adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018MNRAS.474.2580S (fulltext)
that are not perfectly linear too. As a consequence, the linear fittings tend to overestimate the ages of stars younger than 3 Gyr by 0.8–0.9 Gyr. By fitting the distributions of thin and thick discs with quadratic functions, we found the following solutions: From these higher order functions, we find that the average scatter is reduced to 0.5 Gyr for both [Y/Mg] and [Y/Al], which is very close to the typical uncertainties of our age determinations (i.e. 0.4 Gyr). 4 CONCLUSIONS We used high-quality HARPS spectra of 79 solar twins to obtain precise estimates of their atmospheric parameters (T eff , log g , [Fe/H] and ξ) and abundances of 12 neutron-capture elements (Sr, Y, Zr, Ba, La, Ce, Pr, Nd, Sm, Eu, Gd and Dy). The knowledge of the stellar parameters and absolute magnitudes of these stars allowed us to determine their stellar ages through the isochrone method with typical precisions of 0.4 Gyr. Our main scientific results can be summarized as follows: The thin and thick disc populations, identified through the α-elements abundances, are separated in the [X/Fe] versus age plots showed in Fig. 5 . The [X/Fe] ratios of the thin disc distribution are highly correlated with stellar age for the s -process elements (e.g. Ba), while the [X/Fe]–age distributions of the r -process elements (e.g. Eu) are nearly flat. Indeed, the slopes of the [X/Fe]–age distributions are dependent on the s -process contribution percentage of the X element (see Fig. 6 ). This indicates that, the enrichment from AGB stars is the predominant channel of nucleosynthesis of n -capture elements during the evolution of the thin disc. Despite the flat slopes traced by the thin disc stars, the nearly pure r -process elements Eu, Gd and Dy appear more enhanced in the thick disc population. This dichotomy between the thin and thick discs resembles the [X/Fe]–age distributions outlined by the α-elements, which are more abundant in the thick disc than in the thin disc due to an intensive nucleosynthesis by Type II SNe during the early stages of the Galactic disc. The sites of production of the r -process elements are not very well known at present; however it is likely that they are mainly synthesized during the mergers of massive compact objects. On the other hand, the similarity to the distributions of the α-elements suggests that the r -process elements are also produced by Type II SNe and that they could be additional tracers of intensive star formation episodes. There is a possible direct observational test that could be performed on OB associations which are regarded as a proto-type of triggered star formation, such as Orion or Sco-Cen. If Type II SNe are producing copious r -process elements, then the youngest sub-clusters should be enriched in these elements relative to the oldest stars (Cunha Lambert 1992 ). The [X/Fe]–age distributions of the thin disc stars have been fitted by linear functions. The parameters resulting from this linear fitting, listed in Table 5 ,
Paper: 2020A&A...644A.113J (fulltext)
datasets with Gammapy by generating random count maps from a Poisson distribution taking into account the expected residual hadronic background and the physical model. The expected γ -ray profile alongthe Galactic longitude from those simulations for H.E.S.S and CTA is represented in Fig. 4 in two energy bands: 0.5–5 TeV and 5–100 TeV. We can see the variation of the profile morphology in the two energy bands for H.E.S.S. and CTA simulations, but it appears that the statistical errors with H.E.S.S. at high energy are too high to enable us to distinguish any variation between the low- and high-energy profiles (see Fig. 4 a). On the other hand, this simulation clearly demonstrates that CTA will be able to measure such a morphology variation with energy thanks to the SST and the strong increase of the statistic in the high-energy range ( Fig. 4 b). In the near future, CTA observations will therefore establish a clear constraint on the origin of this VHE diffuse emission and on the CR acceleration mechanism in the CMZ. Fig. 4 Expected γ -ray profile along the Galactic longitude from the simulation of 100 GC datasets of 250 h between 0.5–5 TeV (blue) and 5–100 TeV (orange). On the top those profiles are simulated using H.E.S.S. IRFs and on the bottom using CTA IRFs (version prod3b-v2, http://www.cta-observatory.org/science/cta-performance/ ). The solid lines represent the median of the 100 simulated datasets and the colored region the dispersion around the median. The dispersion contains 50% of the realizations in each longitude bin independently. 