adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020MNRAS.498.3658L (fulltext)
view of Event 1 observed simultaneously with AstroSat SXT, Chandra LETG/HRC-S, and HST binned to 100s each. The vertical lines in brown and yellow represents the UV and X-ray flare peaks, respectively. The amplitudes of the HST light curves are scaled to be consistent with X-ray light curves. A detailed analysis of the HST data will be presented in Schneider et al. (in preparation). However, a visual inspection of Fig. 4 indicates that the HST FUV light curve precedes the X-ray light curves by about a few minutes. This may indicate that the presence of Neupert effect (Neupert 1968 ) during the rising phase of Event 2. Using the Z-transformed discrete correlation function (ZDCF) (Alexander 1997 ), the cross-correlation of the HST and the X-ray light curves produces a time-lag between the peaks to be 300–400 s, indicating that due to electron impingement the UV light curve precedes the thermal radiation. Figure 4. Event 2 simultaneously observed with the AstroSat SXT in 0.5–4.0 keV (top panel), Chandra LETG/HRC-S zeroth order in 0.1–12.0 keV (middle panel), and HST FUV in 120–170 nm (bottom panel). 3.4 Comparison The quiescent emission measured with Einstein , EXOSAT, and ROSAT in 0.3–4.0 keV energy ranges are 7.2 × 10 −12 , 4–16 × 10 −12 , and 2.6–7.2 × 10 −12 erg s −1 cm −2 , respectively. The quiescent X-ray flux observed by Einstein and EXOSAT was reported by Haisch Linsky ( 1980 ) and Haisch et al. ( 1990 ), respectively. We used the ROSAT observations listed in the ROSAT Positive Sensitive Proportional Counter source catalogue (Voges et al. 1996 , 2000 ). Assuming a coronal temperature of 1 keV, sub-solar abundance of 0.5 and using WebPIMMS, we computed energy conversion factor ECF PSPC = erg cm −2 counts −1 to convert the observed ROSAT counts to flux in canonical 0.1–2.4 keV ROSAT energy band. Furthermore, we use the X-ray flux reported by Fuhrmeister et al. ( 2011 ) based on XMM–Newton observations. In Fig. 5 , we plot quiescent flux measured between 1979 and 2017 as a function of time. Furthermore, we assume similar temperature and abundance as before and used WebPIMMS to estimate the flux in the 0.3–4.0 keV energy range. The flux obtained from AstroSat is consistent with the previous estimates of quiescent flux for Proxima Centauri. Figure 5. Quiescent emission flux as a function of time in 0.3–4.0 keV energy range observed by several X-ray missions between 1979 and 2017. An arbitrary sine curve with a period of 7 yr is represented as the blue dashed curve. While a clear cyclic behaviour with a period of ∼7.0 yr is observed for Proxima Centauri in ASAS observations, a similar variation in the X-ray data is not apparent immediately. However, Wargelin et al. ( 2017 ) reported the evidence for a 7 yr stellar cycle using observations from several X-ray missions, principally Swift . The temporal coverage of X-ray observation, the energy resolution and uncertainties due cross-calibration restrict a detailed analysis of the cyclic
Paper: 2016A&A...588A..35T (fulltext)
no selection criteria are employed – dashed line and open squares – and the luminosity function obtained when the selection criteria previously described are used – solid line and filled squares. It is worthwhile mentioning here that the theoretical luminosity functions have been normalized to the bin of bolometric magnitude , which corresponds to the magnitude bin for which the observed white dwarf luminosity function has the smallest error bars. Thus, since this luminosity bin is very close to the maximum of the luminosity function, the normalization criterion is practically equivalent to a number density normalization. As clearly seen in this figure, the theoretical results match very well the observed data, except for a quite apparent excess of hot white dwarfs, which is discussed in detail below. We note as well that the selection criteria employed by Limoges et al. (2015) basically affect the low luminosity tail of the white dwarf luminosity function, but not the location of the observed drop-off in the white dwarf number counts, nor that of the maximum of the luminosity function. This can be more easily seen by looking at the bottom panel of Fig. 2 , where the completeness of the simulated restricted sample is shown. We found that the completeness of the entire sample is . However, the restricted sample is nearly complete at intermediate bolometric magnitudes – between and 15 – but decreases very rapidly for magnitudes larger than , a clear effect of the selection procedure employed by Limoges et al. (2015) . Nevertheless, this low-luminosity tail is populated preferentially by helium-atmosphere stars and by very massive oxygen-neon white dwarfs. The prevalence of helium-atmosphere white dwarfs at low luminosities