adsabs/WIESP2022-NER huggingface dataset:
Paper: 2021MNRAS.501.2724W (fulltext)
since the LC acts as a pin-hole, as well as due to their rareness. Single scattering, which leads to angular momentum change of ∼ j lc , is associated with impact parameter ∼( m * j cir / M bh j lc ) r . This impact parameter has to be ≳ R * , and in terms of r, m * , and M bh , strong scattering is relevant if This condition is easily satisfied for TDEs of main-sequence stars, and even for TDEs of red giants or binary break-ups, which leads to HVSs’ production, 3 it is satisfied for apoapsis distances r ∼ r h , which dominates the rate of TDEs and hyper velocity stars’ production. 6 SUMMERY AND DISCUSSION In this work, we have discussed the statistical properties of the pre-TDE dynamics and its correlations with the properties of the TDEs. In general, empty LC ( j d / j lc ≪ 1) is associated with non-violent TDEs of disrupted stars, in which stars that have already experienced significant tidal interaction with the SMBH experience TDE with marginal periastron (β − 1 ∼ j d / j lc ≪ 1). Similarly, full LC is associated with violent TDEs of non-disrupted stars. As for minority populations, different behaviour occurs for empty LC and full LC while considering single value of j d / j lc . In empty LC, a significant fraction () of the TDEs are non-typical being violent and involve mostly non-disrupted stars. This population of TDEs relates to the logarithmic fraction of stars that have been scattered into the LC by single large scatterings rather than by a large number of small scatterings. In the case of full LC, the fraction of non-violent TDEs of disrupted stars drops to zero for j d / j lc ≳ 0.3. However, significant minority population does arise for full LC, while assuming realistic j d / j lc distribution that arises due to the apoapsis distribution of the stars in the galaxy (Section 4 ). In this case, stars in orbits of marginal LC dominate the rate of TDEs, and as a result even if the LC is extremely full at the radius of influence [ j d, h = j d ( r h ) ≫ j lc ], an asymptotic fraction of of the TDEs involve stars in empty LC. Therefore, for any value of j d, h , at least a significant fraction () of the events are non-typical. Finally, in Section 5 , we discuss the value of j d, h / j lc in realistic astrophysical systems and find it to be ≫1 for red giants and for main-sequence stars. The physical consequences of previous interactions with the SMBH were not in the focus of the current work, and therefore are only briefly presented in the current section. For red giants, the role of previous interactions was already presented by MacLeod et al. ( 2013 ). According to this model, due to their inflated structure, red giants tend to ‘graze’ the LC, loose small amount of mass in each passage, and get back to equilibrium as an object of lower mass. This picture gives rise to ‘spoon feeding’ TDE instead of the violent typical TDE. This picture agrees perfectly with our expectation that most of the TDEs of red giants are expected to be
Paper: 2019ApJ...872....7R (fulltext)
review by Somerville Davé 2015 ). At z ∼ 5–7, the excess of bright sources compared to the semi-analytical predictions appears to be even more pronounced than at lower redshifts but we caution that the most constraining measurement is based on a small number of sources only, and thus needs to be put on a firmer statistical footing. Meanwhile, the observations at z ∼ 2–3 appear to be consistent with Vallini et al.’s ( 2016 ) empirical predictions, and thus with what is expected from estimates of dust-obscured star formation activity at high redshift based on infrared luminosity functions. 4.2.2. Cold Gas Density of the Universe The observational constraints on the evolution of the cold gas density with redshift remain in agreement with both semi-analytical (Obreschkow et al. 2009 ; Lagos et al. 2011 , 2012 ; Popping et al. 2014a , 2014b ) and empirical (Sargent et al. 2012 , 2014 ) model predictions at z ∼ 2–3. Since most of the semi-analytical models include a varying α CO between individual galaxies, a simple interpretation of the consistency—despite the disagreement in the luminosity function estimates—remains challenging. In addition, the predictions do not account for the sensitivity limits of the CO surveys, or uncertainties due to cosmic variance. Given the differences in the CO luminosity functions between models and observations at high z , this effect could in principle lead to up to a factor of a few difference in the corresponding gas densities at high redshift. However, as discussed in Section 3.4 , the impact of the sensitivity limits, which would bias the measurements toward lower values, appears to be relatively minor based on the preferred model Schechter function fits to the COLDz data. Meanwhile, cosmic variance due to large-scale structure in the distribution of gas-rich galaxies (which is assumed to be uniform in our analysis) could bias the measurements either low or high. To obtain an approximate estimate of systematic uncertainties introduced by cosmic variance, we follow the prescription by Driver Robotham ( 2010 ), based on the distribution of galaxies near the characteristic stellar mass at a given redshift. 