adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018MNRAS.480..692P (fulltext)
mass with a ratio coefficient f : and the accretion rate will be where f may be of the order of 0.5, as argued by van den Heuvel Bitzaraki ( 1995 ). Because the mass statistics of NSs and MSPs illustrate that the accreted mass at least is about for MSP formation (Zhang et al. 2011 ; Kiziltan et al. 2013 ; Ozel Freire 2016 ; Antoniadis et al. 2016 ), we prefer f to be about 0.1−0.2. A NS/LMXB with m = 1.4 and R 6 = 1 for possesses an accretion rate higher than . However, it cannot accrete at a rate over the Eddington limit, namely . With the limit of the accretion rate , it is possible to derive an upper limit companion mass in the main sequence according to equation ( 11 ): With 0.1 f 0.2, will be about to . Hence a possible mass distribution of the companion in the main sequence in a LMXB is , corresponding to an accretion rate of . In such a LXMB, the NS will evolve to be a MSP with a magnetic field of . For , however, the accretion time might be too short for the binary system to produce a MSP. Table 2. The 16 radio MSPs with a low magnetic fields of (data from the ATNF pulsar catalogue). 2.4 On the minimum magnetic fields of AMXPs AMXPs exhibit an X-ray outburst during the accreting phase, with a luminosity a few magnitudes higher than that in the quiescent phase (Wijnands van der Klis 1998 ; van der Klis 2000 , 2006 ; Mukherjee et al. 2015 ). The variation of the luminosity leads to a change in the accretion rate, and thus the magnetic field of AMXPs can be derived by equating the magnetosphere radius with the co-rotation radius R co of the NS (Burderi et al. 1996 ; Zhang Kojima 2006 ): where P −3 is the spin period P of AMXPs in units of milliseconds. When R co equals the NS radius, the AMXP will have the minimum magnetic field. For 19 AMXPs with spin periods in the range ~1.7–6.1 ms (Patruno, Haskell Andersson 2017b ), their R co are in the range of ~24–56 km, which is larger than the radii of NSs of ~10–15 km. Thus, it can be concluded that the magnetic fields of 19 AMXPs have not achieved their lowest values. Another method for judging the minimum magnetic field of AMXPs is comparing their spin frequencies to the kilohertz quasi-periodic oscillation (kHz QPO) frequencies. The upper-limit kHz QPO frequency of a AMXP is believed to be the Keplerian frequency with orbital accreting matter (van der Klis 2000 ; Zhang 2004 ): where G is the gravitational constant. For a NS with m = 1.4 and R 6 = 1.5, the orbital frequency ν k is . Some AMXPs have an upper kHz QPO frequency over (van der Klis 2000 , 2006 ; Wang et al. 2017 ), which is comparable to ν k . However, the spin frequency of 19 AMXPs ranges from 164 to (Patruno et al. 2017a ), which is much lower than the upper kHz QPO frequency or ν k , and hence we conclude that the minimum magnetic fields of 19 AMXPs have not yet been achieved. If the co-rotation radius approaches the stellar radius, AMXPs will obtain the minimum magnetic field through accretion. 2.5 The minimum magnetic
Paper: 2017MNRAS.472..230T (fulltext)
which describes the adopted stellar mass ( M ), polar radius ( R p ), polar effective temperature ( T eff,p ), equatorial rotation velocity ( v e ) and inclination angle ( i ). For example, ‘m40r40t150v300i30’ is the case of M = 4.0 M ⊙ , R p = 4.0 R ⊙ , T eff,p = 15 000 K, v e = 300 km s −1 and i = 30°. (2) Polar radius (in R ⊙ ). (3) Equatorial radius (in R ⊙ ). (4) Polar effective temperature (in K). (5) Equatorial effective temperature (in K). (6) Mean effective temperature in K (which was derived by averaging the local effective temperature over the observed stellar disc while weighting according to the local continuum intensity). (7) Product of v e and sin i (in km s −1 ). (8) First-zero frequency of He 4471 (in Å − 1 ). (9) Ratio of to , where is the first-zero frequency of classical rotational broadening function (see, e.g. Gray 2005 ), which is related to v e sin i as (λ: wavelength, c : velocity of