adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018MNRAS.480.3503S (fulltext)
length. N J can be written as where n 3 is the number density of the gas in units of 1000 cm −3 , 5, t is the turbulent velocity (approximated here as the velocity dispersion of the cloud) in km s −1 , and μ is the mean molecular weight that we will assume to be 2.3 for a gas composed of H 2 and He. The cloud is gravitationally unstable to collapse if N ≥ N J . The volume density can be obtained from Table 2 by taking the average column density, multiplying by the inverse of the OH/H 2 abundance, and dividing by the path length through the cloud. If we assume the cloud extends in the radial direction, the same amount as in the plane of the sky, the path length would be ≈1–4 pc for distances ranging from 400 to 100 pc. In the most extreme low column density case (), n has a value of 34–140 cm −3 . All other values of T ex lead to higher average densities. For these estimates of n, N J ranges from 3.7 to 7.5 × 10 21 cm −2 . The highest column density derivable from the OH data in Table 2 is based on . Using this value and the OH/H 2 abundance leads to an average N (H 2 ) of 1.1 × 10 21 . Even comparing the highest cloud column densities with the lowest values of N J leads to the conclusion that the cloud is not gravitationally collapsing. In this respect, G211+63 resembles the bulk of high-latitude molecular clouds that are not bound by gravity and likely breaking up on the sound crossing time (). If this analysis is confirmed for other IVMCs then these objects may be transient structures formed as thermal instabilities in large-scale atomic flows (e.g. Shore et al. 2003 ; Shore et al. 2007 ; Barriault et al. 2010b ). 5.2 Linewdiths compared to CO Désert et al. ( 1990 ) observed only one position in the cloud (which we refer to as the ‘CO peak’) in the CO(1–0) line. They noted one component with a velocity full width at half-maximum (FWHM) of . They also reported other CO observations but of the (2–1) line from the IRAM 30 m radio telescope that showed two distinct velocity components like the ones we observe for positions 1–3. They give no line parameters but comment that the strength of the two peaks was highly variable within two beams (about 30 arcsec) of the central observation at (l, b ) = (210.927°, 63.280°). They do show a spectrum for the central CO(2-1) position where the two components are each only two channels wide. Their IRAM observations were made at resolution so the individual components have to be less than wide (FWHM). Our OH linewidths are clearly larger than the CO lines in four out of seven instances. The reason for this behaviour is difficult to ascertain because the CO and OH observations are at significantly different sensitivities and resolutions. The behaviour of molecular gas at cloud edges is not often discussed and there is little consensus on even the phenomenology of spectral lines at cloud edges. If the OH main lines are tracing the diffuse outer regions of the molecular cloud, then the broader profiles could be
Paper: 2018MNRAS.475.5398A (acknowledgments)
Acknowledgements We acknowledge the help of Roberto Menezes, Rogério Riffel, and Rogemar Riffel in reducing a Gemini spectrum of NGC 3115, the continuum of which unfortunately was dominated by stellar emission and contained no information on the LLAGN. We acknowledge useful discussions with João Steiner, Alexander Tchekhovskoy, and Massimo Gaspari. This work was supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) under grants 2015/26831-1 and 2016/24857-6.