5 Conclusions Supernova remnants are natural candidates for Galactic CR acceleration. With a 3D model of CR injection and propagation in the GC, we already showed that the SNe alone can reproduce the total VHE γ -ray flux of the diffuse emission, by considering typical values for the SN rate, the diffusion coefficient, the total mass of the matter in the region, and a low CR acceleration efficiency of approximately 2% ( Jouvin et al. 2017 ). Besides, we showed that SNRs, concentrated at the position of the massive stellar clusters, the Quintuplet, and the central disk, creates a pronounced CR gradient but can only marginally reproduce the data obtained by the H.E.S.S. Collaboration in the inner 30 pc ( Abramowski et al. 2016 ; H.E.S.S. Collaboration 2018a ). Yet, we considered only a burst-like injection in which all the CRs are emitted at the same time in the ISM independently of their energy. The deceleration of the shock wave in the adiabatic phase of the SNR evolution leads to a progressive energy-dependent CR escape in the surrounding medium. To add this more realistic time-energy-dependent escape from the SNR, we followed thework of Gabici et al. (2009) who assume that the time dependency of the proton energy loss in this phase follows a power law. With this approach, the low-energy CRs remain confined a longer time in the remnant than the high energy CRs. At lower energies, the CRs do not
Paper: 2016A&A...586A..97B (fulltext)
forcing a normalized wavelength of 500 nm everywhere, except when we set a wavelength threshold, in which case we force a normalized Landé factor equal to 1.2. Finally, we correct for any difference in the depth of Stokes profiles, except when the submasks are defined with a line depth threshold. 4.3.2. Outcome for <inline-formula specific-use="simple-math"><italic>β</italic></inline-formula> UMa and <inline-formula specific-use="simple-math"><italic>θ</italic></inline-formula> Leo As a first test, we ran LSD for two submasks containing lines with an average Landé factor lower (resp. greater) than the mean Landé factor of the original line list (see Table B.1 ). Hereafter, we consider the normalizing Landé factors used as part of the LSD procedure, since it is the relevant quantity for direct comparison of different LSD profiles. (The normalizing values follow the same trend as the average Landé factors of the submasks.) The resulting Stokes profiles are plotted in Fig. 2 for the two Am stars and the control Ap star. The Stokes profiles are corrected for a 10% difference in equivalent width observed in their associated Stokes profile. Because of a higher noise level than obtained with the complete line mask, the high- and low- profiles of UMa and Leo do not display any statistically conclusive differences. The overplotted running average helps to improve the situation, showing that the high- signals possess higher amplitudes than their low- counterparts. We note that their amplitude ratio is roughly consistent with the ratio, although this point is difficult to establish with high accuracy (even with the running average) because of the level of noise. Fig. 2 Top : comparison of the Stokes profiles obtained by selecting photospheric lines of low (red thin line) and high (green thin line) magnetic sensitivity for UMa. The thick red and green lines represent a moving average over three spectral bins of the thin lines. Center : same figure for Leo. Bottom : same for CVn. All profiles are normalized to the continuum level. As second test, two sublists were defined from our original list by containing lines with a wavelength lower (resp. greater) than the mean wavelength of the original list (Table B.1 ). For a given star, the Stokes profiles were corrected for the 30% difference in equivalent width observed in their associated Stokes profiles. The outcome of this test is illustrated in Fig. 3 , which illustrates a marginally larger amplitude of the Stokes signal when the wavelength increases. As for the previous test, we computed a moving average of the signal to confirm the trend that is otherwise completely hidden in the noise and to check that the trend observed in both Am stars is consistent with the outcome obtained for 2 CVn. Fig. 3 Same as Fig. 2 for photospheric lines of low (thin blue line) and high (thin red line) wavelength. Fig. 4 Same as Fig. 2 for photospheric lines of low (thin red line) and high (thin green line) central
Paper: 2019A&A...627A.126S (fulltext)
