adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018A&A...620L..12V (fulltext)
counter rotation was produced in the first place, the formation of retrograde accretion discs has also been proposed to explain the long-term evolution of spin periods in X-ray binaries ( Nelson et al. 1997 ; Christodoulou et al. 2017 ). However, for the time window 2010–2015 we can only speculate for the evolution of Ṁ due to lack of observational coverage and because of the high absorption of the X-ray spectrum (see Fig. 3 of C18). Nevertheless, the P and Ṗ measurements during the 2014 Chandra observation are consistent with the constant Ṁ assumption (see Fig. 3 ), supporting our finding that the decrease of the observed flux between 2010 and 2015 is only due to high absorption. If Ṁ during that period was two orders of magnitude lower than after 2015 then it is possible that there was no NS spin reversal. In this case the NS spin period should have been larger than a few hundred seconds prior to the SN 2010da event. In general there are multiple ways to maintain the necessary Ṁ to fuel ULXPs. For systems fueled by Roche Lobe (RL) overflow, the accretion flow carries the angular momentum of the orbit. It is therefore implausible for an accretion disc to switch between retrograde and prograde rotation ( Chakrabarty et al. 1997 ), and any change between retrograde and prograde rotation of the NS disc system needs to be due to a change in the direction of the NS rotation. Therefore, for NGC 300 ULX1 it is more plausible that the accretion mechanism was drastically altered during the SN 2010da event, prior to which the NS could have been fueled via wind accretion. A possible explanation for such a phase transition to occur can be an episode of thermal-timescale mass transfer ( King et al. 2001 ). In that case the donor star has a radiative envelope and fills its RL as it expands across the Hertzsprung gap after the wind-fed X-ray phase ends. However, RL overflow is not the only way to explain such high accretion rates. Supergiant systems and luminous blue variables (LBV) can also exhibit mass loss rates in excess of 10 −6 M ⊙ yr −1 ( Smith 2014 ), and therefore for a binary system in a moderately close orbit the compact object can capture enough matter to sustain super-Eddington accretion. An LBV is also most probable according to Binder et al. (2016) while other authors have deemed this classification inconclusive ( Lau et al. 2016 ; Villar et al. 2016 ). We note that many of the arguments used in the classification of the system were based on the decay of the X-ray flux observed after the SN 2010da event. However, the decay in the X-ray flux was most likely a result of rapid increase in X-ray absorption (C18). 4. Conclusions We have studied the spin period evolution of NGC 300 ULX1, the most extreme spin-up NS powered by an accretion disc. We derived precise measurements of P and Ṗ for different epochs, and applied theoretical models of accretion theory in order to estimate the magnetic field strength of the NS. Even though many of the models
Paper: 2018A&A...618A.118S (fulltext)
in Sect. 3.2 . We did not identify any significant gas contamination from other species in any of our spectra. Second, we selected the lines with intensities above a defined threshold (ten times the noise level). We summarize the results in Table 4 . We find that the number of U I lines differs considerably for different lamps (e.g. in the lamp 0127 we find a factor of 1.8 more lines than in the lamp 0120). The number of U II , Ne I, and Ne II lines is essentially constant. Table 4. Number of confirmed isolated U and Ne lines with S/N higher than ten found in the 12 U–Ne spectra for NIR wavelengths. The last column contains the average of the U line intensity normalized to the average of its line intensity in the 12 spectra ( I U ). We looked for the confirmed lines that can be found in all of the 12 spectra to systematically analyse the difference between the 12 lamps. In total, we detected 222 U I and 104 Ne I lines in the spectra of all lamps. We normalized the 12 spectra to the sum of the Ne lines intensities averaged in each spectrum. Then we divided the line intensity of each U line by the average line intensity of this line in the 12 spectra. Last, we calculated the average of the normalized line intensity of the 222 U I lines (named I U in Table 4 ) for each lamp. In Fig. 8 we plot the normalized line intensity of the common U I lines in the NIR spectral range for seven HCLs (for readability reasons). The dashed lines represent I U for each HCL. From Fig. 8 and Table 4 it can clearly be seen that I U varies significantly between the lamps. Lamps with the lowest U line intensities are HKH0120 and HKH0122. Lamps with the highest U line intensities are HKH0127 and HKH131. The maximum U line intensity difference is 88% (with respect to the minimum value), measured between lamps HKH0127 and HKH0120. Fig. 8. Coloured dots represent the normalized line intensity of 222 U I lines for each HCL in the spectral range from 