Paper: 2016A&A...586A..93N (fulltext)
prior. Since we benefitted from transit observations that span more than three years, we did not use a prior on the period and time of inferior conjunction of the transiting planet. 3.4. Results We present in Table 3 the median and 1 limits of the marginalised posterior distributions after running five chains of 100 000 accepted steps (considering a 20% burn-in phase). The acceptance rate is 25% (40% for the burn-in phase). The convergence of the chains is validated by the test of Gelman Rubin (1992) (PSFR better than 1.01), and the autocorrelations are shorter than 2000 steps. Including the second planet in the model undoubtedly improves the fit. The rms of the CORALIE data after the two-planet fit is ten times smaller than after a one-planet fit. The best fit solution is plotted in Fig. 8 for the transit light curves and in Fig. 9 for the radial velocities. Again, the values provided in Table 3 are not the ones used in Figs. 9 and 8 . We checked that they represent a self-consistent set of parameters by comparing the BIC using both sets of values (best fit and median of the posterior distribution) and get compatible results. Table 3 Median and 1 limits of the posterior marginalised PDFs obtained for the WASP-41 system derived from our global MCMC analysis. Notes. (*) Assuming zero albedo and efficient redistribution of energy. Fig. 8 WASP-41b transit data (blue: FTS ; green: TRAPPIST ; red: Danish ) and best fit model (black line). The TRAPPIST light curve was obtained by binning the data from five transit observations, and the Danish one from one full and one partial transit observations. Each point corresponds to a 7.2 min bin. Fig. 9 WASP-41 radial velocity data (blue: CORALIE, green: HARPS; red: HARPS RM sequence) and best fit model (black line). Top : phase-folded on the period of the inner planet (outer planet subtracted). Middle : zoom on the Rossiter-McLaughlin effect. Bottom : phase-folded on the period of the outer planet (inner planet subtracted). The best-fitting model suggests a misaligned planet with a projected orbital obliquity of . However, the uncertainties are large (see Fig. 10 ), and the data do not allow an aligned orbit to be excluded (). The rotation velocity expected from the photometric rotation period of the star (2.44 km s) is compatible within the error bars with the spectroscopic (2.64 0.25 km s), suggesting that the star is equator-on. That reinforces the possibility of an aligned planet. 4. Discussion We have shown that finding long-period planets with instruments such as CORALIE is still possible around active stars. Recognising the periodic structure of activity-related signals is essential to avoiding false detections. While spots or plages induce signals at the rotation period of the star, the evolution of their coverage of the stellar surface is correlated with the magnetic cycle of the star. Such cycles have periods of several years and must be distinguished from long-period companions. Lovis et al.
Paper: 2017ApJ...835...34T (fulltext)
et al. 2005 ; Helder et al. 2011 , 2013 ), although Shimoda et al. ( 2015 ) suggested the measured efficiency could be higher than reality. It is noteworthy that the thermal and nonthermal emission in this SNR is not uniform and has different morphology, which makes this SNR a suitable laboratory to test a possible relation between the acceleration efficiency and the environment. In this paper, we present the systematic analysis of spatially resolved spectra obtained with the X-ray Imaging Spectrometer (XIS: Koyama et al. 2007 ) on board Suzaku (Mitsuda et al. 2007 ). Unless otherwise noted the uncertainty is given at the 90% confidence interval. 2. OBSERVATION AND DATA REDUCTION The entire region of RCW 86 is covered by six observations with Suzaku . The observation log is summarized in Table 1 . The fields of views (FoVs) are shown in Figure 1 with the dashed squares. Figure 1. The XIS image of RCW 86 in a logarithmic scale. Red and blue, respectively, show emission from 0.5–2.0 keV (soft) and 3.0–5.5 keV (hard). The FoVs of XIS are indicated by the dashed squares. They are EAST (cyan), SE (green), SOUTH (blue), SW (orange), WEST (magenta), and NORTH (red). The solid-white shapes are source regions, while the dashed-white shapes are background regions in each FoV. The white and black numbers in the SW region represent SW-A and SW-B regions, as shown in the main text. Table 1 Suzaku Observations of RCW 86 The XIS consists of four X-ray CCD cameras, which observe in 0.2–12.0 keV with X-ray telescopes (XRT: Serlemitsos et al. 2007 ). Three of them (XIS 0, 2, and 3) are front-illuminated (FI) CCDs, and the other (XIS 1) is a back-illuminated (BI) CCD. The FI CCDs have larger effective area in the hard X-ray band while the BI CCD is in the soft band. A pre-flight energy resolution is ∼130 eV (full width at half maximum, FWHM) at 5.9 keV (Koyama et al. 2007 ). After 2006 November 9, the XIS 2 was out of operation. The others (XIS 0, 1, and 3) use spaced-row charge injection (SCI: Nakajima et al. 2008 ; Uchiyama et al. 2009 ) to recover the charge transfer efficiency and improve the energy resolution after 2006 October. Each XRT accumulates X-rays with the effective area of 250 cm 2 at 8.0 keV to make an image over an FoV with angular resolutions of – in the half-power diameter. Thanks to the low-Earth orbit, the non-X-ray background (NXB) is fairly low and stable. Thus, Suzaku is very suitable for RCW 86, with its large extent and low surface brightness in some regions. We reprocessed the data using the xispi software and the recent calibration database released on 2012 May 9. The data were reduced in accordance with the standard screening criteria. 