40 40 This method is based on a generalized expression (their Equation (4)) calibrated through an examination of galaxies within ±1 mag of the characteristic optical magnitude out to z ∼ 0.1 in the Sloan Digital Sky Survey (SDSS), which represent the most common galaxies at a given redshift. See cosmocalc.icrar.org for additional details. The field sizes and CO( J = 1 → 0) redshift ranges in Table 1 are used for all calculations. Including both Poisson uncertainty and cosmic variance scaled to the volume of the COLDz survey, we find a sample variance uncertainty of ∼30%–40% and ∼25% for the COSMOS and GOODS-North fields, respectively. Alternatively, adapting results based on models of the evolution of the most massive galaxies (i.e., M ⋆ > 10 11 M ⊙ ) by Moster et al. ( 2011 ) 41 41 For our estimate, we have made
Paper: 2016MNRAS.456..731S (acknowledgments)
We thank Don Melrose for introducing us to key references in the quantum plasma literature, notably including BM07 . We also thank Bryn Haskell, the first reviewer Taner Akgün, and the anonymous second reviewer for their insightful comments, which have significantly improved the quality and clarity of this paper. This work was supported by an Australian Research Council Discovery Project Grant (DP110103347) and an Australian Postgraduate Award.
Paper: 2018MNRAS.481L.141K (acknowledgments)
ACKNOWLEDGEMENTS The authors thank Lars Bildsten, Jared Brooks, Sterl Phinney, Evan Kirby, Selma de Mink, Thomas Tauris, and Onno Pols for useful discussion. IK is supported by the DOE NNSA Stockpile Stewardship Graduate Fellowship Program. This research is also funded in part by the Gordon and Betty Moore Foundation through Grant GBMF5076. DK is supported in part by a Department of Energy Office of Nuclear Physics Early Career Award, and by the Director, Office of Energy Research, Office of High Energy and Nuclear Physics, Divisions of Nuclear Physics, of theU.S. Department of Energy under Contract No. DE-AC02-05CH11231.
Paper: 2019ApJ...879L..12K (fulltext)
on the individual galaxies. We derived the source counts using a circular aperture with 13′′ radius, which, at a distance of 65 Mpc, corresponds to 4 kpc. To account for the background emission, we used annuli with 60′′–120′′ radii. We did not obtain statistically significant detections for any of the individual galaxies. To increase the signal-to-noise ratio, we co-added the X-ray emission associated with the individual galaxies. For the full sample of 51 LSBGs, this resulted in a total exposure time of 381.1 ks. We did not detect statistically significant emission from the stacked data, implying that the X-ray brightness of LSBGs remains below the detection threshold. We also stacked the subset of 17 UDG candidates and the 17 LSBGs as well as the subset of blue and red galaxies in our sample. We did not detect X-ray emission in any of the subsets. In the absence of detections, we set upper limits on the average luminosity of galaxies by calculating the confidence bounds of the stacked signal. We defined the 95% confidence region of the distribution, and used the upper confidence bound of the count rate as an upper limit. To convert the count rate to flux, we assumed that the emission from the hot gas can be described with an optically thin thermal plasma model. Specifically, we assumed a gas temperature of kT = 0.2 keV and a metallicity of 0.2 solar, which are typical in low-mass elliptical galaxies (e.g., Boroson et al. 2011 ; Goulding et al. 2016 ). Based on the resulting count rate upper limit of , we estimate the upper limit on the flux of for the full sample of 51 galaxies, which corresponds to a luminosity of , where d represents the average distance of the sample in Mpc. We obtained similar upper limits for the subset of UDG candidates and LSBGs and for the blue and red subsamples, which are listed in Table 1 . Table 1 X-Ray Upper Limits on the Stacked LSBGs 5. Discussion 5.1. Constraining the Halo Masses The prototypical UDG, Dragonfly 44, has a virial mass of (van Dokkum et al. 2016 , 2017 ). Using its effective radius of 4.6 kpc and assuming a Navarro–Frenk–White (NFW) dark-matter halo profile, we estimate that it has a total mass of . Based on the L X – M (5 r eff ) scaling relation, this total mass is linked with an X-ray luminosity of L 0.3–8 keV ≈ 2.4 × 10 39 erg s −1 in the 0.3–8 keV band. However, the luminosity upper limit measured for the sample of 51 field LSBGs, with an assumed distance of 65 Mpc, is in the 0.3–1.2 keV band. After converting the X-ray upper limit luminosity to the 0.3–8 keV band, we obtain . This value is ∼40 times lower than that expected for a galaxy with a massive dark-matter halo (see Figure 2 ). A similar conclusion is obtained for the subset of 17 UDG candidates and the subset of 17 LSBGs with 0.3–8 keV, as well as for the blue and red galaxy subsets. Figure 2. Empirical relation between the 0.3−8 keV band X-ray luminosity of hot diffuse gas and the total gravitating mass within 5 r eff (red