1000 to 1700 nm. Dashed coloured lines indicate of each lamp (i.e. average of the 222 U I normalized line intensity). For readability reasons we plot only seven of the 12 HCLs. A possible explanation for the observed behaviour of the HCLs could be a different geometry of the lamps or in the light-fibre coupling efficiency, as seen in Huke et al. (2016) . This could affect the gas-metal intensity ratio. Another explanation could be that the metal line intensities are very sensitive to the internal pressure of the buffer gas ( Crosswhite et al. 1955 ). Therefore, even small changes in pressure from lamp to lamp would have an effect on the metal line intensity. We conclude that HCLs can show noticeable differences in number and intensity of metal lines even if they are manufactured in a single batch. 7. U line list We concluded in Sect. 4 that U cathode lamps are more suitable for wavelength calibrators than Th lamps from 500 to 1700 nm. To use HCLs as wavelength calibrators for high precision RV spectrographs, the wavelength of the
Paper: 2020MNRAS.495.1888M (fulltext)
We also find a large extinction of A V = 1.56 mag for this target. HD 38043, sectors 1–3, 5–6, 8–13 The TESS light curve spans 357 d and includes all sectors except 4 and 7. The data are at 2-min cadence in all available sectors. The p modes appear to be dominated by two nearly equally spaced multiplets: the first contains the strongest three modes – the same ones for which frequencies and amplitudes are provided in Table 1 – with a spacing of ∼0.51 d −1 . The second is slightly lower in frequency and amplitude and has a spacing of ∼0.55 d −1 . These could be rotationally split multiplets of modes with similar but non-identical n and l. This star is highly multiperiodic at lower frequencies, consistent with g-mode pulsation, though we could not identify any clear period spacings. HD 41958, sectors 1, 4–5. 7–8, 11 The three strongest p modes have similar amplitudes (7.5–8.2 mmag). They do not have any obvious harmonic relationship, nor do they have the frequency ratio (0.77–0.78) expected of the fundamental mode and first radial overtone modes. HD 42503, sectors 5–7 The mutliperiodic nature of the light curve at frequencies near 5 d −1 is rather unusual. The frequency content does not strongly resemble that of γ Dor stars, but is also quite different from typical δ Sct stars. No radial modes could be identified from frequency ratios of the stronger peaks. The peaks at 0.99 and 2.00 d −1 are not perfect harmonics, and another peak at 3.94 d −1 also falls on this near-harmonic pattern. HD 43533, sectors 6–7 The star is a γ Dor variable and the light curve is dominated by low-frequency variability, with dozens of significant peaks below 6 d −1 , and this variability spills into the δ Sct frequency domain. Excluding this variability, which presumably does not include independent p modes, there are only a few peaks in the Fourier transform that make this a δ Sct star. All three extracted peaks are significant, with SNR>4, despite their low amplitudes. The low amplitudes perhaps suggest these peaks belong to a contaminating source, but the Gaia DR2 data show no likely contaminant. It is noteworthy that this star is located below the ZAMS compared to tracks of solar metallicity. HD 44930, sector 5 The Fourier transform is dominated by several p modes of mmag amplitude. A group of weaker peaks with frequencies between 2 and 3 d −1 might be g modes. The absence of peaks at even lower frequencies would then suggest these are l = 1, m = 1 prograde modes, which suggests the near-core region rotates rapidly. This star is in the Octans association and has a measured Δν of 6.03 d −1 (Bedding et al. 2020 ). The échelle diagram (Fig A1 ) suggests f 1 = 18.15 d −1 is the fundamental mode, even though this is not in agreement with the P–L prediction. HD 47425, sectors 6–7 The two dominant p modes are too close in frequency to be the fundamental mode and first radial overtone. Indeed, it is not possible to clearly identify radial modes by period ratios in
Paper: 2016A&A...590A..98H (fulltext)
the telluric standard. As a last step in the data reduction process, the science spectra were divided by the response function of the corresponding standard star (examples of the final telluric corrected science spectra can be seen in Figs. B.1 and B.2 ). 4.1. Flux calibration We calibrated the continuum level of our sources to the corresponding spectroscopic standard (the collected telluric standards). For the standard stars we collected the W2 magnitudes (m) from the WISE all-sky catalogue: HR6527 (.103 mag), HR4730 (.025 mag), and HR2421 ( mag). Using these values, the continuum flux at 4.6 m of the three standard stars is respectively, 25.83 Jy, 36.62 Jy, and 42.05 Jy. There are small differences in the widths of the point spread function for the science spectra and the telluric standard spectra (we expect these differences to be due to variations in the performance of the adaptive optics system). We do not correct for these differences, but note here that the error expected from these differences in our flux calibration is 10%. Furthermore, when viewing the full spectra for each source there are inconsistent variations in continuum level at different wavelength settings (or detectors) for overlapping or neighbouring regions. These variations are at the 10% level. We apply flux shifts to the frames where this is needed to make the full spectrum fit one consistent continuum curve. 