this model may not represent the true morphology, but may vary on smaller angular scales, the intensity scaling parameters per energy bin, , are re-determined for each sky region and the background. The celestial emission in this energy range is dominated by the bright 511 keV line emission from the Galaxy’s centre, modelled by a narrow bulge, a broad bulge, and a point-like source centred at ( l ∕ b ) = (0°∕0°). To this, a Gaussian-shaped disk is added to capture the faint and low surface-brightness emission beyond the bulge. The details of the spatial emission models are found in Siegert et al. (2016) , and in Appendix E . The instrumental background is modelled in a self-consistent way, using long-term knowledge about the detector behaviours, space-craft conditions, and physical origins of γ -ray emissions in the satellite ( Siegert et al. 2016 ). Based on the INTEGRAL/SPI BackGround and Reponse Data Base (BGRDB, Diehl et al. 2018 ), the background detector patterns (relative counts of the detectors to each other) are predicted as a function of energy and time. This data base includes spectral information of hundreds of instrumental γ -ray lines which are associated to different isotopes in the satellite, being excited by cosmic rays and de-exciting either promptly or delayed. The continuum background, mainly due to bremsstrahlung inside the spacecraft, is modelled in the same manner. Long-term trends of detector degradation from this cosmic-ray bombardment and radioactive build-ups are individually traced by this technique. In this energy range, eight instrumental γ -ray lines, on top of a power-law shaped instrumental continuum is used to model these background patterns ( Siegert 2017 ), to be distinguished from the expected sky emission patterns. The background scaling parameters are determined on a three-day interval (see also Siegert et al. 2019 ), corresponding to one INTEGRAL orbit. This amounts to 1083 background scaling parameters for each, the continuum and line backgrounds as a whole, for a total of 2166 background parameters. In summary, 6 (2) parameters are fitted for the celestial emission in a simultaneous (consecutive) fit of the regions of interest and the remaining Galaxy, and 2166 parameters for the instrumental background. The number of degrees of freedom in each individual energy bin thus amounts to 1 212 627 (1 212 631). 2.2 Spectral extraction 2.2.1 Full sky 511 keV signal The total spectrum of the 511 keV template map ( Fig. 2 , top two panels) is shown in Fig. 1 , together with a multi-component fit. We identify four spectral components: a narrow and a broad 511 keV line, an ortho-positronium (o-Ps) continuum, and the galactic diffuse γ -ray continuum. The derived spectral parameters are consistent with previous studies, although both, the broad and the narrow annihilation line, appear to be broader than previously measured ( Jean et al. 2006 ). This may arise from different line shapes in the disk and the bulge
Paper: 2019ApJ...871...62G (fulltext)
SNe Ia are monitored only for a few months; if CSM is more prevalent or typically at a larger distance from the WD, we might be systematically missing the signatures of this interaction. There are additional good reasons to suspect that we might be systematically missing the interaction of CSM with SN Ia ejecta. For example, SN Ia 2006X exhibited evolution in its Na i D absorption line that was interpreted as the photoionization of more distant CSM (Patat et al. 2007 ). In a compilation of 17 SNe Ia with multi-epoch spectra, Sternberg et al. ( 2014 ) found that ∼18% exhibit time-variable Na i D. Additionally, studies of large samples of SNe Ia (20–35 events) found Na i D to be blueshifted ∼20% more often than redshifted, and argued that this was best explained by outflowing CSM from the progenitor system (Sternberg et al. 2011 ; Maguire et al. 2013b ), but see Bulla et al. ( 2018 ) for an alternative explanation. In these SNe Ia, the CSM is estimated to be 5 × 10 16 –10 18 cm away from the explosion, which means that the fastest SN ejecta would not interact until >1 yr. Additional support for late-time CSM interaction is presented by Fox Filippenko ( 2013 ), who interpreted an increase in Spitzer mid-infrared photometry for SN Ia 2005gj at 500–1000 days past peak brightness as dust heated by hot blackbody emission from new or renewed CSM interaction. Additional evidence for nondegenerate companion stars comes from detections of, e.g., “blue bumps” in the light curve in the week after explosion (Hosseinzadeh et al. 2017 ) and/or late-time H α emission from material swept off the companion star and embedded in the ejecta (Maguire et al. 2016 ; Sand et al. 2018 ). It is important to note that there is plenty of evidence that many—or even most—SN Ia progenitor systems host a degenerate binary companion and/or do not contain CSM (e.g., Hayden et al. 2010 ; Maoz et al. 2014 ; Chomiuk et al. 2016 ). In this work, we aim to put upper limits on the fraction of SNe Ia with CSM, and we are not suggesting that the systematic oversight of CSM interaction extends to all SNe Ia. There is further motivational support in searching for late-onset CSM interaction in SNe Ia from recent observations of delayed CSM interaction in some core-collapse SNe. For example, Milisavljevic et al. ( 2015 ) presented observations of SN 2014C, an SN Ib that appeared to explode into an empty cavity surrounded by CSM, which transitioned to an SN IIn as the ejecta caught up with the previously released material. Similarly, Mauerhan et al. ( 2018 ) found H α emission from the onset of CSM interaction in SN Ib 2004dk 13 years after the original explosion. Vinko et al. ( 2017 ) presented the results of a systematic narrow-band imaging survey of Type Ibc, IIb, and Ia SNe to look for H α emission due to CSM interaction years to decades after explosion. Most of their potential detections are associated with core-collapse events, but of particular relevance to this work is their
