adsabs/FOCAL huggingface dataset:
It has been cleared out in the observations that a coronal flux tube could consist of a twisted magnetic field (e.g. Kwon & Chae 2008; Aschwanden et al. 2012; Thalmann et al. 2014; Wang et al. 2015). In a magnetically twisted flux tube, the background magnetic field has an azimuthal component which causes the magnetic field lines to wind around the axis of the tube. The winding number (the number of twist turns around the tube axis) has been reported to have values in the range (0.11, 0.87) (Kwon & Chae 2008). The role of twisted magnetic field in the MHD waves has been studied in many theoretical works (e.g. Bennett et al. 1999; Erdélyi & Carter 2006; Erdélyi & Fedun 2006, 2007, 2010; Ruderman 2007, 2015; Carter & Erdélyi 2008; Karami & Barin 2009; Karami & Bahari 2010, 2012; Terradas & Goossens 2012; Ruderman & Terradas 2015; Ebrahimi & Karami 2016; Ebrahimi et al. 2017; Terradas et al. 2018). Sakurai et al. (1991a) studied resonant absorption of MHD waves in presence of a twisted magnetic field and obtained jumps of the perturbations around the resonance point (see also Sakurai et al. 1991b; Goossens et al. 1992). Ebrahimi et al. (2017) investigated resonant absorption of kink MHD waves and phase mixing of the perturbations in twisted magnetic flux tubes. They showed that depending on the profile of the azimuthal component of the magnetic field and the azimuthal mode number of the global kink wave (m = ±1) magnetic twist can enhance or suppress the decay rate of the kink wave and the rate of phase mixing of the perturbations. Ebrahimi et al. (2017) concluded that even a small amount of twist can have a large impact on the generation of small spatial scales and transferring the wave energy from the global mode to the local Alfvénic oscillations. However, Ebrahimi et al. (2017) neglected the dissipation effects in their analysis. It is known that dissipation could affect the generation of small scales due to phase mixing (McLaughlin et al. 2011; Ebrahimi et al. 2020; Howson et al. 2020).
Citation: Carter & Erdélyi 2008
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Based purely on quality of fits of atmosphere model spectra to observed spectra obtained here, one composition is not preferred over another for the three older CCOs. The primary differences in fit results when the atmosphere is composed of carbon instead of hydrogen are a ∼40 per cent lower temperature and ∼3 times larger emission radius (to maintain nearly constant $R_{\rm em}^2T^4$). The larger Rem could be an argument in favour of carbon because it is closer to the neutron star radius R, which would imply that the entire surface is essentially at a single temperature and would explain non-detection thus far of pulsations from each of these three CCOs. However, a hot region with radius 3–4 times smaller than R can still produce a pulsed fraction below current limits of 20–40 per cent in the spin period range 0.1–0.4 s of known CCOs (see Section 1; for pulsed fraction dependence on spot size, see, e.g. Psaltis, Özel & DeDeo 2000; DeDeo, Psaltis & Narayan 2001; Weinberg, Miller & Lamb 2001; Bogdanov, Grindlay & Rybicki 2008; Lamb et al. 2009; Bauböck, Psaltis & Özel 2015; Elshamouty et al. 2016). For example, Gotthelf, Perna & Halpern (2010) find that a model which includes a hotspot with Rem/R ∼ 0.4 (and a second smaller spot) is able to produce a pulsed fraction that matches the 11 per cent measured for the CCO in Puppis A. Also of note is the stronger limit on the Cassiopeia A CCO pulsed fraction of 12 per cent for P > 0.01s compared to the other CCOs (see Table 1). Meanwhile, a hydrogen atmosphere is a natural consequence of even a very low-level of accretion from the interstellar medium on to a relatively cool neutron star surface several hundred years after neutron star formation (see Section 5.1 for further discussion). Thus from an evolution standpoint, a hydrogen atmosphere for the older CCOs studied here might be preferred. Future measurements of pulsations or improvements to pulsation constraints could provide stronger indications of their atmosphere composition.