4.2. Line detection All of our observed sources have clear detections of H i recombination lines in emission: Pfund 7-5 and the Humphreys 11-6 line. For these lines, individual line profiles are shown in Fig. B.3 . The FWHM, the line centres, and the derived doppler shifts, together with the 3 error bars are shown for all sources in Table B.1 . Spectra from four of our sources (HD 163296, HD 250550, Hen 2-80, Hen 3-1227) also show clear detections of CO ro-vibrational emission lines. The CO emission from these four sources is not spatially resolved (for more details on spatially resolving emission with CRIRES see van der Plas et al. 2015 ). CO ro-vibrational emission lines could also be present in MWC 137. The spectrum shows what appears to be many wide and often blended emission lines. For the four sources with CO detections, individual CO lines were identified and extracted using wavelengths from Chandra et al. (1996) . For each source certain wavelength settings overlap, resulting in a few lines being detected twice. Furthermore, in the cases of Hen 2-80 and Hen 3-1227 we collected observations during two nights with the same wavelength settings. These doubly collected lines can be used for sanity checks and uncertainty estimates. For the further analysis we consider our line selection carefully. Some lines are contaminated by telluric residuals and some lines are blended and cannot be separated for individual profile extraction. We thus manually select the best uncontaminated and unblended lines for further analysis (Table C.1 ). Fig. 2 FWHM as a function of
Paper: 2016ApJ...818..191T (fulltext)
the 7 Be ii doublet cannot be resolved, its total equivalent widths, W ( 7 Be ii )s, in the LVC and the HVC are measured. After subtracting the combined effects of contaminations discussed above we tabulate the resulting W ( 7 Be ii ) in Table 3 . The errors of W are estimated from the S/N of the neighboring continuum. They do not include the uncertainties in the continuum placements. Table 3 Equivalent Widths of Blue-shifted Absorption Lines in Observed Novae The abundances of 7 Be in nova ejecta is estimated following the same procedure as used in Tajitsu et al. ( 2015 ). We compare the equivalent widths of Ca ii K () and 7 Be ii (, respectively) in the LVC, which show a simpler structure than the HVC. Here we need the following assumptions: (1) both the 7 Be ii and Ca ii lines are not saturated and (2) the covering factor of the absorbing gas cloud to the background illuminating source has no wavelength dependence. We notice that the LVC feature of 7 Be ii at −786 km s −1 of V5668 Sgr might be saturated. The bottom of the 7 Be ii lines in the LVC almost reaches to that in the HVC where its flat profile suggests that the absorption is saturated. The corresponding LVC component of the Ca ii K line in V5668 Sgr is shallow and the line appears to be unsaturated. The abundance of 7 Be in V5668 Sgr obtained under such a condition should be taken as a lower limit. Following Spitzer ( 1998 , Equations (3)–(48)), the ratio of column number densities, N , can be written asUsing data of the W ( 7 Be ii ) and the listed in Table 3 the column density ratios N ( 7 Be ii )/ N (Ca ii ) derived in the LVC of V5668 Sgr and V2944 Oph are 8.1 ± 2.0 and 2.5 ± 1.5, respectively. These ratios are close to that found in V339 Del at +47 days. The ionization states of each species are keys to convert the above ratios into atomic abundances. We assume that the most of 7 Be is in the singly ionized state because it still stays in hot ejecta. We also assume that Ca is in the singly ionized state. The absence of Ca i lines in the blueshifted absorption line systems supports this assumption. The difference in the second ionization potential (Be: 18.21 eV, Ca: 11.87 eV) may lead to different balances between the second and the third ionized ions and this may be a source of an error in determining the abundances. We tried but failed to detect absorption lines of doubly ionized ions of Fe-peak elements, which have intermediate second ionization potentials, consulting Kramida et al. ( 2014 ). Absorption lines of Fe iii are observed in optical range spectra of B-type stars (Thompson et al. 2008 ). This may support the assumption that all of 7 Be and Ca contained in the LVC are in the singly ionized state. Adopting this assumption, the mass fraction of 7 Be to the sum of all constituent mass components, ( 7 Be ii ), can be presented as: ( 7 Be) ∼ N ( 7 Be ii )/ N (Ca ii ) × 7/40 × X (Ca). We have obtained ( 7 Be)/ (Ca) = 1.4 ± 0.3 for V5668 Sgr and 0.44 ± 0.26 for V2944 Oph.