6 6 see ( http://heasarc.nasa.gov/docs/suzaku/processing/criteria_xis.html ). Grades 0, 2, 3, 4, and 6 events were used in the following analysis. We removed events during the South Atlantic Anomaly passages, Earth elevation angles below 5°, and Earth day-time elevation angles below 20°. We also
Paper: 2019MNRAS.487.5248L (fulltext)
could hinder follow-up observations. 6 CONCLUSION The ASKAP Early Science data set presented in this paper verifies that the array and its associated processing pipeline askapsoft – both in moderately preliminary states – are successfully producing scientifically useful data. Overall, within the 12-beam image cube centred on the NGC 7232 group, we detect 17 H i sources. Six of these detections are well-known H i -rich galaxies including one fully interacting pair. Five of these detection are newly resolved H i galaxies with identifiable stellar counterparts. The remaining six H i detections are likely tidal debris associated with the NGC 7232/3 triplet. The triplet is a complex system. The H i components of NGC 7232 and NGC 7233 appear to be fully intertwined. NGC 7232B still retains most of its gas but shows evidence that it is beginning to interact with the other two galaxies. H i clouds C5 and C6 are likely tidal clumps that have been produced by the triplet system and possibly indicate the projected spatial location of two tidally formed tails of H i . If H i cloud C6 is moving away from its parent galaxies, it has sufficient mass to eventually decouple from the tidal tail and possibly develop into a long-lived TDG. H i clouds C1–C4 might have been produced by the triplet system, or these clouds could indicate an earlier interaction event involving another group member, such as IC 5181. A portion of the H i within this region, which was originally identified as belonging to HIPASS J2214−45 is likely diffusely distributed and lies below the detection threshold of our current ASKAP observations. Accordingly, it is difficult to ascertain the origins of the H i bridge that appears to be connecting NGC 7232/3 and IC 5181. Future work would include adding short-spacing/single-dish observations to the ASKAP data in order to recover more of the diffuse gas in and around the tidal features, in order to further understand the interaction processes that are taking place. The high-resolution capabilities of ASKAP produced moderately well-resolved moment maps of four galaxies (i.e. IC 5171, ESO 288−G049, ESO 298−G010, and ESO 289−G011) that can be used for further kinematic analysis. The newly detected H i counterparts of five stellar galaxies indicate their membership to the group. These nine galaxies provide a more complete picture of the group environment surrounding the NGC 7232/3 triplet. There are many areas where the data quality and processing procedure can be greatly improved for ASKAP. The addition of more antennas – to provide more complete sky coverage and achieve higher sensitivity with less integration time – along with the use of the on-dish calibration system and an overall improved observing method will show vast improvements to the data quality. With expanded computing systems and a more robust askapsoft pipeline, larger data sets can be processed more efficiently. The observations and results presented in this paper serve as one
Paper: 2016MNRAS.458L..74L (acknowledgments)
We acknowledge financial contribution from the agreement ASI-INAF I/037/12/0. NLP and LS acknowledge the grant from PRIN-INAF 2014 ‘Towards a unified picture of accretion in HMXRBs’.
Paper: 2019MNRAS.483.2547R (fulltext)
(Shu, Adams Susana 1987 ) do not also play a role in bringing ε SF down. We note, however, that if clouds form stars preferentially in one short burst with ε SF ≈ ε min , this presents a challenge to the survivability of these star clusters because star clusters with ε SF ≲ 10 per cent tend to dissolve after the natal gas has been removed (Baumgardt Kroupa 2007 ; Shukirgaliyev et al. 2017 ). We speculate that studies of star clusters with N -body simulations that include a centrally peaked star formation profile as in the model by Parmentier Pfalzner ( 2013 ) together with slow gas removal with velocities of approximately 10 km s −1 as predicted by our warpfield2 simulations will result in a higher survival rate even for low star formation efficiencies. 