hopkins 2012 ), we find A = M *, gal /Λ, with . Assuming M ⊙ and M ⊙ , we estimate Λ ≈ 9.2. Therefore, assuming an escape fraction from the atomic phase of the ISM in the galaxy (defined excluding the absorption due to the molecular cloud) that is constant as a function of the cluster mass, we find: Therefore, as anticipated before in Section 3.3 , in the local Universe (fiducial clouds) the escaping ionizing radiation from a galaxy is produced by roughly equal contribution from small and large mass star clusters, and the number of escaping photons is ∼10 59 per unit solar mass in stars. Therefore, the total escaping radiation is quite insensitive to the upper and lower mass limits of the mass distribution of OB associations. Compact star clusters are similar but with ∼10 times more ionizing photons per mass in stars. For very compact clouds (100 times denser than the fiducial clouds) the escaping ionizing radiation is dominated by the few most massive star clusters in the galaxy, and the number of escaping photons per units star mass is about 40 times higher than for the fiducial clouds. Also, if we make the simple assumption that the mass of the most massive star cluster is related to the total stellar mass M *, gal of the galaxy, by setting , we find . Hence, if star clusters in high-redshift galaxies form in very compact molecular clouds, massive galaxies would be more efficient contributor to propel reionization than dwarf galaxies. Of course the discussion above is only valid if is constant not only as a function of the star cluster mass but also as a function of the mass of the galaxy. Similar to S esc, tot , we can estimate the total emitted ionizing radiation by OB association: and the mean escape fraction from a galaxy by taking the ratio : This last equation confirms that from galaxies in the local Universe (fiducial clouds) is extremely small , and only assuming that molecular clouds at redshift z > 6 were 100× denser than in the local Universe is possible to propel reionization with UV radiation from massive stars in galaxies. 5 SUMMARY AND CONCLUSIONS In this paper, the second of a series, we calculate the hydrogen- and helium-ionizing radiation escaping realistic young star cluster forming in turbulent molecular clouds. To the best of our knowledge this is the first work in which is calculated by self-consistently simulating the formation, UV radiation feedback, and contribution to the escaping ionizing radiation from individual massive stars producing the observed IMF slope and normalization. We used a set of high-resolution radiation-magnetohydrodynamic simulations of star formation in self-gravitating, turbulent molecular clouds presented in He et al. ( 2019 ), in which we vary the mass of the star-forming molecular clouds between m gas = 10 3 M ⊙ and 3 × 10 5 M ⊙ and adopt gas
Paper: 2019A&A...627A..77M (acknowledgments)
A.M.B. thanks Christian Ginsky for the help in reducing the SPHERE/IRDIS data and the useful discussion afterwards, and Wolfgang Brandner for the help in reducing the GPI data. A.M.B. would also like to thank the anonymous referee for the useful and constructive comments. G.M.K. is supported by the Royal Society as a Royal Society University Research Fellow. G.C. and S.P.Q. thank the Swiss National Science Foundation for the financial support under the grant number 200021_169131. J.O. and N.G. acknowledge financial support from the ICM (Iniciativa Científica Milenio) via the Núcleo Milenio de Formación Planetaria grant. J.O. acknowledges financial support from the Universidad de Valparaíso, and from Fondecyt (grant 1180395). N.G. acknowledges support from project CONICYT-PFCHA/Doctorado Nacional/2017 folio 21170650. A.M. and A.Q. acknowledge the support of the DFG priority program SPP 1992 “Exploring the Diversity of Extrasolar Planets” (MU 4172/1-1 and QU 113/6-1). This research has made use of the Washington Double Star Catalog maintained at the U.S. Naval Observatory, and 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 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 made use of Astropy ( http://www.astropy.org ), a community-developed core Python package for Astronomy ( Astropy Collaboration 2013 , 2018 ).