is due to the fact that stars with hydrogen-deficient atmospheres have lower luminosities than their hydrogen-rich counterparts of the same mass and age, because in their atmospheres collision-induced absorption does not play a significant role and cool to a very good approximation as black bodies. Also, the presence of massive oxygen-neon white dwarfs is a consequence of their enhanced cooling rate, owing to their smaller heat capacity. Fig. 3 Top panel : probability test as a function of the age obtained by fitting the three faintest bins defining the cut-off of the white dwarf luminosity function. Bottom panel : white dwarf luminosity function for the best-fit age. Fig. 4 Top panel : probability test as a function of the age of the burst of star formation obtained by fitting the nine brightest bins of the white dwarf luminosity function. Bottom panel : synthetic white dwarf luminosity function for a disk age of Gyr and a recent burst of star formation (black line), compared with the observed white dwarf luminosity function of (red lines). 4.2. Fitting the age Now we estimate the age of the disk using the standard method of fitting the position of the cut-off of the white dwarf luminosity function. We did this by comparing
Paper: 2021MNRAS.502.3066S (fulltext)
lighthouse effect. Comparing the neutrino modulation frequency with the GW frequency, we found that the neutrino peak frequency is m /2 times larger than the GW peak frequency, where m represents the deformation mode of the PNS (around the rotation axis) induced by the low- T /| W | instability. In the non-rotating model, the neutrino modulation frequency, as previously identified, is almost the same as the SASI frequency, and it is half of the GW frequency. We discussed the detectability of these neutrino modulations by IceCube and HK at a source distance of 10 kpc. If we observe our rotating models along the equatorial direction, the characteristic peak in the power spectra for the event rates at IceCube would be above the noise level. The characteristic peak due to the SASI in our non-rotating model observed along either polar or equatorial directions is also above the noise level. This analysis indicates that the joint observation of the GW and neutrino signals would be useful to extract information on growing multiple modes of non-axisymmetric instabilities such as the low- T /| W | instability and the spiral SASI activity, which is otherwise inaccessible by electromagnetic-wave observations. Finally, we shall discuss several major limitations of our work. Even when the pre-collapse core is a slow rotator (Heger et al. 2005 ) but with a sufficiently weak initial magnetic fields, the magnetic fields may be amplified to a dynamically relevant strength by the magnetorotational instability (MRI, e.g. Akiyama et al. 2003 ; Obergaulinger et al. 2009 ; Masada, Takiwaki Kotake 2015 ; Rembiasz et al. 2016 ). Although the role of the MRI on the post-bounce dynamics remains still unclear, the magnetic fields should play a key role in the angular momentum transport especially in the vicinity of the (differentially rotating) PNS surface. Possible impacts on the growth of the low- T /| W | instability with magnetic fields remain to be clarified. If progenitors have both strong initial magnetic fields ( G) and rapid rotation, the magnetic fields are amplified due to the field wrapping to dynamically relevant strength shortly after bounce, leading to the formation of magnetohydrodynamic (MHD) jets. This would also make the post-bounce dynamics such as the shock evolution and the post-shock flow very different comparing to those of the non-magnetized models. Such difference should also affect the angular momentum transport, not to mention the onset criteria of the low- T /| W | instability. Although there are a few recent 3D MHD core-collapse simulations, the development of the low- T /| W | instability has been only reported in Scheidegger et al. ( 2010 ) and suggested in Kuroda et al. ( 2020 ) (see, however, Mösta et al. 2014 ). Also, the convective dynamo may amplify the magnetic fields and modify the dynamics in the late phase of the core collapse (e.g. Raynaud et al. 2020 ). To answer these questions, one apparently need to perform 3D GR-MHD
Paper: 2021ApJ...912...93O (fulltext)