Citation: Weinberg, Miller & Lamb 2001
Citation function: Uses
In particular, two main scenarios have emerged: the first one attributes differences in radio morphology to the large-scale (i.e., host galaxy and environment, see also below in this Section) properties of radio-AGN which influence the interaction between the radio jet and the external medium (e.g., Kaiser and Best 2007; Wing and Blanton 2011; Miraghaei and Best 2017; Mingo et al. 2019, 2022), with those between HERGs and LERGs being instead dictated by different fuelling mechanisms as discussed earlier. According to this framework, HERGs are powered by accretion of cold gas, provided by e.g., a recent merger with a gas-rich galaxy, while LERGs accrete hot intergalactic gas from dense environments at a low rate (e.g., Best and Heckman 2012), with fuelling from major mergers strongly disfavoured by recent observations (e.g., Ellison et al. 2015). On the other hand, other works do not observe any difference in the host and/or environmental properties of FRI and FRII galaxies, except in the rare cases of FRII HERGs (e.g., Lin et al. 2010; Capetti et al. 2017b; Jimenez-Gallardo et al. 2019; Massaro et al. 2019, 2020; Vardoulaki et al. 2021) or even between those of HERGs and LERGs (e.g., Fernandes et al. 2015), so that an alternative mechanism for their large-scale radio behaviour has to be invoked. In this case, ageing processes can be thought as the main driver for the observed morphological differences, with an evolutionary pattern that proceeds from FRII HERGs that switch from efficient to inefficient accretion due to gas starvation and transform themselves into FRII LERGs, sources that still maintain their large radio structures thanks to the past nuclear activity at high efficiency (e.g., Ghisellini and Celotti 2001; Tadhunter 2016; Macconi et al. 2020; Grandi et al. 2021). The switch off/change in accretion mode will eventually show in the radio morphology with the delay needed to reach Kpc-to-Mpc distances, and the source will ultimately turn into an FRI galaxy.
Citation: Ellison et al. 2015
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In our simulations, we assumed that the growth of dust grains and planetesimals occurred during the first stages of planetary accretion. Thus, we used a bimodal disc composed of embryos (60 per cent of the disc’s mass) and planetesimals (40 per cent of the disc’s mass; Izidoro et al. 2015). It was assumed that embryos are formed by oligarchic growth and are thus spaced randomly by 5–10 mutual Hill radii (Kokubo & Ida 1998, 2000) with a density of 3 g cm−3. The mass of each planetesimals is ≈ 0.002 M⊕. In the numerical integrations, the planetesimals do not have gravitational interactions with themselves but only with stars, planets, and protoplanetary embryos. The protoplanetary embryos masses scale as M ≈ r3(2 − x)/2Δ3/2 (Kokubo & Ida 2002; Raymond, Quinn & Lunine 2005; Raymond et al. 2009; Izidoro et al. 2015), where Δ is the mutual Hill radii separations between embryos orbits. As we are using distinct systems with different parameters, the number of embryos and planetesimals are not the same among the systems; see Table 4. Fig. 5 shows the initial conditions of x = 1.5 and 2.5, for all our simulations. Discs with x = 2.5 have embryos more massives in the inner region of the disc, and with 1.5 in the outer region. We chose these two values of the parameter x, besides being used frequently in some works (Raymond, Quinn & Lunine 2004; Raymond et al. 2005; Izidoro et al. 2014a,2015; Izidoro, Morbidelli & Raymond 2014b; Izidoro & Raymond 2018), to study the dynamic evolution in discs that have mass growing as a function of the orbital radius of the bodies and in cases where the mass decreases as a function of the orbital radius (see Fig. 5). This is an important point because we have some systems where the giant planet is in the inner region of the disc and others in the outer region. So we needed to consider the two cases for all systems. The orbital inclination of the embryos and planetesimals is chosen randomly between $10^{-4}\, ^{\circ }$ and $10^{-3}\, ^{\circ }$ with respect to the binary plane, and the eccentricity is chosen between 0 and 0.01.