Paper: 2018ApJ...852...17C (fulltext)
the spacecraft to the magnetic null (see Fu et al. 2015 for details). The PI method significantly depends upon the size of SC tetrahedron. Usually, a large tetrahedron (large SC separation) is favorable for null detection, while a small tetrahedron (small SC separation) is not. In contrast to the PI method, the FOTE method can detect a null both inside and outside of the tetrahedron, and can avoid limitations of the PI method such as data resolution, instrument uncertainty ( offset), and tetrahedron size (Fu et al. 2015 ). Taking the advantages and disadvantages of these two methods into account, in this study we will use the FOTE method to find magnetic nulls. In addition to null detection, the FOTE method can also be used to identify magnetic-null types based on the three eigenvalues () of the matrix and reconstruct magnetic-null topology by tracing magnetic field lines around the null (Fu et al. 2015 , 2016 ). In theory, the sum of the three eigenvalues is zero , meaning that either all of the three eigenvalues are real, or one is real while the other two are conjugate complex. If all of the eigenvalues are real, the null is of radial type, which includes A- and B-type. If one eigenvalue is real while the two others are conjugate complex, the null is of spiral type, which includes - and -type. A, B, and , are all null types in the 3D regime (Lau Finn 1990 ). They can, however, degenerate into 2D structures in certain conditions. Following Fu et al. ( 2015 ), we simplify the A- and B-type nulls to 2D X-line when , and simplify the - and -type nulls to 2D O-line when . If the relationship among the three eigenvalues belongs to none of the above six categories, we classify the null type as “unknown.” Such identification of magnetic-null types is summarized in Table 1 . Table 1 Null Type Identification Using the Three Eigenvalues () of Matrix δ , which is Derived from Four-point Measurements 3. Observations and Analyses 3.1. Event Overview The Earth's magnetosheath is a region downstream of the bow shock where the magnetosphere interacts with the solar-wind flow. Due to this interaction, usually strong turbulence of magnetic field and its resultant thin current sheet, where magnetic reconnection quite possibly occurs, can be observed (Burgess et al. 2005 ). Therefore, the magnetosheath is an ideal place to investigate magnetic reconnection driven by turbulence or reconnection in turbulent plasmas. In this study, the reconnection event we consider was measured by Cluster (Escoubet et al. 2001 ) on 2002 March 27. This event has been reported by Retinò et al. ( 2007 ) and further investigated by others (e.g., Sundkvist et al. 2007 ; Chasapis et al. 2015 ). In this event, Cluster was located in the magnetosheath at [9.6, −8.0, −8.1] RE in Geocentric Solar Ecliptic (GSE) coordinates; it forms a regular tetrahedron, with inter-spacecraft separation of ∼100 km. Such separation is quite small, so that the measurements of magnetic field by four Cluster
Paper: 2015MNRAS.446.1293C (acknowledgments)
KEKC thanks the Science and Technology Facilities Council of the United Kingdom (STFC) and JEG thanks the Royal Society for a University Research Fellowship. JSD acknowledges the support of the European Research Council via the award of an Advanced Grant, the support of the Royal Society via a Wolfson Research Merit Award, and both JSD and NB acknowledge the contribution of the EC FP7 SPACE project ASTRODEEP (Ref. No: 312725). AK acknowledges support by the Collaborative Research Council 956, subproject A1, funded by the Deutsche Forschungsgemeinschaft (DFG). We would like to thank Alexandra Pope for useful discussions regarding stacking of clustered populations and Martin Hardcastle for suggesting to perform the radio stack. This work is based on observations carried out with SCUBA-2 on the James Clerk Maxwell Telescope (JCMT). The JCMT is operated by the Joint Astronomy Centre on behalf of the STFC, the National Research Council of Canada, and (until 2013 March 31) the Netherlands Organisation for Scientific Research. Additional funds for the construction of SCUBA-2 were provided by the Canada Foundation for Innovation.