1. Hipparcos AGB stars. This list is biased toward nearer stars, mostly within 1 kpc. McDonald et al. ( 2012 ) obtained effective temperatures and luminosities of 107,619 Hipparcos stars (ESA Publications Division 1997 ) based on photometric data covering from the UV to the far-IR. Our search was limited to Hipparcos stars restricted to T eff 3500 K and 1000 ( L / L ⊙ ) 54,000, which eventually reduced the number of candidates to 801 objects. The maximum temperature and minimum luminosity (Salaris Cassisi 1997 ) are criteria intended to reduce the contamination of the sample by RGB stars, while the upper limit of luminosity corresponds to the tip of the AGB ( M bol = − 7.1; Wood et al. 1983 ) that separates massive, evolved AGB stars from supergiants in the HR diagram. Eventually, the spectral classifications of the selected stars were examined in the SIMBAD database to exclude symbiotics, CVs, and other stars that had their temperature and/or luminosity miscalculated by McDonald et al. ( 2012 ). 2. Mass-losing AGB stars. In order to include stars with a circumstellar dust shell ( yr −1 ), a sample of 563 mass-losing AGB stars detected with the Japanese experiment IRTS (Murakami et al. 1996 ) was selected (Le Bertre et al. 2003 ). 3. S-type AGB stars. This class of objects represents the link between O- and C-rich AGB stars and includes two distinct subcategories: (i) the intrinsic S stars are genuine AGB that have their atmosphere enriched by s-process elements brought from the bottom of the convective shell by the third dredge-up process; (ii) the extrinsic S stars have accreted mass from a former AGB companion (now a WD) and generally do not show overabundances of s-process elements. We used the 2nd. edition of the General Catalog of S Stars (Stephenson 1984 ), that contains 1347 stars exhibiting ZrO or LaO bands in their spectra, obtained after various sky surveys. 4. C-rich AGB stars. C-rich stars are the result of the third dredge-up during the thermal-pulse AGB phase, which causes the abundance of carbon to exceed that of oxygen. We adopted a corrected, machine-readable version of the original General Catalog of Galactic Carbon Stars by Stephenson et al. ( 2001 ) available on the Vizier platform, containing 6891 objects. 3. AGB Counterparts in the 4XMM Catalog We cross-correlated the sample of AGB stars described above with the 4XMM-DR9 catalog 3 3 http://xmm-catalog.irap.omp.eu and assumed an X-ray source in this catalog to be a candidate counterpart of an AGB star if their angular distance is within three times the individual positional uncertainty (i.e., 3 × σ pos ). After discarding symbiotic systems, other X-ray emitters, and misclassified AGB stars, we were left with a sample of 19 AGB stars with candidate X-ray counterparts. We then proceeded to download all available XMM-Newton EPIC data of these sources from the XMM-Newton Science Archive (XSA). 4 4 http://nxsa.esac.esa.int/nxsa-web/#home A preliminary inspection revealed that
Paper: 2017MNRAS.470.2069G (fulltext)
the mass, metallicity, effective temperature and individual frequencies in the same manner as before and computed masses and radii using the scaling relations iteratively with the reference functions described in equations ( 3 ) and ( 4 ). The results are shown in Figs 3 and A3 . These figures show that the reference functions that we present here indeed remove trends that are present in the mass and radius determinations as a function of max and mitigate the biases to a large extent. However, the standard deviations from using either equation ( 3 ) or ( 4 ) are very similar and significantly larger than in the ideal case, showing the impact of uncertainties in the observations. Figure 3. Same as Fig. 2 but now with the initial values of T eff , max and [Fe/H] perturbed with typical uncertainties (see the text for more detail). 4.1 Hare-and-hound validation We have thus far demonstrated that the new functions improve mass and radius estimations for the data they fit. In order to prove the general efficacy of our new corrections, we appraise the performance of the functions on data to which they have not been exposed. We perform a series of hare-and-hound validations using stellar models calculated with two additional evolution codes. We used garstec (Weiss Schlattl 2008 ) and mesa (Paxton etal. 2011 ) to compute grids of stellar tracks from which we draw testing data. Over 1000 models from each grid were extracted to serve as hares with the requirement that each selected model falls within the verified mass, metallicity and max ranges of the correction functions. The choice of microphysics and modelling assumptions differ between these two codes and they also differ from the code used to calculate the training data in yrec . Thus, mass and radius predictions of the hares will indicate the degree of stellar evolution code dependence in our function. Both the garstec and mesa grids were computed using OPAL opacities (Iglesias Rogers 1996 ) in conjunction with Ferguson etal. ( 2005 ) tables at low temperatures. We utilized the updated 2005 tables for the OPAL equation of state (Rogers Nayfonov 2002 ) along with the assumption of an Eddington plane-parallel atmosphere. We have taken the recommended nuclear reaction rates from the NACRE collaboration in combination with those from Caughlan Fowler ( 1988 ). The treatment of convection follows the mixing length theory as described by Kippenhahn, Weigert Weiss ( 2012 ) and models were computed with the respective solar-calibrated mixing lengths. Radial mode frequencies were calculated with the adipls pulsation package (Christensen-Dalsgaard 2008 ) for the garstec models and with the gyre pulsation package (Townsend Teitler 2013 ) for the mesa models. The large frequency separation was determined using a weighted median around the scaled max as per Bellinger etal. ( 2016 ). The grids differ in that the garstec models assume Asplund etal. ( 2009 ) solar abundances and were computed without
