adsabs/FOCAL huggingface dataset:
Among the suggestedmechanisms responsible for the strong damping of the coronal loop oscillations (e.g., Ruderman & Roberts 2002; Ofman 2005, 2009; Morton & Erdélyi 2009) resonant absorption of the MHD waves, which was established first by Ionson (1978), is a strong candidate. Several works developed this theory (e.g., Davila 1987; Sakurai et al. 1991a, 1991b; Goossens et al. 1995; Goossens & Ruderman 1995; Erdélyi 1997; Cally & Andries 2010). The necessary condition for the resonant absorption is a continuum of Alfvén or slow frequency across the loop (Ionson 1978; Hollweg 1984, 1987; Davila 1987; Sakurai et al. 1991a). Resonant absorption occurs when the frequency of the global MHD mode matches at least with one of the frequencies of the background Alfvén or slow continuum at a location called he resonance point. As a result, the energy of the global MHD mode transfers to the local Alfvén modes in a layer around the resonance point, named the resonance layer (Lee & Roberts 1986; see also Goossens et al. 2013; Soler & Terradas 2015). In the absence of dissipation mechanisms, the amplitude of the oscillations diverges at the resonance point. Dissipation is important in the resonance layer, where the oscillations make large gradients. The background Alfvén or slow continuum can be due to the variation of the plasma density (e.g., Davila 1987; Ofman et al. 1994; Ruderman & Roberts 2002; Terradas et al. 2006; Soler & Terradas 2015), twisted magnetic field (Ebrahimi & Karami 2016), or both of them together (Karami & Bahari 2010; Giagkiozis et al. 2016). There are a variety of theoretical works related to the damping of the coronal loop oscillations based on the theory of resonant absorption of MHD waves (e.g., Goossens et al. 2002, 2009; Ruderman & Roberts 2002; Van Doorsselaere et al. 2004; Andries et al. 2005; Terradas et al. 2006; Karami et al. 2009; Karami & Bahari 2010; Soler et al. 2013; Soler & Terradas 2015; Ebrahimi & Karami 2016; Giagkiozis et al. 2016; Jung Yu & Van Doorsselaere 2016). For a good review about the theory of resonant absorption, see also Goossens et al. (2011).
Citation: Soler & Terradas 2015
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In Fig. 20, we show two volumes containing filaments which are almost aligned to the sky plane, as an example to illustrate the implications of this effect on the rotation measurement of such objects. The top panels show the projected maps of density, RM and ε for the four Chronos simulations. In presence of a large degree of alignment between magnetic fields and filaments, we therefore expect the magnetic field to mostly lie in the sky plane as well, with a very small line-of-sight component, thereby reducing the observable |RM| towards the observer. Current instruments (e.g. VLA and LOFAR) are able to detect values of |RM| ≳ 5 rad/m2 (e.g. Bonafede et al. 2013; O’Sullivan et al. 2019; Locatelli, Vazza & Domínguez-Fernández 2018). The Figure suggests that, on one hand, clusters easily meet this requirement, while filaments would only be marginally detected, even for the runs in which the magnetic field is stronger (baseline and Z), due to the large degree of $\boldsymbol {B}$-filament alignment, which implies low values of ε, as can be seen in the third column. Therefore, the small line-of-sight component yields only little |RM|, typically below the detection threshold of present instruments, especially for runs in which the magnetization is weak already (DYN5 and CSFBH2). On the bottom panels we give, for each of the two selected areas, the median value of ε as a function of the rotation measure (in absolute value). The highest values of |RM|, mostly associated to clusters, correspond to higher values of ε, although never approaching ε ≈ 1; at the lower side of |RM|, corresponding to the areas populated by filaments, lower values of ε are found, as expected from our previous considerations. The simulations are in overall agreement, except for CSFBH2, where AGN and star formation feedback introduces additional effects: although the impact of a quasi-parallel $\boldsymbol {B}$-filament configuration is noticeable for a larger sample of objects (e.g. see Fig. 18), the bursty and random occurrence of star forming/AGN events may strongly affect the local magnetic field topology and cause the statistic over a small volume to deviate from the expected trend.