Paper: 2021MNRAS.505.1730L (fulltext)
π is readily apparent. A simple way to quantify this apsidal alignment is to compare with the number fraction f even of an even π distribution. If we have N Trojans in total, since the width of each π bin is adopted to be 30 ○ , a sample size of N bin = (30/360) N per bin is expected, i.e. the mean fraction . Considering the random variations about the value of f even due to counting statistics, the uncertainty from Poisson distribution can be calculated by . Accordingly, in the upper panels of Fig. 1 , the horizontal solid and dashed lines are plotted to indicate the mean fraction f even and its 5 σ upper uncertainty, respectively. As the peak of the histograms can achieve the value of ∼0.21 (L5)–0.23 (L4), much higher than the dashed line, the clustering of π shows strong significance over 5 σ confidence level. Another key point shown in these two figures is that the number peak corresponds to the bin of π = 30 ○ –90 ○ (300 ○ –330 ○ ) for the L4 (L5) Trojan swarm, giving a difference of around +60 ○ (−60 ○ ) with Jupiter’s longitude of perihelion π J (indicated by the red line). Figure 1. Distribution of the longitudes of perihelia π (upper panels) and the longitudes of ascending nodes Ω (lower panels) of the observed Jupiter Trojans, at the epoch of 2020 May 31. Left-hand column: There are 4625 objects in the L4 region, and the values of their π are clustered around π J + 60 ○ ( π J is the longitude of perihelion of Jupiter). Right-hand column: There are 2729 objects in the L5 region, and the π clustering is around π J − 60 ○ . For reference, the horizontal solid lines are plotted in the upper two panels for the uniform distribution in π , and the dashed lines indicate the 5 σ upper uncertainty from Poisson statistics. In order to further confirm the newly found characteristic of apsidal clustering, we need to consider the evolving orbits of Jupiter Trojans at different epoch. Since the periodicity in the variation of Jupiter’s longitude of perihelion π J is ∼0.17 Myr, we propose that the 1-Myr time-scale is long enough to check the persistence of the apsidal confinement of Jupiter Trojans due to different precession rates of their π . Then the π distribution of the Jupiter Trojans after 1-Myr evolution is shown in Fig. 2 , from the integration mentioned at the beginning of this section. One can immediately notice the similar patterns depicted in Fig. 1 : (1) the longitudes of perihelia π are clustered around π J + 60 ○ and π J − 60 ○ for the L4 and L5 swarms, respectively; and (2) the number fraction of the clustered samples within a π bin could be over 0.2, which is significantly larger than f even ∼ 0.083 (>5 σ confidence level) in the case of a uniform π distribution. Therefore, the apsidal asymmetric-alignment of Jupiter Trojans should be intrinsic but not due to the observational bias. We suppose that the gravitational perturbation of Jupiter with eccentricity e J ∼ 0.05 may induce and maintain this intriguing orbital
Paper: 2020MNRAS.495.3715Z (fulltext)
indicates that the generation of different emission bands occurs in different parts of the source with a non-uniform magnetic field and plasma density. From Fig. 1 , it is clear that each emission band has a fine structure: It consists of narrower (in frequency) elements that show a characteristic evolution in time. Each emission band begins with the appearance of a low-frequency element, which exists for a shorter time than the burst as a whole. Then there appears the next element, which is shifted towards the higher frequencies, etc. Each band contains 3–5 individual elements of the fine structure. Schematically, this evolution is more clearly shown in Fig. 2 , where the bright elements in the four emission bands from Fig. 1 are represented as dark horizontal lines. Figure 2. Schematic representation of the evolution of the dynamic spectrum (Fig. 1 ) with a fine structure of the emission bands. A fragment of the dynamic spectrum enclosed in a rectangle is analysed in Section 3 (see Fig. 7 ). A careful examination of the dynamic spectrum in Fig. 1 and similar spectra published by Hankins and Eilek leads to the conclusion that the elements of the fine structure are not superimposed on the quasi-harmonic emission bands. They actually form these bands, and the observed frequency drift of the emission bands towards higher frequencies is due to the successive change of one bright element to another, higher frequency element at a later instance of time. This