Paper: 2018ApJ...869..127B (fulltext)
row: particles reach a quasi-steady-state scale height in which downward settling is balanced by upward turbulent diffusion: . Across the columns, we vary the nondimensional turbulent viscosity: . Simulations with radiative damping: we have simulated ZVI with the initial Run_Brunt_Step profile with vertical domains from z = −3 H to z = +3 H for 2000 orbits with nonuniform vertical cooling. The simulations were local at one radius—that is, the radial extent of the computational domain was . Because of additional damping near the vertical boundaries (for stability), the effective domain is . Thick, blue vertical dashed lines indicate simulations that did not develop ZVI, whereas thick, red vertical solid lines indicate that ZVI was triggered and developed into full zombie turbulence. The vertical extent of these lines indicates the effective size of the computational domain. Note that when no part of the computational domain or only a small part of the computational domain extends into the gray region, ZVI is not triggered, while simulations in which the stratified regions of the computational domain have significant overlap with the gray regions do develop ZVI and turbulence. 4.4. Simulations of ZVI with Radiative Damping If the photon mean free path is longer than the largest scale of interest within a flow, then all scales are optically thin and radiative transfer can be modeled with a size-scale independent Newton cooling (i.e., radiated power proportional to temperature difference with respect to some equilibrium value). On the other hand, if the photon mean free path is shorter than the smallest scale of interest within a flow, then all scales are optically thick and radiative transfer can be treated as simple diffusion. A significant challenge is the case where, at the same location in space and time in the flow, small fluctuations are optically thin and large fluctuations are optically thick; using Newton cooling will overdamp large fluctuations, while using a diffusion operator will overdamp small fluctuations. Monte Carlo techniques for radiative transfer are ideal for cases that do not fit safely within the optically thin or optically thick regimes, but these methods involve a substantial investment in additional coding and computational resources. Our goal here is more modest: we want to determine how much radiative damping baroclinic critical layers can withstand and still support the development of ZVI. In Appendix A , we report on simulations with uniform stratification that confirm that ZVI requires Newton cooling times longer than a few orbital periods. In real PPDs, gravity and stratification are not uniform. Not only that, the radiative relaxation time can vary in position within the disk and is especially sensitive to how much the dust has settled. The baroclinic critical layers are most sensitive to radiative cooling; their radial extent is much less than a gas scale height and is expected to be optically thin. Thus we
Paper: 2016ApJ...829..107T (fulltext)
is small compared with the speed of the flow, and the inertial term in Equation ( 2 ) can be ignored. This eliminates the variable, v θ from the induction equation, so it can be rewritten as: Therefore, expansion of the plasma () corresponds to attenuation while compression () corresponds to amplification of b θ . From the preceding discussion it follows that the latter situation is more likely to occur in downdrafts. Equation ( 4 ) looks remarkably similar to the vorticity equation for an incompressible fluid:where ω denotes vorticity in the z direction. The right-hand side of Equation ( 5 ) represents the well-known vortex stretching effect: the angular velocity of a vortex tube increases when it is stretched and decreases when it is compressed (Spurk Aksel 2008 , p. 100). In contrast, Equation ( 4 ) shows that the θ component of the magnetic field increases when the flow decelerates and decreases when it accelerates. The fact that the twist amplification stems from the induction equation emphasizes the magnetic nature of the process. Twist amplification may be thought of as a magnetic analogue of vortex stretching. In a more general situation, when the magnetic field is not weak, the twist evolution requires a more detailed treatment. In the following sections we study the twist amplification analytically as an eigenvalue problem and numerically, and analytically. We also discuss the energy source, and the physics of the amplification process. 