4.3.1 Giant clumps Giant clumps at redshift ∼ 1−3 with gas masses of have typical surface densities of pc −2 and are consistent with isothermal spheres, i.e. α = −2 (Ceverino et al. 2012 ). In this paper we probe the lower mass end of such clumps. Our results indicate that they are more resilient against destruction by stellar feedback than clouds with shallower density profiles. As noted above, this is due to the larger binding energy of the giant clump and in particular of the inner region when α = −2 (see equation 28 ). As more of the gas mass is accumulated in the inner regions, an expanding shell in a cloud with such a steep density profile decelerates faster, making it more susceptible to energy loss via leakage of hot gas after gravitational fragmentation and via strong cooling. Our results indicate that giant clumps at the low-mass end () can be destroyed by a single starburst with ε SF ≥ 4 per cent for pc −2 ( per cent for pc −2 ). Were the star formation spread out over the lifetime of the clump (∼30 Myr), this would correspond to ε ff = 0.5 per cent ( per cent for pc −2 ). This result is in line with simulations by Oklopčić et al. ( 2017 ) but puts analytic models by Krumholz Dekel ( 2010 ) into question who argue that star formation efficiencies per free-fall time of a few per cent are insufficient to disrupt a giant molecular clump (they focus on clumps with though). Our result does not yet take into account that the metallicity in galaxies at ∼ 2 is approximately a factor 2 lower than in present-day galaxies (Yuan, Kewley Richard 2012 ), which will affect the amount of radiative cooling, the strength of metal-line-driven winds of massive stars, and the coupling of radiation to the ISM. We plan to revisit giant clumps with warpfield in the future. 5 CONCLUSION In this paper we have presented improvements to the 1D stellar feedback code warpfield (Rahner et al. 2017 ). warpfield is a fast, publicly available code which models the formation of a shell around a massive cluster and how this shell is affected by stellar winds, radiation, and SNe, as well as gravity. The improvements which are part of a new code release, warpfield2 , include, but are not limited to, a better treatment of
Paper: 2016MNRAS.457.3241A (acknowledgments)
This work is based in part on observations from Spitzer Space Telescope and was supported by RSA 1415602 and RSA 1346842, issued by JPL/Caltech. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência, Tecnologia e Inovação (Brazil) and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina). This work is also partially based on observations made with ESO-NTT Telescope at the La Silla under programme ID 184.D-1140 (PI Benetti). We would like to thank the anonymous referee for their insightful comments during the revision of this paper.
Paper: 2016ApJ...826...85S (acknowledgments)
We thank Roger Griffin for radial-velocity monitoring and calculation of the orbital elements for HIP 99725. We acknowledge support from the Research Council of the Lithuania under grant No. MIP-85/2012, from the Latvian Council of Science under grant No. 09.6190, and from the Universidad Nacional Autónoma de México by way of project IN103014 of the PAPIIT/DGAPA. This research has made use of the Simbad database operated at CDS, Strasbourg, France. We greatly thank the referee for his constructive and valuable discussions and comments which have improved this paper.
Paper: 2020MNRAS.493.2127M (fulltext)
smaller than the symbols. Right: Similar to the left panel, but showing the distribution of . All spectra were visually inspected for the presence of Ca ii triplet emission. The spread in EW values is extremely large at low S/N values due to noise (compare the left and right panels of Fig. 3 ), but rapidly tightens as the S/N increases, making it trivial to identify genuine emission features such as SDSS J1228+1040. Closer to the bulk EW distribution, it becomes difficult to detect Ca ii triplet emission such as that of SDSS J0738+1835 and SDSS J1043+0855 (see Fig. A1 for the EW values). We therefore chose to limit the sample used for the following statistical analysis to spectra with S/N ≥ 5, wherein if there were any additional emission features with an EW similar to the gaseous debris discs in our sample we should have detected them. Assuming that we can only detect gaseous emission in the spectra of systems above S/N = 5, the number of white dwarfs in our sample reduces to 7705, which we use for the calculations in the next section. 