light). (10) First-zero frequency of Mg 4481 (in Å − 1 ). (11) Ratio of to . The wavelengths of the reference pseudo-continuum, necessary for reducing the normalized profile, were defined in almost the same way as in Section 4.1: Having found the critical wavelength λ* corresponding to the maximum level between these two lines, we set [, ] = [4471 − (λ* − 4471), λ*] and [, ] = [λ*, 4481 + (4481 − λ*)]. The Fourier transforms were then calculated for the resulting R (λ) profiles of He 4471 and Mg 4481 lines. Fig. 6 illustrates the behaviours of | f (σ)| as function of σ for the same selected cases as in Fig. 5 . The first-zero frequencies (σ 1 ) measured from the computed transforms are presented in Table 2 . Figure 6. Fourier transform amplitudes [| f (σ)|] plotted against σ, for the theoretical profiles of He 4471 (left-hand panels) and Mg 4481 (right-hand panels) computed for six representative models (same as those shown in Fig. 5 ). The upper panels (a) and (b) show the results for T eff,p = 12 000 K, while the lower panels (c) and (d) are for T eff,p = 15 000 K. 5 DISCUSSION 5.1 Characteristics of first-zero frequencies We first discuss the trend of theoretical σ 1 modelled in Section 4.2 . Since this quantity is expressed as σ 1 = 0.660/(λ v e sin i / c ) in the classical approximation, the projected rotational velocity (or the linewidth for the case of rotation-dominated broadening) plays the most significant role for determining σ 1 , though its precise value is affected also by the profile shape. The resulting values of σ 1 corresponding to the theoretical line profiles simulated on the gravity-darkened models are plotted against v e sin i in Fig. 7 , where the classical σ 1 versus v e sin i relation is depicted by a slanted solid line and the observed σ 1 values for six stars are indicated by horizontal dashed lines. Figure 7. The values of theoretical σ 1 , measured from the Fourier transforms of simulated spectra for gravity-darkened models, are plotted against v e sin i . The results for He 4471 (left-hand panels)
Paper: 2019A&A...621A.129L (fulltext)
rate coefficients. Notes. TW18 and MP17 refer to models with nominal values of the oxygen-bearing influx (see Sect. 4 ). ( a ) CO 2 best-fit mixing ratio at 0.15 mbar from photochemical modelling in Orton et al. (2014b ) is 8.0 × 10 −11 . ( b ) Ice grain ablation influx giving rise to 1.2 × 10 5 and 4.5 × 10 3 cm −2 s −1 for H 2 O and CO 2 , respectively. The outcome of this sensitivity test indicates that a CO relative abundance of 7.0 × 10 −9 at 0.4 mbar allows an optimal match of the line core and wings. Table 4 lists different cases where ( D , t impact ) have been tuned to obtain q CO = (7.0 ± 0.1) × 10 −9 at the ~0.4 mbar region, the delivered CO mass (in g), and the CO mixing ratio obtained in 200–100 mbar. The resulting profiles in the 200–100 mbar region reflect that larger impactors give rise to larger CO abundances although below the upper limits in Teanby Irwin (2013) . Table 4 shows that the solution is degenerate; in other words, the same stratospheric CO mixing ratio abundance can be obtanied with pairs of ( D , t impact ) that represent larger impacts having taken place longer ago, or smaller impactors occurred more recently. For instance, the temporal evolution of the material delivered by a cometary impact indicates that the CO currently observed in the Uranus stratosphere could be due to a comet nucleus of 3.5 km diameter that hit the planet 822 yr ago. Figure 4 shows the comparison of the measured spectra and the modelled radiative transfer as a function of the different CO vertical distribution resulting from steady ice grain ablation and cases 3 and 4 for cometary impact. Any other of the cases in Table 4 will give rise to a CO mixing ratio of ~ 7.0 × 10 −9 at the 0.4 mbar pressure level that will give good match to the Herschel data. Stratospheric CO mixing ratio profiles with an abundance larger than the value in the pressure range probed by Herschel (i.e. between 3 and 0.4 mbar) can in principle be