Citation: Raymond et al. 2009
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The specific radiance received from the optically thin dust plume can be expressed as
(1)
\begin{equation}
L_\lambda =f_{\rm plume}\frac{p}{\pi } \frac{\phi (\alpha )}{\phi (0)} \frac{f_{\lambda }}{r_{\rm h}{^2}} 
\end{equation}
where p is the geometric albedo of the dust particles at wavelength λ, ϕ(α) is the phase function at phase angle α, fλ is the solar irradiance (in W m−2 nm−1 at 1 au), rh is the heliocentric distance in au and fplume is the dust filling factor (e.g. the fraction of a pixel covered by dust). Assuming that the geometric albedo of the dust particles is similar to that of the nucleus, the geometric albedo and specific solar flux are 0.068 and 1.513 W −2 nm−1 for the orange (648.6 nm) filter, and 0.027 and 0.23 W −2 nm−1 for the UV (270.7nm) filter (Fornasier et al. 2015), respectively. The flux ratio ϕ(α)/ϕ(0) can be derived by using the dust phase function (Kolokolova & Kimura 2010). By integrating the radiance over the image area (e.g. within the boxes in Fig. 7) containing the dust from a difference outburst plume, the total cross-section from difference images of the dust jet from within a given time interval can be determined. Then, we used a power-law index g = 3.7 for the size distribution with a constant bulk density of 1000 kg m−3 for all ejected particles. The ejected mass in size interval of a1  a  a2 (i.e. 1 μm to 1 mm) is given by
(2)
\begin{equation}
M=\frac{({4}/{3})\pi \rho N}{4-g} \left(a_2^{4-g}-a_1^{4-g}\right), 
\end{equation}
where N is the total number of dust particles in the size interval 1 μm to 1 mm. The estimated dust cross-section and ejected mass are given in Table 2. The uncertainty of the ejected mass is typically of the order of 5–10 per cent, depending on the uncertainty on the brightness integration of the selected box. The averaged mass ejection rate for the outbursts can be estimated from the ejected mass (M) by dividing by the time interval between the difference images. Note that our calculation is based on the chosen time intervals and hence produces lower limits on the mass ejection rates. For example, the estimation of the ejected mass for a major outbursts on July 29 is about 4550 kg. Given a time interval of 18 min, the average mass ejection rate would be of the order of 4 kg s−1. However, if this outburst lasted for a time interval of 5 min only, which is the cadence for the outburst sequence, the corresponding mass ejection rate would be as much as 15 kg s−1.
Citation: Kolokolova & Kimura 2010
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The plethora of cosmological observations has turned cosmology into a quantitative science. From combining several probes that observe the Universe at different epochs and have different systematics and statistics, emerged the ‘concordance model’ of cosmology, a six parameter model, most of them measured to the accuracy of a per cent. Among these probes, Type Ia supernovae (SNe) are a powerful cosmological tool to directly measure the expansion history of the Universe (see e.g. a recent review of Weinberg et al. 2013). The type Ia SNe are known to be standard candles and one can measure the luminosity distances to them accurately. Several SNe surveys have set strong constraints on cosmological models from the distance–redshift relation (e.g. Riess et al. 1998; Perlmutter et al. 1999; Riess et al. 2007; Sullivan et al. 2011; Campbell et al. 2013). However the measured apparent magnitudes, have a residual scatter arising from its intrinsic scatter and effects due to line-of-sight (LOS) structures. The intrinsic scatter (∼0.4 mag) can be significantly reduced to ∼0.1 mag by empirically calibrating the luminosity curves. The scatter due to photon deflection along the LOS is composed of many different physical effects. The dominant effects are peculiar velocities at z  0.1 and gravitational lensing at z ≳ 0.3. Within the realm of cosmological perturbation theory and the stochastic nature of the LOS structures, all effects are expressed as an integral over the power spectrum with appropriate kinematical factors (Ben-Dayan et al. 2012). The lensing effects create residuals from the best-fitting curve in the magnitude–redshift relation. The lensing magnifications of SNe can be extracted by correlating the residuals with the surface densities of nearby foreground galaxies. The lensing dispersion is roughly proportional to the SNe redshift z, (e.g. Holz & Linder 2005; Ben-Dayan et al. 2013), and specifically for the concordance model, the predicted value is ∼0.06z mag.