Citation: O’Sullivan et al. 2019
Citation function: Uses
Using the constrained hyperbolic divergence cleaning scheme with variable cleaning speed from Tricco et al. (2016), we can keep the divergence error low in all cases. The mean normalized divergence error, ⟨ϵdivB⟩=⟨h|∇ ⋅ B|/|B|⟩, is typically of order 10−5 − 10−3. In Fig. 17, we show the normalized divergence error maps for several test problems. Again we see that the divergence cleaning works extremely well here, the maximum error is generally around 10−2. Comparing to Hopkins (2016, their Fig. 4), we find that the errors are smaller than their MFM simulations with the Dedner et al. (2002) cleaning in general, with an exception for the outskirt of the advection loop (where the magnetic field is essentially zero and thus not important for the result). The improvement is probably due to the more advanced constrained cleaning method (Tricco et al. 2016). The normalized divergence error for the μ = 10 cloud-collapse case at the jet launching time is shown in Fig. 18. Here, the divergence cleaning still performs very well in the disc, along the jets and for the majority of the regions where the outflow interacts with the ambient gas, especially when the divergence error is compared to the total gas pressure (right panel). The result is similar to the Dedner cleaning in Hopkins (2016), although our error is somewhat larger at the tip of the jets where the gas is shocked. However, we note that the comparison is not direct in this case as the jets may develop differently. Overall, the result from cleaning is still worse than the constrained transport or constrained gradient schemes (Hopkins 2016). For SPMHD, as shown in Tricco & Price (2012), divergence errors can be reduced to machine precision (or more practically to a certain tolerance value) using cleaning, with the help of a sub-cycling routine. However, local adjustments are required to determine the number of iterations for each particle to efficiently subcycle the cleaning in the simulation. This is because certain regions are more affected than others and because divergence is spread to nearby neighbours. Conceivably, if vector potentials (Stasyszyn & Elstner 2015) could work for a wider range of problems this could be an interesting avenue as well. However, the exploration of these methods in detail is beyond the scope of this work.
Citation: Tricco et al. 2016
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Citation: Tricco et al. (2016)
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To check for any spectral variation in the optical/IR bands, we looked for variation in the V − J band colour against the V-band brightness. This colour variation was analysed for the epochs A, B, D, and E. During epochs A and B, the source showed a ‘redder when brighter’ (RWB) behaviour. During epoch E, a bluer when brighter behaviour was observed. During epoch D, we observed a complex behaviour. Upto a V-band brightness of around 15 mag, the source showed a ‘bluer when brighter’ behaviour, but for optical brightness fainter than 15.0 mag, a ‘redder when brighter’ behaviour was observed. The colour–magnitude diagrams for all the four epochs are shown in Fig. 10. The spectral variations shown by the source are thus complex. From studies on the optical–IR colour–magnitude diagram, it is known that FSRQs in general show an RWB trend, which is attributed to them having a luminous accretion disc (Gu et al. 2006; Bonning et al. 2012). The observed optical emission is a combination of thermal blue emission from the accretion disc and non-thermal red emission from the jet. As the source gets brighter, the non-thermal emission has a more dominant contribution to the total flux, giving rise to the RWB behaviour (Bonning et al. 2012). During epochs A and B, there is a trend of the object to become RWB, irrespective of its optical brightness. The optical flares dominated by synchrotron emission processes during A and B have corresponding γ-ray flares that are produced by EC processes. However, during epochs D and E, the colour variations were found to depend on the optical brightness. During the epochs when this complex spectral behaviour was noticed, the source showed an optical/IR flare with no or a weak corresponding flare in the γ-ray band. The source showed a much larger amplitude of variability in the optical/IR bands, while in the γ-ray band it was either faint or below the detection limit of Fermi. This definitely points to some complex physical changes and could be due to a combination of changes in the bulk Lorentz factor, electron energy density, and magnetic field as seen from our SED modelling of the multiband data.