3. UNSTABLE TWISTS IN AN EXPONENTIALLY DECAYING DOWNDRAFT The set of governing Equations ( 1 ) and ( 2 ) can be reduced to a single second order PDE for the magnetic field perturbation, b θ (Taroyan 2008 ):where , and . In deriving the above equation, we have used the equation of mass conservation. In a static medium with , the well-known wave equation can be derived from Equations ( 1 ) and ( 2 ): Equation ( 7 ) was first analyzed by Ferraro ( 1954 ) in the context of Alfvén wave propagation in the solar atmosphere. Solutions in terms of the Bessel functions were constructed for an isothermal atmosphere with an exponential density profile:where z 0 is the scale height. The corresponding Alfvén speed is given by:Note that in our notations z denotes depth. Equation ( 7 ) with the profile ( 8 ) was subsequently analyzed by different authors. They found standing wave solutions in terms of the Bessel functions (Ferraro 1954 ; An et al. 1989 ) or propagating wave solutions in terms of the Hankel functions (Hollweg 1978 ; Cally 2012 ) depending on the imposed boundary conditions. An advantage of the smooth exponential profile is the absence of any model dependent artificial reflections that may arise due to discontinuities in the Alfvén speed or its derivatives (Cally 2012 ). One of the drawbacks is the finite Alfvén travel time to (An et al. 1989 ). In studies of the convection zone, it is common to adopt a polytrope with a linear temperature. Here, we adopt the exponential profiles ( 8 ) and ( 9 ) with
Paper: 2021MNRAS.501.5330S (fulltext)
(see Section 2.4 ). For solar metallicity μ converges to ∼2.4 in the CNM, to ∼1.2 in the WIM, and to ∼0.6 in the CGM. As we deal with only low-density environments in the simulations the assumption of an ideal gas is legitimated. Hence, γ = 5/3 in all simulations. 2.2 Self-gravity The effect of self-gravity for an arbitrary matter distribution is described by solving the well-known Poisson’s Equation for the gravitational potential ( G denotes Newton’s gravitational constant). Each mass element of contributes to . If the total mass becomes a significant fraction of the (temperature-dependent) Jeans mass M J for a particular , self-gravity cannot be neglected as it relevantly affects the dynamics of all mass elements. However, it has been shown in Sander Hensler ( 2019 ) that self-gravity has a measurable effect on the evolution of even clouds with masses well below their Jeans mass. If self-gravity is stronger than the acceleration of gas in the opposite direction (e.g. due to evaporation or advection by a streaming CGM), the net acceleration at the cloud surface points in the same direction like the density gradient. Hence, the condition for Rayleigh–Taylor instability (RTI) is not given. So, it is expected that self-gravity significantly suppresses RTI at the cloud surface (see Murray et al. 1993 ) and the typical finger-like structures do not form. According to Murray et al. ( 1993 ), the minimum mass of self-gravitating clouds above which they are stable against Kelvin–Helmholtz instability (KHI) when moving with a certain speed v rel through an ambient medium with density ρ CGM reads with being the average mass density in the cloud. To ensure that self-gravitating clouds, which are embedded in a medium with pressure P CGM , are gravitationally stable initially, their total mass must be below their Bonnor–Ebert mass (Ebert 1955 ; Bonnor 1956 ) Here, and are the average temperature and mean molecular weight in the cloud, respectively. 2.3 Metallicity Observations indicate a common metallicity for CHVCs of 0.1 to (Wakker 2001 ). In order to study extreme cases, we consider two different initial cloud metallicities of and . We note that the CGM has constant metallicity in all runs (see Section 4.3 ). The ratio of the abundances of hydrogen and helium is assumed solar and so are the ratios of metal abundances. 2.4 Dissociation and ionization of elements The simulations contain cool clouds and hot plasma, so a temperature range from a few hundreds up to several 10 6 K is covered. For T 900 K molecules exist, but they successively dissociate and finally become totally ionized with rising temperature. In our simulations, we semi-analytically calculate both dissociation and ionization for hydrogen in thermodynamic equilibrium. The fraction of H ii is then related to He and metals. We note that we do not trace single species but rather have one fluid for which the composition is calculated based upon a given metallicity. The fractions of