discarded as they will overestimate the observations. Similarly, the tropospheric CO mixing ratio profile has to be lower than the upper limit 2.1 × 10 −9 established by Teanby Irwin (2013) . Equations (14) and (15) in Zahnle et al. (2003) , adapted to Uranus where the impact frequency is ~ 4 times smaller than on Jupiter, allow us to plot the frequency of impact versus the impactor size. Figure 5 displays two different scenarios depending on the origin of the impactors: the size-number distribution of impactors is like that inferred at Jupiter (ecliptic comets), and those impactors more representative of nearly isotropic comets (as long-period or Halley-type comets). Zahnle et al. (2003) conclude that known craters on the Saturnian and Uranian satellites are consistent with either case; that is, both kinds of impactors are in the Uranian system and they could have entered the Uranus atmosphere. Also, Zahnle et al. (2003) assume that the impact rate on Uranus is ~ 0.00125 comets per year (i.e. one impact every ~800 yr)
Paper: 2020MNRAS.493L.108B (fulltext)
This observational evidence makes HL Tau an example of a young (∼1 Myr; Briceño et al. 2002 ), embedded, disc-hosting star. HL Tau has therefore become a prime target for studies aiming to characterize young discs (Greaves et al. 2008 ; Carrasco-González et al. 2009 ). In particular, HL Tau was the first circumstellar disc observed with the long baselines of Atacama Large Millimeter/submillimeter Array (ALMA). This revealed an ordered series of concentric rings and gaps in the disc across multiple millimetre wavelengths (2.9, 1.3, and 0.9 mm; ALMA Partnership et al. 2015 ). Many theories have been put forward to explain the origin of these structures (e.g. Zhang, Blake Bergin 2015 ; Okuzumi et al. 2016 ), but one of the most persistent involves the growth of planets within the disc (Dipierro et al. 2015b ). While efforts to detect thermal emission from young planets in the gaps have been unsucessful, the corresponding upper limits on their masses still lie at the higher end of the giant-planet regime (10–15 M Jup ; Testi et al. 2015 ). The combination of the potential for massive planets at large radii, coupled with evidence of a high disc mass (∼0.1–0.13 M ⊙ ; Guilloteau et al. 2011 ; Kwon, Looney Mundy 2011 ), has seen gravitational instability (GI; Boss 1997 ) being invoked to explain both the observed dust structures in HL Tau (Akiyama et al. 2016 ; Takahashi Inutsuka 2016 ), along with the origin of any planetary companions (Nero Bjorkman 2009 ). However, recent measurements of the gas mass in the HL Tau disc using have shown appears to be too low for GI to occur ( M gas = 2–40 × 10 −3 M ⊙ ; Wu et al. 2018 ). In this Letter, we present a detection of the J = 3–2 transition towards the disc around HL Tau. We have demonstrated this line to be a robust tracer of disc gas mass (Booth et al. 2019 ). We use these data to derive a lower limit to the total gas disc mass and discuss how this impacts the gravitational stability of the HL Tau star–disc system. 2 OBSERVATIONS HL Tau was observed by ALMA in Band 7 on 2017 November 24 for 1.46 h with 49 antennae in configuration C43-8 under project code 2017.1.01178.S (PI: E. Humphreys). Baseline lengths ranged from 92 to 8547 m, and the spectral window (SPW) covering the J = 3–2 transition (321.852 GHz) had a native spectral resolution of 0.908 km s −1 (which we note does not resolve the J = 3–2 hyperfine structure). Data (self-)calibration and imaging were performed with casa version 5.1.1 (McMullin et al. 2007 ). Continuum subtraction was performed in the uv -plane using a constant baseline (fitorder 0). Line imaging was performed with the clean algorithm, using a Keplerian mask with the measured position and inclination angles of the disc (e.g. PA = 138° and i = 46°; ALMA Partnership et al. 2015 ). The native resolution of the data resulted in a natural beam size of 0.14 × 0.11 arcsec 2 (−13°). We used a 0.2-arcsec uv -taper, which was found to maximize the signal-to-noise ratio (S/N) of the line