Citation: Bonning et al. 2012
Citation function: Compare/Contrast
Dense gas-fraction and the star-forming fraction. As in Paper I we define the dense gas-fraction, Mfrac, as the fraction of gas having density, n ≳ 103 cm−3 and being colder than ∼50 K. Although somewhat ad hoc, this density and temperature threshold is good enough to estimate the fraction of gas likely to end up in putative star-forming clumps (e.g. Ragan et al. 2016 and other references therein). Furthermore, we also use a higher density threshold, n ≳ 104 cm−3, to trace the fraction of strongly self-gravitating gas in a pristine cloud. In typical star-forming clouds such dense pockets of gas are traced due to emission from molecules such as HCN, HNC and HCO+ (e.g. Gao & Solomon 2004, Usero et al. 2015 and Biegel et al. 2016). The dense gas fraction, Mfrac$\equiv \frac{M_{\text{thresh}}(n \gtrsim 10^{3} \mathrm{cm}^{-3}, 10^{4} \mathrm{cm}^{-3}; 50 \mathrm{K})}{M_{\text{gas}}}$, for each choice of bimpact is shown on the upper panel of Fig. 6. Irrespective of the choice of the impact parameter and the density threshold, n, the fraction, Mfrac, increases steadily with time, but at best cycled a little under ∼ 10 per cent of the gas into the dense-phase at the time calculations were terminated. Indeed, this fraction is significantly smaller in the realization where the inflows merely grazed past each other. While the fraction of gas cycled into the dense phase could possibly increase as the post-collision slab continues to accrete gas from the colliding flows, it is unlikely to exhibit a dramatic increase. This is because the NTSI destabilises the shocked slab and causes fluid layers to mix, thereby rupturing the dense pockets of gas. In any case, it is evident that grazing inflows are most inefficient in cycling gas into the dense phase. The fraction of gas cycled to densities higher than ∼104 cm−3 is typically an order of magnitude smaller. Evidently, star formation in a pristine cloud must be quite inefficient. We also note, irrespective of the choice of the density threshold and the impact parameter, the characteristics of the dense gas fraction look mutually similar. This is because whatever the choice of the pre-collision impact parameter, the fraction of gas cycled into the dense phase is limited by shearing interaction between layers of gas in the shocked slab. The source of shear, however, is different in the extreme scenarios of near head-on collision and one in which the gas flows merely graze past each other. In the former, shear is induced by the growth of the NTSI while in the latter, it is the obliqueness of the collision that induces a strong shearing interaction between layers of gas.
Citation: Gao & Solomon 2004
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The radius estimate of the X-ray emitting area is small compared to the size of a neutron star, which typically has a radius of 10–14 km. The emission is therefore likely to be coming from the polar caps of PSR J1909–3744, as is expected from such old objects where the surface of the neutron star has cooled so that it is no longer detectable in the X-ray band. The emitting radius is somewhat smaller than the classical radius of a polar cap, 




R
pc

=



2
π
R


cP



R


$ R_{\mathrm{pc}}= \sqrt{\frac{2 \pi R}{c P}} R $


 (e.g. Dermer & Sturner 1994), where R is the neutron star radius, c the speed of light in a vacuum and P the rotation period of the neutron star. The latter is ∼2.9 km if we suppose a 10.6 km radius for the PSR J1909–3744 neutron star, the average of the best radius values for a neutron star of M = 1.5 M⊙ as determined by Özel et al. (2016b) who undertook a comprehensive study of 12 neutron stars. Considering the range of typical radii of neutron stars (10–14 km), the classical polar cap radius is between 2.7 and 4.4 km. Bogdanov et al. (2006) state that the radius determined through fitting the pulsar spectrum can be smaller than expected when the spectrum has been fitted with a single-temperature model, but that a higher signal-to-noise spectrum would require a two-temperature model, as for PSR J0030+0451, PSR J2124–3358 (e.g. Bogdanov et al. 2008), and PSR J0437–4715 (Bogdanov 2013). Fitting the spectrum with two black bodies does not improve the fit, again probably due to the low signal-to-noise ratio. Further, it is known that the radii of neutron stars are underestimated when using a black-body model as opposed to a realistic neutron star atmosphere model (e.g. Heinke et al. 2006). However, assuming the classical radius of the polar cap for this neutron star (2.9 km) in the nsatmos model provides a poor fit to the data with a C-statistic = 171.6, 33 degrees of freedom, suggesting that such a radius is too large. In fact, the nsatmos model produces a polar cap with size ∼100–400 m, slightly larger than the ∼50–300 m radius obtained with the black-body model (see Fig. 4).