Paper: 2018MNRAS.480.1950K (acknowledgments)
ACKNOWLEDGEMENTS The authors thank the anonymous referee for useful comments which allowed them to improve the manuscript, Emmanuel Fonseca (on behalf of the NANOGrav collaboration) for providing probabilities of the Shapiro-delay parameters from the NANOGrav 9-yr data set and Maxim Voronkov for helpful discussions. The work of AVK and DAZ (Section 3 ) was supported by the Russian Foundation for Basic Research, project No. 18-32-00781 mol_a. AYuK and SVZ acknowledge PAPIIT grant IN-100617 for resources provided towards this research. The manuscript is based on observations made with the GTC, installed in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, in the island of La Palma. iraf is distributed by the National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. This research has made use of the USNOFS Image and Catalogue Archive operated by the United States Naval Observatory, Flagstaff Station ( http://www.nofs.navy.mil/data/fchpix/ ). 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 web site is www.sdss.org . The authors used WD colour tables available at http://www.astro.umontreal.ca/bergeron/CoolingModels .
Paper: 2019A&A...622A.109B (fulltext)
of the new fitting functions are shown in the second and fourth columns of Fig. 4 . In this case, the measurements of P θ θ are reproduced with a maximum systematic error of 3% on all scales below k = 0.7 h Mpc −1 , and for all redshifts and neutrino masses considered. We therefore use a total of only five free parameters k δ , b , a 1 , a 2 and a 3 to mimic, with a 3% level accuracy at k 0.7 h Mpc −1 , the nonlinear effects on both the auto- and cross-spectra P θ θ and P δ θ . Let us now focus on the sensitivity of these parameters to cosmology and specifically to the overall amplitude of the matter power spectrum. From our set of four simulations at four different redshifts we are able to span a large range of possible values of σ 8 , which we use as a proxy for the amount of nonlinearities. Regarding neutrino cosmologies it is necessary to choose whether we use the σ 8 defined for cold dark matter only, σ 8, c , or the one defined for the total matter, σ 8, m . It has been shown ( Castorina et al. 2015 ) that regarding the bias or the nonlinear effects on the density power spectrum P δ δ , what matters is the amplitude of the cold dark matter clustering and not the total one. We have analyzed the dependency of the fitted parameters with respect to both amplitudes σ 8, c and σ 8, m and we found that one should use the total matter σ 8, m parameter in order to assess the correct values of k δ , b , a 1 , a 2 and a 3 ; at least, this choice is the one that lowers the residual dependency with respect to the neutrino mass. Figure 5 shows that the cosmological dependance of the fitting parameters can be mostly encapsulated into the σ 8, m parameter evaluated at the corresponding redshift. The most relevant example is the good match at redshift 1.5 of the ΛCDM simulation with the M ν = 0.53eV simulation at redshift 1; these simulations share almost the same value of the total matter σ 8, m , while differing significantly in the power spectrum shape. For the two cases, we obtain the same values for the fitted parameters k δ and k θ . Fig. 5. Top panel : dependence of the fitting parameters k δ , b , k θ , a 1 , a 2 and a 3 on the total matter clustering amplitude σ 8,m at each redshift, in the corresponding simulation (symbols). Lines are showing the fit of the dependance. Bottom panel : residual between the fitted σ 8,m dependance and the measured one. On the contrary, when using the cold dark matter σ 8,c parameter (see Table 1 ) the residuals are increasing because of spurious neutrino mass dependence when going from one cosmology to another. This effect can be explained by the fact that if massive neutrinos have a weak effect on the dark matter clustering in the nonlinear regime, they add, instead, a relevant contribution to the velocity field which is felt by dark matter particles. As a result, it seems that the preferred dependence on the total matter σ 8,m comes from the fact that nonlinearities in the velocity field are generated by the
Paper: 2019MNRAS.488.3625N (acknowledgments)
ACKNOWLEDGEMENTS NN and EJ acknowledge financial support from the International Science Program (ISP). BB thanks the European Research Council (ERC Starting Grant 757448-PAMDORA) for their financial support.