Paper: 2021A&A...650A...6C (fulltext)
211 A and 171 A from AIA, and the bottom panels are the line-of-sight (LOS) magnetogram and intensity map from HMI. For the EUV images, our study utilizes bandpass filter images, and as such examines only periodicity in the EUV bandpass brightnesses, and not in other properties such as line Doppler velocity or Doppler width. The EUV and radio data were examined for periodicities utilizing a method that identified peaks and valleys above a threshold value in the normalized power (PSP and Wind) or normalized detrended light curve (SDO/AIA and HMI). The detrending time periods and intervals for analysis of AIA data were selected to avoid introducing artificial periods ( Auchère et al. 2016 ; Dominique et al. 2018 ). Periodicities for the radio data were determined both using the measured values and using data interpolated to the cadence of the AIA data. Figure 4 shows an example of the “peak” approach for the radio, EUV and HMI data sets. Panels a and b show the normalized power above average for the two frequency bands (6.2 and 18.4 MHz) from the PSP radio data versus time. Panel c plots the resulting average periods versus frequency for the HFR (>5 MHz) band, which was determined using a threshold of one for the normalized power. Panels d and e plot the detrended normalized intensity for two AIA bands, 171 and 211Å in Region 2; and panel f plots the average period versus temperature (based on the peak of the temperatureresponses of each bandpass for the six coronal lines and the one photospheric line) for Region 2, where the periodicitieswere most prominent. The AIA temperature responses are overplotted; colors identify the same lines for both periodicity and temperature response. It should be noted that all of the AIA bandpass filters have broad temperatureresponses and some have bimodal responses. We cannot use these data to measure a strict temperature without differential emission measure analysis, but the peak temperature response gives a rough estimate of which temperaturerange we are likely to be observing. For the filters that have a doubly peaked response, we plotted the temperatures of both peaks for reference. Although some studies of quasi-periodicities in EUV lines have identified a temperaturedependence, the periods we observe are independent of temperature to within the error bars. Panels g and h plot the time series of the HMI intensity for two regions within the EUV subregion 0, and the periods determined for all three HMI regions are plotted in panel i. It is clear that the periodicity in the radio waves (~4–5 min) is comparable to those in the AIA and HMI data. We note that periodicities in the radio, EUV and HMI data were also determined using fast Fourier transforms (FFTs), with similar results. Fig. 3 Regions analyzed overlaid on SDO images. Top row : two AIA filters that have sensitivity to quiescent coronal temperatures, and bottom row : HMI line-of-sight magnetogram and intensity map. Images shown are at a time near the
Paper: 2016ApJ...823...54P (acknowledgments)
J.R. acknowledges funding support from the French Research National Agency: CHAOS project ANR-12-BS05-0009 ( http://www.chaos-project.fr ). J.R. also acknowledges financial support from the UnivEarthS Labex program of Sorbonne Paris Cité (ANR-10-LABX-0023 and ANR-11-IDEX-0005-02).
Paper: 2016A&A...593A.113B (fulltext)
width measurements of several unblended Fe i lines. Projected rotation velocities () were determined by fitting the profiles of the Fe i lines after convolving with the instrumental resolution ( = 75 000) and a macroturbulent velocity adopted from the calibration of Doyle et al. (2014) . We also estimated from the CCF using the procedure of Boisse et al. (2010) and found consistent results: km s and km s for WASP-113 and WASP-114, respectively. Furthermore, we estimated the spectral type using Teff and Table B1 of Gray (2008) . The derived stellar parameters for WASP-113 and WASP-114 are given in Table 4 . We find that the stellar parameters of WASP-113 and WASP-114 are very similar. Table 4 Stellar parameters of WASP-113 and WASP114 from spectroscopic analysis. Notes. Spectral type estimated from and Table B1 of Gray (2008) . 