Citation: Özel et al. (2016b)
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Figure 3 (left) shows the moment zero map of the SiO (5–4, Eu = 31.26 K) emission integrated over the central ~3 km s−1 of the line covering the VLSR, between 21.4 and 24.0 km s−1. In contrast to Cesaroni et al. (2017), here we integrate the SiO emission over a narrower velocity range to highlight the elongated structure at near VLSR velocities. The elongated structure of the emission is clearly visible and perpendicular to the large-scale outflow (Fig. 2). Fitting the integrated SiO emission with a 2D Gaussian in the image plane indicates a PA of ~ 47 ± 7° and a major axis of ~0.28″ (~600 au). The deconvolved PA is 30 ± 10° consistent with the PA of the dust continuum emission. The SiO emission is broad in velocity, ranging from −3.0 to 45.7 km s−1 considering emission above 3 σ, this is broader than presented in Cesaroni et al. (2017), 4–39.1 km s−1, owing to our improved images after self calibration. In most massive YSOs, SiO is very spatially extended, typically tracing emission at shock fronts (e.g. Schilke et al. 1997) created by active jets and outflows driven by the energetic central sources (e.g. Cabrit et al. 2007; Sánchez-Monge et al. 2013b; Duarte-Cabral et al. 2014; Klaassen et al. 2015; Cunningham et al. 2016; Cesaroni et al. 2017; Beltrán et al. 2018; Moscadelli et al. 2018). In at least one massive YSO, Orion source I, the SiO emission is rather compact, associated with SiO masers and is shown to trace a rotating disc and disc wind structure (Goddi et al. 2009; Ginsburg et al. 2018). The SiO emission from G17.64 is also relatively compact, unlike a jet. There is also compact emission from other silicon and sulphur bearing species in our observations, emission from SiS (v = 0 12–11, Eu = 69.95 K) and 33SO (65 –54, Eu = 34.67 K) are centrally peaked at the location of the continuum and SiO emission. The strong detection of SiO points to a reservoir of silicon in the gas phase, which, in addition to the detected sulphur-bearing species, suggest an association with ionised, hot (>100 K), turbulent and shocked gas (e.g. Minh et al. 2010; Minh 2016) where these species are released from the grain material.
Citation: Schilke et al. 1997
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In recent decades, radio interferometers, such as the Karl G. Jansky Very Large Array (VLA), Australia Telescope Compact Array (ATCA), and Giant Meterwave Radio Telescope (GMRT), have surveyed fields of different sizes (ranging from tens of square arcminutes to thousands of square degrees), depths (microjansky to jansky), and multiwavelength coverage (e.g., Becker et al. 1995; Condon et al. 1998, 2003, 2012; Ciliegi et al. 1999; Georgakakis et al. 1999; Bock et al. 1999; Prandoni et al. 2001; Hopkins et al. 2003; Schinnerer et al. 2004; Bondi et al. 2003, 2007; Norris et al. 2005; Schinnerer et al. 2007, 2010; Afonso et al. 2005; Tasse et al. 2007; Smolčić et al. 2008, 2014; Owen & Morrison 2008; Miller et al. 2008, 2013; Owen et al. 2009; Hales et al. 2014). These past surveys have shown that deep observations at high angular resolution (≲1″) with exquisite panchromatic coverage are critical to comprehensively study the radio properties of the main galaxy populations, avoiding cosmic variance with large area coverage (e.g., Padovani et al. 2009; Padovani 2011; Smolčić et al. 2008, 2009b,a; Smolčić 2009; Smolčić & Riechers 2011; Seymour et al. 2008; Bonzini et al. 2012, 2013). In this context, large area surveys down to unprecedented depths are planned with new and upgraded facilities (e.g., VLA, Westerbork, Australian Square Kilometre Array Pathfinder, MeerKAT, and Square Kilometre Array; e.g., Jarvis 2012; Norris et al. 2011, 2013, 2015; Prandoni & Seymour 2015). Figure 1 shows the 1σ sensitivity of each survey as a function of the area covered for past, current, and future radio continuum surveys. The VLA-Cosmic Evolution Survey (COSMOS) 3 GHz Large Project bridges the gap between past and future radio continuum surveys by covering an area as large as two square degrees down to a sensitivity reached to date only for single pointing observations. This allows for individual detections of >10 000 radio sources, further building on the already extensive radio coverage of the COSMOS field at 1.4 GHz VLA (VLA-COSMOS Large, Deep and Joint projects; Schinnerer et al. 2004, 2007, 2010), 320 MHz VLA (Smolčić et al. 2014), 325 MHz and 616 MHz GMRT data (Tisanić et al., in prep.), 6 GHz VLA (Myers et al., in prep.), and the deep multiwavelength X-ray to mm photometry (Scoville et al. 2007; Koekemoer et al. 2007; Hasinger et al. 2007; Capak et al. 2007; Sanders et al. 2007; Bertoldi et al. 2007; Elvis et al. 2009; Ilbert et al. 2013; McCracken et al. 2012; Scott et al. 2008; Aretxaga et al. 2011; Smolčić et al. 2012; Miettinen et al. 2015; Civano et al. 2016; Laigle et al. 2016, Capak et al., in prep.) and more than 97 000 optical spectroscopic redshifts (Salvato et al., in prep.; zCOSMOS, Lilly et al. 2007, 2009; Trump et al. 2007; Prescott et al. 2006; Le Fèvre et al. 2015; Aihara et al. 2011; Nagao et al., priv. comm.). This further makes the survey part of one of the richest multiwavelength data sets currently available.