fact is also indicated by Hankins et al. ( 2016 ), who analysed a large number of pulses and concluded that the drift of the emission bands towards higher frequencies is due to the appearance of new elements in the band that are delayed in time and start at slightly higher frequencies. Fig. 3 shows another, more rare type of the dynamic spectrum (Hankins, Rankin Eilek 2009 ). In the observed frequency range 8–10 GHz, the dynamic spectrum exhibits a continuous fine structure of 10 elements, rather than individual emission elements grouped into quasi-harmonic bands. Note that an insufficiently high frequency resolution does not allow an unambiguous conclusion to be drawn whether a finer frequency structure similar to that observed in Fig. 1 exists inside the observed emission bands. We also note that the interval 8–10 GHz, in which radiation with the above-mentioned structure was observed, is too narrow to definitely judge the change in the emission band spacing. It is quite possible that it remains constant. The latter will be taken into account in Section 3 when explaining the dynamic spectrum depicted in Fig. 3 . Figure 3. Rare type of the dynamic spectrum with the emission bands. This figure is adapted from Hankins et al. ( 2009 , fig. 5). Note that in both types of the dynamic spectrum, the signal lags as the radiation frequency is decreased. Hankins et al. ( 2016 ) relate this effect with the group delay of the signal directly in the local radiation source with a zebra pattern. It is
Paper: 2018ApJ...859..109S (fulltext)
to the dotted line in Figure 5 . The expected change of gas-phase metallicity due to this process can also be estimated using the toy model worked out in Appendix A . On the one hand, the drop of metallicity after accreting a gas mass Δ M a scales with the accreted gas mass aswhere M g 0 stands for the mass of gas already present in the object and C is a time-dependent parameter that is of the order of 1 after the accretion event (see Equation ( 26 ), with Z in ≪ Z g Z g 0 ). On the other hand, M a / τ in , and thereforeThe logarithmic derivative has been evaluated assuming Δ M a ∼ M g 0 and C ∼ 1. Its actual value can go all the way from −1 (when Δ M a ≫ M g 0 ) to 0 (when Δ M a ≪ M g 0 ). 4. Is the Correlation between Size and Gas-phase Metallicity a Result of Differences in the Depth of the Gravitational Potential of the Galaxies? The short answer to the above question is no . The long answer is elaborated in this section showing that the escape velocity and the metallicity are not correlated in the EAGLE galaxies. In order to parameterize the depth of the gravitational potential, we use the escape velocity at the half-mass radius,with Φ( R ⋆ ) the gravitational potential at R ⋆ . We model Φ as a combination of the potential due to DM, Φ DM , and the potential due to stars, Φ ⋆ ,The EAGLE database does not directly provide the depth of the gravitational potential. We infer the DM component from the DM mass and the half-mass radius of the DM assuming that the density drops with radius following a NFW profile (Navarro et al. 1996 ). The procedure is sketched in Appendix B . The stellar contribution is also inferred from the stellar mass and the half-mass stellar radius, this time assuming that the stellar density drops exponentially with radius. We follow the work by Smith et al. ( 2015 ). We assume the galaxy disks to be thin (scale height of 0.2 kpc), with the escape velocity computed in the plane of the disk. The results are rather insensitive to these assumptions since the potential is dominated by the DM component. This is also the reason why the gas mass is not included in the computation of v esc , because it represents only a minute fraction of the total mass. Figure 7 is similar to Figure 2 , but this time the symbols are color-coded with the escape velocity at the half-mass stellar radius. The spread in gas-phase metallicity is uncorrelated with the escape velocity, which is mostly set by the stellar mass. For a given stellar mass the galaxies have the same escape velocity irrespectively of the metallicity of their gas (cf. Figures 2 and 7 ). This fact is even clearer in Figure 8 . It shows Z g versus v esc for the full set of EAGLE galaxies (top left), as well as for narrow bins in galaxy mass (Δ log M ⋆ ∼ 0.3). Even though the full set shows a global trend for the gas-phase metallicity to increase with the escape velocity, this is just a construct (or a mirage) resulting from the mass–metallicity relation and the