Paper: 2016A&A...593A..58J (fulltext)
above even a high percentile point necessarily belong to a real filament. The histograms in Fig. 4 g are plotted for the intersection of two sets of pixels, those that are above the 95% percentile of significance (given by the and values) and those that coincide with a real filament (see Fig. 4 d). The RHT parameters are this time optimised manually, only keeping = 10 fixed. This leads to values = 5 and = 0.65. By visual inspection of the results, TM is slightly more successful in highlighting the location of filaments (Fig. 4 c) and estimating their position angles (Fig. 4 g). Fig. 4 Comparison of RHT and TM results in the case of non-linear filamentary structures on a fluctuating background. For the description of individual frames see Fig. 2 . Figure 5 shows how the results change as a function of the parameter values. For TM, the values of and are varied in 30% steps. For RHT, the parameter is kept at a value of 0.65, which was found to give the best results in Fig. 4 , but and are also change in 30% steps around the best parameter combination. The results of TM are less sensitive to these changes in the input parameters. Fig. 5 Change in RHT and TM results as a function of the method parameters. RHT parameters and are varied and parameter is kept at a value of 0.65. 3.2. Reliability and completeness We address questions of TM reliability estimation in the case of the simulation shown in Fig. 4 . equals 2.8 pixels and any two estimates that are separated by approximately five pixels can be considered independent. We first analyse maps similar to those in Fig. 4 but without filaments and with different realisations of noise and of large-scale fluctuations. According to this Monte Carlo exercise, 84%, 97.7%, and 99.9% confidence limits correspond to values of 0.0457, 0.0638, and 0.0850, respectively. This can be compared to the values of the same percentiles that are obtained directly from the input map of Fig. 4 . Those values are 0.057, 0.23, and 0.43 and they would thus result in lower estimates of the statistical significance of a given value. For example, , the apparent value corresponding to the 84% confidence limit, is in reality closer to the 97.7% confidence limit. The values are higher because of the presence of real elongated structures. The more real structures the map has, the more conservative are the limits derived from the statistics of the image itself. For a 360 360 pixel image, one would expect 2981 spurious pixels above the given threshold of . We count as spurious all pixel whose distance to real filaments exceeds three pixels. The number of such pixels is 3174, by 6.5% higher than expected. However, there are still some pixels with that are associated to filaments but are at distances exceeding three pixels. This suggests that the threshold obtained from the Monte Carlo simulations gives a rather accurate estimate of the reliability. For the 97.7% confidence limit, we expect the map to contain 68 instances where two
Paper: 2018MNRAS.473.2084M (fulltext)
Also included is the total reflection from the disc, R ( E ), but we do not include the intrinsic or reprocessed disc emission as the energy of this is too low to make a significant contribution to the RXTE data above 3 keV. Figure 1. The assumed geometry. The green region emits the soft spectral shape, S ( E ), and the cyan region emits the hard spectral shape, H ( E ). The direct contribution from the thermal disc (red) is neglected. Fluctuations are generated throughout the flow on the viscous time-scale, t visc ( r ), and propagate down towards the compact object at a local velocity, v ( r ) = rf visc ( r ). Figure 2. The decomposition of Observation 1 (ObsID: 10238-01-08-00) used to augment the standard propagating fluctuations model. Shown are the total energy spectrum (black), the hard Compton component ( H ( E ), cyan), the soft Compton component ( S ( E ), green) and the reflection component ( R ( E ), magenta). Filled circles show