Paper: 2016A&A...585A..61A (fulltext)
excitation temperatures) owing to atmospheric transmission and telluric lines, and would limit the detections to some energetic rotational transitions such as the 12.4 m blend observed in Pontoppidan et al. (2010a) . 5. Conclusions From the outcome of our model, we have provided a scenario that can explain the observations in the mid-IR towards a Herbig star: we considered some limitations in our description of disks around Herbig stars, and we think that these would not be problematic for the correct physical description of the mid-IR spectroscopy. Observations have been performed up to now with facilities affected by low spectral resolution and lower sensitivity. These two elements limit any possible firm conclusion about the nature of disks around Herbig stars, which can be intrinsically different from the ones surrounding T Tauri stars. Low signal-to-noise ratio (S/N) is the most likely explanation for the low detection rates of mid-IR water lines around early type PMSs. This problem also partially affects later type PMSs. T Tauri stars spectra are less noisy; however, mid-IR water line fluxes are lower, and the detection rate is only a factor two more than for Herbig stars. Better performing instruments with resolution 3000 and longer integration times are definitively needed to detect water successfully in the 1–20 m range in protoplanetary disks. Appendix A: Sensitivity limits Our analysis sample includes a selection of T Tauri and Herbig Spitzer IRS high resolution observations. BCD data products were retrieved from the Spitzer archive 4 . The data were reduced with the c2d IRS science pipeline using the PSF extraction method (see Lahuis et al. 2007 ; Lahuis 2007 , for details), which provides higher S/N spectra than the standard tapered aperture extraction used to populate the Spitzer archive. After extraction, additional defringing ( Lahuis Boogert 2003 ) was applied to remove any low-level fringe residuals. Sensitivity limits were determined by calculating the line flux for synthetic lines with an amplitude equivalent to the 1 noise level in the IRS spectrum at the respective blend wavelengths and a width comparable to the blend width at a spectral resolution of 600. Appendix B: Spectral convolution We applied Gaussian convolution and rebinning to the theoretical spectra from our models. For this task we used the ISO spectral analysis package ( Kessler et al. 1996 ), considering the three resolutions of Spitzer IRS LH/SH modules (; Houck et al. 2004 ), VLT VISIR (; Lagage et al. 2000 ). For JWST MIRI we split the range into four spectral windows: for 7.63–11.71 m, for 11.71–13.59 m, for 13.59–18.14 m, for 18.14–28.43 m, accounting for the variable spectral resolution ( Clampin 2011 ). We add noise through a random generator according to \newpage where is the computed noise and a function both of the continuum flux () multiplied for a random generator between 0 and 1 () and of the selected S/N. Here we consider 100 as claimed in
Paper: 2018MNRAS.475.3453S (fulltext)
based on the Lick indices and the abundance ratios. In Section 4 , our results are summarized and discussed. In Section 5 , conclusions are given. 2 OBSERVATIONS AND DATA REDUCTION Our sample consists of 37 galaxies, the full spectroscopic sample of the SMAKCED project. For each of them, we obtained data suitable for a detailed stellar population study, with relatively high spectral resolution and high S/N ratio. Two galaxies in the sample (VCC1684 and VCC2083) were not included, since no ages could be determined because of lack of observed Balmer lines. The spectroscopic data were obtained at three different telescopes. A total of 26 dEs were observed at the 4.2-m William Herschel Telescope (WHT) using the double-arm ISIS spectrograph, of which the blue-arm covered the wavelength range 4200–5000 Å and the red-arm covered the wavelength range 5500–6700 Å. A total of 10 dEs were observed at the 2.5-m Isaac-Newton Telescope (INT), using the IDS spectrograph covering the wavelength range 4600–5600 Å, whereas the remaining three dEs were observed at the 8-m Very Large Telescope (VLT), using the FORS2 spectrograph that covers the wavelength range 4500–5600 Å. Table 1 summarizes the main properties of these 37 dEs (see also T14 ). Table 1. Properties of the SMAKCED dEs. Column 1: galaxy name. Columns 2 and 3: right ascension and declination in J2000, respectively. Columns 4 and 5: r -band magnitude (in the AB system) and half-light radius by Janz Lisker ( 2008 , 2009 ), respectively. Column 6: velocity dispersion. The data were reduced following the standard procedure for long-slit spectra using the package reduceme (Cardiel 1999 ). Details on sample selection, observations, and data reduction are presented in T14 . 