3.1. Stellar age Fig. 6 Modified H-R diagrams for WASP-113 on the left and WASP-114 on the right . We display the stellar models of YY ( Demarque et al. 2004 ). The isochrones are shown solid black line (for Gyr old stars from left to right ) and and the mass tracks in red ( from left to right we show 1.3, 1.2, and 1.1 ) for the corresponding metallicity given in Table 4 . Combining the sin with the stellar radius we derive an upper limit to the stellar rotation period of days and days for WASP-113 and WASP-114, respectively. These allow us to derive an upper limit to the gyrochronological age of Gyr for WASP-113 and Gyr for WASP-114 using Barnes Kim (2010) . However, the lithium abundance suggests an age of Gyr for both stars ( Sestito Randich 2005 ). A discrepancy between the age indicators is not unusual ( Brown 2014 ; Maxted et al. 2015 ); however, the reason is still not clear. A more precise constraint on the age can be obtained by using theoretical stellar models. We follow the procedure of Brown (2014) using three sets of stellar models: the Padova models of Marigo et al. (2008) and Bressan et al. (2012) , the Yonsei-Yale (YY) isochrones of Demarque et al. (2004) , and the Dartmouth Stellar Evolution Database (DSED) models of Dotter et al. (2008) . We use the values of and [Fe/H] derived from the spectroscopic analyses and the transit derived stellar density whose derivation is explained in the next section. For WASP-113 we found an age of Gyr, Gyr, and Gyr respectively for the models of Padova, YY, and DSED. In the left panel of Fig. 6 we show the isochrones and mass tracks for WASP-113 for the YY models. According to these models WASP-113 has a mass of , which is very close to the critical mass for the stellar cores to become convective. Owing to the convective cores, the evolution and consequently the shape of the evolutionary tracks for higher mass stars is significantly different from lower mass stars, as can be seen in this figure. In this region of the parameter space details on the treatment of convective overshooting become important and the uncertainty in the stellar age and mass are higher. We
Paper: 2018MNRAS.474.4447C (fulltext)
the effect of granular convection. Small coloured particles were put on the bottom layer, and the entire apparatus was shaken at Γ = 4.0 for around 12 000 cycles. After the oscillations, it was confirmed that the coloured small particles either remained at the bottom or were pushed to the cylinder wall, but none of them moved to the centre and rose upwards. This shows that granular convection was only slightly induced beside the cylinder wall, but it was not the dominant mechanism for the BNE in our experimental set-up. In this sense, both our numerical simulations and hardware simulations suggest the existence of ‘less-convective’ conditions. 4.2 Results and discussion Variation of the vibration amplitude The necessary conditions to induce the BNE were first investigated by focusing on the vibration amplitude. The amplitude was varied between 2.5, 5.0, and 10.0 mm, and the frequency was also varied to vary the parameter Γ for each amplitude. Fig. 12 shows the results of the evaluation of the BNE and the RBNE. For each amplitude value, the RBNE was induced over Γ ≈ 3.5, which is consistent with the evaluation by the one-dimensional model. Fig. 13 (upper panel) shows the number of cycles it took for the intruder to rise to the surface. The numbers of cycles required to rise to the surface was much larger than for the nominal cases of the simulations as a whole, especially under the conditions of case (b) for the one-dimensional model. This is because of the size difference of the small particles or the fact that both the particle–particle and particle–wall friction constants were lower in the laboratory experiments. It is clear that the BNE is more likely to occur as Γ increases. The decrease in the number of cycles plateaued at Γ ≈ 1.9 and this indicates that the mechanism for inducing the BNE changed at this point. This result is interpreted as the boundary between the cases (a) and (b) for the one-dimensional model with the coefficient of restitution being 0.4 e 0.6, which was estimated from Fig. 3 . This is also fairly consistent with the assumptions of the numerical simulations. The estimated coefficient of restitution is an ‘empirical’ value, which may be different from the value obtained in the bouncing experiments. It can be stated that the cases (a) and (b) are, respectively, the ‘slow BNE’ case and the ‘fast BNE’ case. For the cases categorized as (a) in the one-dimensional model where Γ 1.9, it was evaluated by Δ h = Af (Γ, e ) (Fig. 2 ) as is shown in Fig. 13 (lower panel), where e = 0.6. Even if the amplitude was different, the number of cycles was similar for the same value of Δ h , which is compatible with our hypothesis. Variation of the density of the intruder The density of the intruder was varied and the vibration amplitude was fixed at 5.0 mm. Three kinds of material were prepared for the intruder: acryl (1.2 g cm −3 ), glass (2.4 g cm −3 ), and high-carbon chromium steel (7.8 g cm −3 ), which were all identical to the