Citation: Smolčić & Riechers 2011
Citation function: Motivation
In this paper, our primary interest is in determination of plasma temperatures, in particular the characterization and measurement of high-temperature lines and continuum in the Chandra/HETGS spectrum of ζ Pup. If X-ray emission originates solely from embedded-wind shocks (Lucy & White 1980; Feldmeier et al. 1995), then the maximum temperature is determined by the highest relative velocities of the colliding structures, and the amount of emission is indicative of the emitting volume. Hot thermal plasmas emit strongly in bound–bound lines of highly ionized states, in thermal Bremsstrahlung radiation, and in bound-free continuum emission. Bremsstrahlung and bound-free emission drop exponentially for photon energies larger than about kT of the plasma (in which k is Boltzmann’s constant and T is the plasma temperature). For some plasma temperatures, bound-free emission can exceed that from thermal Bremsstrahlung at high energies (Landi 2007; Kaastra et al. 2008). However, the continuum shape is similar to that from Bremsstrahlung. The drop in the spectrum at high energies (short wavelengths) is sensitive to the hottest temperatures present in a multithermal plasma. Thermal emission lines are also very sensitive to temperature, having temperatures of peak emissivities that increase with atomic number; they typically emit most strongly over a range in temperature of about 0.3 dex (defined by the full width at half maximum of their emissivity curves). Hence, we concentrate here on the 2–9 Å region due to the relative sparseness of emission lines, the high-temperature sensitivity, and the reduced importance of wind absorption. The temperature sensitivity occurs because for the expected plasma temperatures from embedded-wind shocks (2–10  MK), the spectrum will drop accordingly somewhere in the 1–10  Å range. In this regime, the wind absorption is relatively unimportant since the continuum opacity (due mainly to K-shell absorption by metals) drops very steeply to short wavelengths, so we do not have to be concerned with the wind density structure to interpret the spectral shape.
Citation: Kaastra et al. 2008
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NGC 3079 is a well-known nearby (z = 0.003723) Seyfert 2/LINER galaxy with a nuclear starburst, which is a member of an interacting galaxy pair. It is an edge-on spiral galaxy with several regions of star formation along the disk. Its eight-shaped radio structure with a ring-like feature (ring hereafter) inside its northeast lobe (Duric & Seaquist 1988; Irwin & Saikia 2003; Wiegert et al. 2015; Irwin et al. 2019), its slow-moving (v ∼ 0.1c) parsec-scale radio jet (Irwin & Seaquist 1988; Baan & Irwin 1995; Middelberg et al. 2005), and copious amount of hot X-ray gas and emission-line filaments (Cecil et al. 2001, 2002) have been well documented. NGC 3079 is a Compton-thick AGN (Iyomoto et al. 2001) having a disk-like pseudo-bulge. The origin of the double-lobed morphology observed in NGC 3079 is not yet completely understood. Duric & Seaquist (1988) argue that the lobe material is moving at supersonic velocities, though they dismiss the possibility that these are jets that may be precessing based on the difficulty in reproducing the closed-loop morphology using these models. They suggest that these are probably winds originating from a nuclear starburst or accretion activity. X-ray emission and emission-line imaging shows that NGC 3079 hosts a superwind (Veilleux et al. 1994; Cecil et al. 2001, 2002). Superwinds are believed to be generated when the kinetic energy from supernovae and massive stellar winds are transformed into thermal energy. The heated gas then expands into the lower pressure ambient medium. The direction of the steepest pressure gradient is along the minor axis. The hot gas is easily traced by the X-ray emission, which is a more direct tracer compared to the emission-line gas, which is generated at shock fronts as a result of the interaction with the ambient medium. The emission-line ratios seen in superwinds are typical of shock-ionized gas as also seen in the case of NGC 3079 (Veilleux et al. 1994). Although these authors favored a starburst-wind origin for the radio lobes, they were not able to rule out AGN-driven winds. Several authors favored the jet origin of the lobes (Irwin & Seaquist 1988; Irwin & Saikia 2003). Irwin et al. (2017) find that NGC 3079 is one of the few edge-on galaxies in the CHANG-ES sample (Irwin et al. 2012) that shows radio lobes that stand out in polarized intensity compared to the galactic disk emission that is not as highly polarized.
Citation: Cecil et al. 2001; Cecil et al. 2001
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