2.1 Line-strength measurements Observed spectral data can be studied either by fitting the full spectrum or by focusing on selected line indices. In this work, we study selected line indices. We measured Lick indices (Worthey et al. 1994 ) in the Line Index System (LIS)-5 Å flux calibrated system (Vazdekis et al. 2010 ). The new LIS has numerous advantages over the Lick system. It is defined at three different resolutions, namely 5.0 Å, 8.4 Å, and 14.0 Å. As such, it is particularly useful for analysing small galaxies and globular clusters. As the resolution of the Lick/IDS library (FWHM ∼ 8–11 Å) is much lower than what is available with our high resolution spectra, we broadened the spectra to the LIS-5 Å system. The LIS-5 Å system choice expresses a factor of 2 improvement in resolution over Lick/IDS system. Also, the fact that the LIS system is flux calibrated makes it easier to reproduce data from other authors. The spectra were broadened to the LIS-5 Å system, taking into account the velocity dispersion of the spectra. This ensures that every galaxy spectrum has the same spectral resolution, which is important and necessary to compare them with each other. We measured a total of 23 Lick indices (Faber et al. 1985 ; Gorgas et al.
Paper: 2019MNRAS.482..231L (fulltext)
correlations between the p -values for each formation channel provided in Table 1 and the half-mass relaxation time, t rh . Fig. 8 shows that there is no strong correlation between the p -values obtained for the mass-transfer channel and the cluster half-mass relaxation time. If such a correlation were present, 2 one interpretation would be that the initial BS velocity distribution immediately after formation is not Maxwellian, but instead evolves towards a dynamically relaxed state over a relaxation time. This would, in principle, be more consistent with the collisional hypothesis, since the binary mass-transfer hypothesis predicts that BSs descended directly from internal evolution within (relatively) old binaries that have had plenty of time to relax towards a Maxwellian velocity distribution. Thus, the results from this component of our analysis are most consistent with a mass-transfer origin for the majority of the BSs in our samples, since the observed BS velocity distributions are typically consistent with having formed from a dynamically relaxed population. However, as already discussed, this is insufficient to fully exclude the collisional channel, because collisions among the dynamically relaxed binary population would yield the same Maxwellian velocity distribution of the collision products in very relaxed clusters. As shown in Table 1 and Fig. 8 , the 2+2 collisional velocity distributions best match the observed BS velocity distributions for the post-core collapse GCs in our sample, namely NGC 6624, NGC 6681 and NGC 7099. The latter being our strongest candidate for having a large fraction of BSs formed via 2+2 collisions. This provides good independent evidence to support the claim of a strong contribution from collisions to BS formation in NGC 7099, as found by Ferraro et al. ( 2009 ). 4 SUMMARY AND DISCUSSION In this paper, we have performed a thorough statistics-based search to answer the question: What are the origins of BS stars in GCs? The BS catalogue of Simunovic Puzia ( 2016 ) provides us with observational measurements for BS velocities (from their proper motions) and masses (from isochrone-fitting and assuming they are single isolated objects). We compare these observed BS masses and velocities to analogous theoretical predictions for BSs formed from MS–MS collisions during single–binary (1+2) and binary–binary (2+2) interactions, obtained via a suite of numerical scattering experiments performed with the FEWBODY code (Fregeau et al. 2004 ). The results of this analysis are ultimately consistent with the BS samples having been derived from a dynamically relaxed population. At face value, this appears to favour the mass-transfer (and/or binary merger) hypothesis for BS formation. This is because the p -values obtained from Kolmogorov–Smirnov tests suggest that the observed BS velocity distributions most closely resemble Maxwellian velocity distributions, adjusted to account for the slightly higher masses of the