Citation: Riess et al. 1998
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The results of Ivanova et al. (2003) are somewhat closer to ours. A remaining key difference is that Ivanova et al. (2003) find that their calculated mass-transfer rates for systems with initial orbital periods, Porb, i  0.4 d sometime exceed a critical mass-transfer rate, $\dot{M}_{\rm crit}$ related to the location of the so-called trapping radius (e.g. Begelman 1979; Chevalier 1993; MacLeod & Ramirez-Ruiz 2015b). In systems with very large super-Eddington mass-transfer rates, matter presumably piles up around the NS and forms a growing, bloated cloud engulfing a large fraction of the accretion disc. A system will only avoid a CE if it manages to evaporate the bulk of the transferred matter via the liberated accretion energy at a distance from the NS larger than the trapping radius. Otherwise, the incoming material has too much negative binding energy to be ejected. At the same time, this trapping radius must be located inside the Roche lobe of the NS in order to avoid a CE (King & Begelman 1999). The exact location of the trapping radius, and thus the value of $\dot{M}_{\rm crit}$, is difficult to calculate because it also depends on the cooling processes of the infalling gas (Narayan & Yi 1995; Blandford & Begelman 1999). Nevertheless, in all of our models presented in Table 1 with Porb, i > 0.06 d we find that $|\dot{M}_{\rm He}^{\rm max}|\le \dot{M}_{\rm crit}$, where $\dot{M}_{\rm crit}$ is calculated from equation 15 in Ivanova et al. (2003), and varies from about 3.7 × 10−3 M⊙ yr−1 (for Porb, i = 2.0 d) to 4.3 × 10−4 M⊙ yr−1 (for Porb, i = 0.08 d). Only for Porb, i = 0.06 d, we find a couple of systems where $|\dot{M}_{\rm He}^{\rm max}|> \dot{M}_{\rm crit}$. However, these systems are anyway found to result in a runaway mass transfer and thus formation of a CE. Therefore, our calculated mass-transfer rates from the helium stars donors must be slightly smaller than those calculated by Ivanova et al. (2003). The reason for this, besides from using different stellar evolution codes, is perhaps that our mass-transfer rates are calculated using the prescription by Ritter (1988) whereas Ivanova et al. (2003) adopted the prescription by Tout & Eggleton (1988). To summarize, we caution that all numerical calculations of Case BB RLO could potentially be affected by uncertain accretion processes at high mass-transfer rates exceeding the Eddington limit by ∼4 orders of magnitude.
Citation: King & Begelman 1999
Citation function: Compare/Contrast
Utilizing the full range of peak absolute magnitudes observed in LBV stars [M ≃  (−13)–(−9) mag; e.g. Smith et al. 2011b] provides a range of peak apparent magnitudes of m ≃  16.5–20.5 mag, for a distance of D ≃ 8 Mpc (Table 1). Hence, if the transient source (m ≈ 21.0 mag; Section 2.1.2) is an LBV star, it must have been observed a short time after its peak (Fig. 2; left-hand column; rows 4–5); quiescent LBV stars can have absolute magnitudes as low as M ≃ −6 mag (e.g. Smith et al. 2011b), or m ≃ 23.5 mag (for a distance of D ≃ 8 Mpc; Table 1). An LBV star provides an adequate explanation for the transient time-scale, the isolation (e.g. Smith & Tombleson 2015; Smith 2016), the lack of a host H ii region (Fig. 2 and 3; see below, however), and the transient/main source offset (d ≈ 0.3 kpc, for D ≃ 8 Mpc; Table 1; see below, however). In addition, (net) fading of the LBV peak event by Δm ≲ 3 mag (over a period of approximately 40 yr) may possibly produce an apparent brightness centroid shift/morphology variation in the main source (Sections 2.1.2 and 2.1.3). However, this scenario has its caveats. First, it is difficult to interpret the flux variability of the main source (Sections 2.1.4 and 2.3.1) within such a context. Secondly, although a fraction of LBV stars are isolated (e.g. Smith & Tombleson 2015; Smith 2016), in the only XMP with a documented LBV star, the LBV star appears embedded within an H ii region (DDO 68; Pustilnik et al. 2017); no clear H ii region at the location of the transient source is discernible in the HST images (Fig. 3; top), although it should be detectable given the typical lifetime of an H ii region (few Myr; e.g. Alvarez, Bromm & Shapiro 2006). Thirdly, a (net) magnitude variation of Δm ≲3 mag of the transient over a period of approximately 60 yr would result in a quiescent LBV source (m ≲ 23.5 mag) that should have been detectable in the HST images (Fig. 3; top). Lastly, as LBV stars brighten, they become redder (e.g. Sterken 2003), which appears to contradict the POSS data (Table 2; Fig. 2; rows 2–5). Consequently, as the LBV scenario explains some of the observables challenged by other scenarios (e.g. transient timeline), it remains a contender for the observed phenomenon.