the PCA (red) and HEXTE (black) data. The red, green and blue bands denote the Low (3.13–4.98 keV), Mid (9.94–20.09 keV) and High (20.09–34.61 keV) energy ranges, respectively. Table 1. Fit parameters for the spectral model shown in Fig. 2 , with the reflected emission from the sum of the two Comptonization components: tbabs*(nthcomp+nthcomp+kdblur*xilconv*twocomp) . The electron temperatures ( kT e ) of both Comptonization components are tied. The fixed parameters in our fits are the Galactic absorption column density (0.6 × 10 22 cm −2 ), the seed photon temperature (0.2 keV), the kdblur index (3.0), the inclination angle of Cyg X-1 (27 o ), the inner disc radius (10 R g ) and the xilconv iron abundance (1.0). 4.2 Spectral-timing model In all simulations, we assume that Cyg X-1 has a black hole of mass, M BH = 15 M ⊙ , and a dimensionless spin parameter of a * ∼ 0.85 (Kawano et al. 2017 ). The inner radius is set to the approximate ISCO size implied from the spin of Cyg X-1, so that r i = 2.5. The time-averaged spectrum, , emitted from each radius is given by the expression r SH here is the transition radius between the soft and hard Comptonization regions. This is analytically derived from an assumed emissivity, ε( r ) ∝ r −γ b ( r ), where b ( r ) is an inner boundary condition, such that the luminosity ratio between the two components matches that observed, such that The light curves produced by the standard propagating fluctuations model at each radius are then made energy-dependent and renormalized such that their time-average is the flux for that energy bin and radius, yielding The summation limits implied by ‘ region ’ are { r o to r SH } for r n > r SH and { r SH to r i } for r n r SH . This normalization guarantees that if equation ( 6 ) is time averaged and summed over all radii, the observed energy spectrum is reproduced. We match our spectra to the data as closely as possible by converting these fluxes into count rates using the detector effective area A eff ( E ) and Galactic absorption
Paper: 2017MNRAS.464.4318N (fulltext)
we find that the median total number of stars that are enriched per event is ∼13, which is comparable to the maximum number of G dwarfs (stars with similar mass to the Sun, 0.8–1.2 M ⊙ ) that were enriched in the more populous clusters studied in Parker et al. ( 2014a ) as are the fraction of enriched G-dwarf stars that were unperturbed (∼0.5 per cent). In an attempt to increase the fraction of enriched stars, we explore a host of initial conditions for the star clusters. However, we find that no initial conditions result in a significantly higher (more than twice) fraction of enriched stars. The principal reason for this is the effects of two-body relaxation. In order to enrich more than half of the stars in a low-mass cluster, the required stellar density at the time of the SN(e) explosion(s) corresponds to a radius of only ∼0.4 pc, which is impossible to achieve after 5 Myr of evolution. Two-body relaxation results from a stellar system attempting to reach dynamical equilibrium and even a moderately dense system (100 stars pc −3 ) such as our default model expands significantly in the first 10 Myr, as shown in Fig. 7 . Here, the coloured lines represent the median local stellar density with time in each of the 20 realizations of these initial conditions. The solid black line is the mean central density across all 20 simulations (where we define the central density as the density within the half-mass radius). Clearly, the clusters have expanded significantly before the SN explosions (shown by the vertical dashed lines). Figure 7. Evolution of the median local volume density in each simulation as a function of time. Coloured lines indicate each of the 20 simulations and the black line indicates the average central density. Vertical dashed grey lines indicate times of the SNe. Irrespective of the initial conditions, the clusters never attain significant enrichment because the initial density is either too high (and two-body relaxation