Paper: 2021MNRAS.502..510J (fulltext)
(by ∼400 km s −1 ) than in Cano et al. ( 2018 ). Figure 9. Time evolution of the pEWs for features 1, 3, 4, 7, and 8 together with the Si ii expansion velocity evolution (bottom right panel). Black circles are the measured pEWs after lens- and host galaxy subtraction and de-reddening. Transparent points and shaded bands are individual measurements and the binned mean (±1σ) of low-redshift SNe from Folatelli et al. ( 2013 ), for all (red) and ‘Normal’ (blue) SNe Ia in their sample. The black and red dashed lines shows the pEW and velocity evolution of the Hsiao template and SN 2007le, respectively. Turning to the pEW measurements, we do not see any significant deviations from the time-evolution of SNe Ia in Folatelli et al. ( 2013 ). In Fig. 9 , the black points show the pEW measurements of iPTF16geu compared to all (red points) or ‘normal’ (blue points and blue shaded region) SNe Ia in Folatelli et al. ( 2013 ). However, we note that some measurements are outside the 1σ range, e.g. late-time pEW1 (likely due to improper lens and host galaxy removal), pEW3 and pEW7 (where the telluric corrections are imperfect). 5 TIME-DELAY MEASUREMENTS FROM SPECTRA OF SPATIALLY RESOLVED LENS IMAGES In our single epoch of HST spectroscopy, we can spatially resolve two spectra: one spectrum corresponding to Image 2 and one spectrum corresponding to Images 1, 3, and 4. However, Images 3 and 4 are subdominant, contributing with 7 per cent and 5 per cent to the total flux in F 814 W at this epoch, respectively. Hence, we will treat this spectrum as stemming from Image 1. By comparing the time evolution of spectral features between the spectra, we can in principle provide an independent measurement of the time delays between the SN images. However, in our case we are limited by the coarse ( R ∼ 210) spectral resolution. To complicate things further, at the epoch (+29 d) the Si ii absorption feature is no longer well-defined, displaying two or more local minima. Age dating of SN spectra is routinely done using cross-correlation techniques (e.g. snid ; Blondin Tonry 2007 ), and have been successful in measuring cosmic time-dilation (Blondin et al. 2008 ). We construct a simple χ 2 -statistic, fitting Hsiao template spectra (Hsiao et al. 2007 ) at different phases to the spectra of the spatially resolved SN images. This allows us to simultaneously fit for residual lens and host galaxy contamination using our template spectrum, and subtract a fraction of that flux (0.80 ± 0.03 and 0.19 ± 0.02 for Images 1 and 2, respectively) from the resolved SN spectra, so that the subtracted SN spectra and Hsiao templates at each phase match the host subtracted F 814 W photometry (see upper panel of Fig. 10 ). Figure 10. Top panel: HST spectra of the spatially resolved Images 1 + 3 + 4 (blue line) and Image 2 (green line). The summed spectra (red line) show very good agreement with the ground-based Keck spectrum (black line), observed at the same time. Bottom panel: χ 2 minima of
Paper: 2020A&A...642A..25F (fulltext)
star discovered by Caffau et al. (2011a ). The other symbols are literature data. The black and yellow dashed lines delimit the low-carbon band. Details can be found in Bonifacio et al. (2018) . 