2.1 The occurrence rate of gaseous discs at white dwarfs We find no new gaseous discs in our magnitude and S/N limited Gaia /SDSS sample, resulting in a total of five detected gaseous components to debris discs out of 7705 systems. Using Bayes’ theorem we calculate the probability distribution, p ( f | n, t ), of an occurrence rate, f , of a gaseous debris disc at a white dwarf, given n detections out of t systems as where p ( n | f, t ) = f n (1 − f ) t − n is the binomial distribution, p ( f ) is the prior distribution of f , and p ( n, t ) is the probability distribution of detecting n gaseous disc hosts out of t systems which is a constant. We assume an uninformative prior distribution known as the Jeffreys prior (Jeffreys 1946 ), which for the binomial distribution is where B is the beta function. Substituting this prior into equation ( 1 ) results in Taking the median and 1σ intervals of this probability distribution (which is independent of the proportionality constant) with n = 5, and t = 7705, we find that 0.067 ± per cent of white dwarfs host a debris disc with a detectable gaseous component (Fig. 4A ). This is significantly lower than the occurrence rate of detectable dust discs around white dwarfs, which has been estimated by various studies to be 1–3 per cent (Farihi et al. 2009 ; Girven et al. 2011 ; Rocchetto et al. 2015 ; Rebassa-Mansergas et al. 2019 ; Wilson et al. 2019 ). For further discussion, we adopt the estimate of Wilson et al. ( 2019 ), 1.5 ± per cent, calculated using an unbiased sample of 195 white dwarfs observed with Spitzer containing three dusty debris discs. We note, however, that using equation ( 3 ) with n = 3 and t = 195, we obtain a slightly different occurrence rate of 1.6 ± per cent, and the probability distribution of this occurrence rate is shown in Fig. 4(B) . These two occurrence rates of dusty debris discs at white dwarfs are in agreement, and the difference results
Paper: 2016MNRAS.462.3570S (fulltext)
of any model for distributions of the properties of the clouds in the BLR. In fact, in the current analysis, our only constraint is to suppose that all the hydrogen lines are emitted from the same clouds with certain density and excitation conditions, which is a reasonable assumption considering the similarity of the profile of the various H i lines we analysed for each object. Additionally, if more than one grid point is a good match to the data, we adopt a simple weighting scheme where we calculate median Φ H , n H and line ratios from these point. A detailed description of our photoionization modelling scheme is given in Section 3.3 . 3.3 Extinction measurements The extinction affecting a set of line ratios may be determined by comparing the measured ratios with their theoretically predicted intrinsic values. In the case of the He ii lines, considering the He ii λ4686/He ii λ10 126.4 line ratio is expected to be similar to the case B prediction even in the BLR spectrum (Bottorff et al. 2002 ), we estimate the extinction to both the NLR and BLR assuming an intrinsic He ii λ4686/He ii λ10 126.4 line ratio of 3.77, corresponding to the case B prediction for a temperature of 10 000 K and a density of 10 6 cm −3 . If broad He ii λ4686 Å is not observed, we estimate a lower limit to A V (BLR) based on the broad He ii λ10 126.4 Å flux. This was done decreasing the observed broad He ii λ4686/He ii λ10 126.4 ratio in steps of 0.1, starting from the intrinsic value of 3.77, until the broad He ii λ4686 Å line becomes indistinguishable from the continuum. The lower limit to the extinction is then derived from this ratio. In Table 2 , we list A V (NLR) and A V (BLR) as estimated from the He ii lines for each object. The errors in these estimates were derived assuming an uncertainty of 20 per cent in the observed line ratios. Table 2. Extinction to the narrow-line region, A V (NLR), and extinction to the broad-line region, A V (BLR), derived from Balmer and Paschen H i line ratios and the He ii λ4686/He ii λ10 126.4 line ratio as described in Section 3.3 . In objects where broad He ii λ4686 is not detected, a lower limit to A V (BLR) was determined from broad He ii λ10 126.4 Å. These lower limits are marked with an asterisk. Abbreviated name: MCG–05-14-012, MCG–05-23-16 and MCG–06-30-015. In the case of the H i lines, determining A V (NLR), is a straightforward process since, as outlined in Section 3.1.3 , a fixed set of intrinsic line ratios can be assumed. Deriving the extinction A V ( NLR ) to the NLR was done during the step of fitting and subtracting the narrow lines as described in that section. In Table 2 , we list A V (NLR) as estimated from the H i lines for each object. The errors in A V estimates were derived assuming an uncertainty of 20 per cent in the observed line ratios. The extinction to the BLR is derived in a different way, since the H i intrinsic line ratios are not known. To do so, we followed these steps. We compared the
Paper: 2016MNRAS.461L.112T (acknowledgments)
TT is grateful to K. Nitadori and J. Makino for the tuning of our code. The computations in this research were performed on the K computer of the RIKEN AICS through the HPCI System Research project (Project ID:hp120304) together with XC30 of CfCA in NAOJ. YS was supported by JSPS postdoctoral fellowships for research abroad. This study was supported in part by the Grants-in-Aid for the Scientific Research from the Ministry of Education, Science and Culture of Japan (Nos. 24103006, 24244036, 26104001, 26707013, 26870823, 15H01039 and 15H00789) and by HPCI Strategic Program of Japanese MEXT.