causes significant expansion), or the initial density is so low that despite the initial subvirial motion of the stars, significant clustering of the stars never occurs. The fraction of enriched unperturbed G-dwarf stars across all initial conditions range between ∼0.07 and 0.55 per cent. 3.4 Low-mass clusters containing one massive star The second median cluster chosen from our Monte Carlo sampling contained 113 stars, of which 1 was massive (24 M ⊙ ), resulting in an SN explosion at ∼7 Myr. The same set of initial conditions are focused on (α vir = 0.3, r F = 1.0 pc and D = 1.6) before summarizing the others. An average of six stars were enriched by the SN, a similar number to the median cluster containing two massive stars. The dynamical interaction and cluster density histories were also similar, resulting in ∼0.1–0.4 per cent of G dwarfs being enriched and unperturbed. With almost identical enrichment fractions and dynamical histories, the difference between clusters containing one or two massive stars is
Paper: 2016MNRAS.463..604M (fulltext)
Strassmeier 2012 ) observed in total 11 transits in five observing seasons using the filters Johnson B and Sloan r ′. The first seven transits were observed with both filters alternating. These r ′ band light curves were already published by Seeliger et al. ( 2014 ). The four light curves from 2014 to 2016 were taken only in Johnson B . WiFSIP holds a back-illuminated 4k × 4k 15 μm pixel CCD and offers a field of view (FoV) of 22 arcmin ×22 arcmin. To minimize the read-out time, a windowing of the CCD was used reducing the FoV to about 15 arcmin × 15 arcmin. A small defocus was applied to spread the point spread function to an artificial full width at half-maximum (FWHM) of about 3 arcsec. One transit was observed with the NOT as a Fast Track program using ALFOSC in imaging mode. ALFOSC contains a 2k × 2k E2V CCD providing an FoV of 6.4 arcmin × 6.4 arcmin. One transit was observed with BUSCA, the four-channel imager at the Calar Alto Observatory 2.2 m telescope (Reif et al. 1999 ). The instrument performs simultaneous photometry in four different bandpasses with an FoV of 11 arcmin × 11 arcmin. For the bandpass of shortest wavelength, we used a white glass filter and the beam splitter defined the limit of λ 430 nm. For the other bandpasses from blue to red, we used a Thuan–Gunn g , Thuan–Gunn r , and Bessel I filter. Unfortunately, the observation of a pre-ingress baseline was lost due to weather, and the observing conditions remained to be non-photometric. We discarded the light curve of shortest wavelength because it exhibited significantly larger correlated noise than the other three light curves. One transit was observed with the IAC80 telescope, owned and operated by the Instituto de Astrofísica de Canarias (IAC), using its wide field imager CAMELOT. It is equipped with a CCD-E2V detector of 2k × 2k, with a pixel scale of about 0.3 arcsec pixel −1 providing an FoV of about 10.5 arcmin × 10.5 arcmin. Two transits were observed with the 70 cm telescope of the AIP, located in the city of Potsdam at the Babelsberg Observatory. The telescope is equipped with a cryogenic cooled 1k × 1k TEK-CCD providing an FoV of 8 arcmin × 8 arcmin. The first transit was observed in Johnson B and Johnson V quasi-simultaneously with alternating filters, the second one in Johnson V only. We applied a 3 × 3 pixel binning to reduce the detector read-out time. Data of an additional transit were taken with the triple beam, frame-transfer CCD camera ULTRACAM (Dhillon et al. 2007 ) mounted at the WHT. The instrument optics allow for the simultaneous photometry in three different bandpasses. We chose the filters Sloan u ′, Sloan g ′, and a filter centred on the sodium doublet at 591.2 nm with a width (FWHM) of 31.2 nm. To avoid saturation of the brightest stars, the exposure time was extremely short with 0.3 s. However, the overheads are negligible owing to the frame-transfer technique. The detectors were read out in windowed mode. For the u ′ channel, 10