Citation: Smith & Tombleson 2015
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Citation: Smith & Tombleson 2015
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In particular, the presence of slow magneto-acoustic-gravity waves (MAG waves, hereafter) guided by the magnetic field is supported by increasingly observational evidence in different atmospheric structures, e.g. photospheric flux tubes (Roberts & Ulmschneider 1997), sunspots (Jess et al. 2013; Freij et al. 2014; Khomenko & Collados 2015; Madsen, Tian & DeLuca 2015), coronal loops (King et al. 2003), and coronal plumes (Nakariakov 2006). These oscillations are also used to estimate the formation heights of different emission spectral lines. As a result of the analysis of 3 min oscillations detected in observations from the Atmospheric Imaging Assembly instrument (AIA; Lemen et al. 2012) on-board the Solar Dynamic Observatory (SDO; Pesnell, Thompson & Chamberlin 2012), Deres & Anfinogentov (2015) found that the formation heights of the corresponding spectral lines are consistent with models of the sunspots umbra involving strong temperature gradients of the type used in this paper (e.g. Fontenla et al. 2009). Meanwhile the lower atmospheric magnetic structure is frequently believed to be mostly formed by small magnetic flux tubes of circular cross-section emerging from the photosphere and expanding upwardly in the corona (Solanki, Inhester & Schüssler 2006). The photosphere and chromosphere are known to be dominated by acoustic-gravity waves with observed short periods of ∼[3–5] min. Whereas in the lower corona a wider range of periods are present (up to about 80 min – e.g. Sakurai et al. 2002–), short periods ([3–5] min) have also been detected in certain coronal structures, e.g. coronal loops and intense magnetic flux tubes (Srivastava & Dwivedi 2010; Jess et al. 2012; Reznikova et al. 2012). A rich range of periods are found in sunspots, the periods becoming larger as the distance from the sunspot umbra increases; a likely result of the influence of the magnetic field (Bogdan & Judge 2006; Jess et al. 2013; Yuan et al. 2014; Madsen et al. 2015).
Citation: Pesnell, Thompson & Chamberlin 2012
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The chemical composition of protostellar envelopes and their properties along the evolutionary stage of protostars is an important topic in astrochemistry. Since the pioneering work by Cazaux et al. (2003) and Sakai et al. (2008), systematic chemical studies of solar-type protostars (see Ceccarelli et al. 2007; Caselli & Ceccarelli 2012 for a review; also Lefloch et al. 2018) have identified two classes of objects. The first class corresponds to the so-called “hot corinos”, that is, sources which display a rich content in complex organic molecules (COMs) in the central inner regions of the protostellar envelope (see Ceccarelli et al. 2007 for a review; also Taquet et al. 2015). Only a few hot corinos have been identified so far either with single dish or interferometric observations: IRAS16293-2422 (Cazaux et al. 2003; Bottinelli et al. 2004b; Jørgensen et al. 2011, 2016), IRAS2, IRAS4B (Bottinelli et al. 2007), IRAS4A (Bottinelli et al. 2004a; Taquet et al. 2015), HH212 (Codella et al. 2016), L483 (Oya et al. 2017), B335 (Imai et al. 2016), SVS13A (Bianchi et al. 2017), Serpens SMM1, and SMM4 (Öberg et al. 2011). We note that very few sources were investigated in a systematic manner meaning that the COM budget in hot corino sources is very inhomogeneous, making a general picture difficult to come by. Hot corinos share some similarities with the hot cores observed around high-mass stars but they are not scaled-down versions of these. Bottinelli et al. (2007) showed that the abundances of O-bearing species scaled to methanol are higher than those measured in hot cores by one to two orders of magnitude or more. The second chemical class of protostars corresponds to the so-called Warm Carbon Chain Chemistry (WCCC) sources, which have a rich content in C-chains but are poor in COMs. A recent survey of a sample of 36 Class 0/I protostars of the Perseus molecular cloud complex by Higuchi et al. (2018) shows that the majority of the sources observed have intermediate characters between these two distinct chemistry types.
Citation: Codella et al. 2016
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