6.3 <italic>α</italic> and neutron-capture elements Figure 6 shows the abundance ratios of [Mg/Fe] and [Ca/Fe] as a function of [Fe/H] for our sample of stars using the solar abundances from Lodders et al. (2009) . Literature data from Roederer et al. (2014) are also shown, which contain results from a rather large sample of evolved and main sequence stars. We were able to measure magnesium in the five stars. Among them, SDSS J081554.26+472947.5 seems to have a rather low [Mg/Fe] abundance ratio and a subsolar [Ca/Fe] upper limit abundance. This is due to our high upper limit of [Fe/H]. In fact, by adopting the very low [Fe/H] determined by González Hernández et al. (2020) , we obtain [Mg/Fe] = 1.62 dex in excellent agreement with the [Mg/Fe] = 1.66 dex abundance that these latter authors obtained. The stellar parameters we adopted for SDSS J081554.26+472947.5 are close to those used by González Hernández et al. (2020) with a difference of 15 K on the temperature, a difference of 0.6 dex in log g that has no strong effect (typically 0.1 to 0.15 dex on the neutral Ca and Mg) on the determination of the abundance of neutral species, and the same micro-turbulent velocity. We found three stars with subsolar values for calcium, confirming the existence of stars with low [ α /Fe] ratios as already suggested by Bonifacio et al. (2018) . However, we reiterate the fact that in very metal-poor stars, under the LTE hypothesis, the resonance line that we used to determine the abundance of calcium leads to an underestimation of the calciumabundance ( Spite et al. 2012 , and references therein). For turnoff stars, the amplitude of the effect is rather small. Spite et al. (2012) computed a correction of the order of +0.1 dex in a turnoff star with [Fe/H] = −3.2 dex. Figure 7 shows the [Mg/Ca] ratio as a function [Fe/H] (upper panel) and as a function of [Mg/H] (lower panel). We have added the literature data from Roederer et al. (2014) for comparison. The [Mg/Ca] ratio found in our sample of stars ranges from +0.2 to +0.5 dex. This ratio is slightly higher than the abundance ratio found in the [Fe/H] range of –2 to –3 dex. At lower metallicities, the results from Roederer et al. (2014) show that the spread in the [Mg/Ca] ratio increases as [Fe/H] decreases with values ranging from negative abundance ratios to highly enhanced [Mg/Ca] ratios. From our measurements, the [Mg/Ca] ratio seems to increase as [Fe/H] decreases. The result for SDSS J081554.26+472947.5 found by González Hernández et al. (2020) seems to corroborate this point. The increase of the [Mg/Ca] ratio is also visible when the ratio is plotted as a function of [Mg/H]. However, a high value of [Mg/Ca] at very low [Mg/H] is not found in all the stars. In particular, SDSS J102915+17292, the normal
Paper: 2017A&A...606A..30S (acknowledgments)
The authors thank S. Gunar, B. Gelly, and the team of THEMIS for assisting with the observations. We would like to thank Jean-Marie Malherbe and Thierry Roudier whoco-aligned the SOT frames. They tested, up to now unsuccessfully, the CST and LCT methods to derive the flow pattern in the plane of the sky. We thank J. Dudik who provided the time-distance code to track the knots in the SOT cube of data, and G. Aulanier and P. Démoulin for fruitful discussions. This paper was discussed during the ISSI workshop (PI N. Labrosse) on “Solving the prominence paradox”. P.J.L. acknowledges support from an STFC Research Studentship. N.L. acknowledges support from STFC grant ST/I001808/1. Hinode is a Japanese mission developed and launched by ISAS/JAXA, with NAOJ as domestic partner and NASA and STFC (UK) as international partners. It is operated by these agencies in co-operation with ESA and NSC (Norway). IRIS is a NASA small explorer mission developed and operated by LMSAL with mission operations executed at NASA Ames Research Centre, and major contributions to downlink communications funded by the Norwegian Space Center (NSC, Norway) through an ESA PRODEX contract. The AIA data are provided courtesy of NASA/ SDO and the AIA science team. M.Z. acknowledges support from the project RVO:67985815 of the Czech Academy of Sciences.