adsabs/FOCAL huggingface dataset:
Disk galaxies typically reveal out-of-equilibrium features due to incomplete equilibration. These may appear in the form of bars and spiral arms, which are large-scale perturbations in the radial and azimuthal directions, responsible for a slow, secular evolution of the disk. In the vertical direction, disks often reveal warps (Binney 1992). In the case of the Milky Way (MW) disk, which can be studied in much greater detail than any other system, recent data from astrometric and radial velocity surveys such as SEGUE (Yanny et al. 2009), RAVE (Steinmetz et al. 2006), GALAH (Bland-Hawthorn et al. 2019), LAMOST (Cui et al. 2012), and above all Gaia (Gaia Collaboration et al. 2016, 2018a, 2018b) have revealed a variety of additional vertical distortions. At large galactocentric radii (>10 kpc) this includes, among others, oscillations and corrugations (Xu et al. 2015; Schönrich & Dehnen 2018), and streams of stars kicked up from the disk that undergo phase mixing, sometimes referred to as “feathers” (e.g., Price-Whelan et al. 2015; Thomas et al. 2019; Laporte et al. 2022). Similar oscillations and vertical asymmetries have also been reported in the solar vicinity (e.g., Widrow et al. 2012; Williams et al. 2013; Yanny & Gardner 2013; Gaia Collaboration et al. 2018b; Quillen et al. 2018; Bennett & Bovy 2019; Carrillo et al. 2019). One of the most intriguing structures is the phase-space spiral discovered by Antoja et al. (2018) and studied in more detail in subsequent studies (e.g., Bland-Hawthorn et al. 2019; Li 2021; Li & Widrow 2021; Gandhi et al. 2022). Using data from Gaia DR2 (Gaia Collaboration et al. 2018a), Antoja et al. (2018) selected ∼900,000 stars within a narrow range of galactocentric radius and azimuthal angle centered around the Sun. When plotting the density of stars in the (z, v

z
)-plane of vertical position, z, and vertical velocity, v

z
, they noticed a faint, unexpected spiral pattern, which became more enhanced when color-coding the (z, v

z
)-“pixels” by the median radial or azimuthal velocities. The one-armed spiral makes two to three complete wraps, resembling a snail shell, and is interpreted as a signature of phase mixing in the vertical direction following a perturbation, which Antoja et al. (2018) estimate to have occurred between 300 and 900 Myr ago. More careful analyses in later studies (e.g., Bland-Hawthorn et al. 2019; Li 2021) have nailed down the interaction time to ∼500 Myr ago.
Citation: Bland-Hawthorn et al. 2019
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Citation: Bland-Hawthorn et al. 2019
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Citation: Antoja et al. (2018)
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Citation: Thomas et al. 2019
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Citation: Quillen et al. 2018
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To be a feasible mechanism of cusp-core transformation, SNF needs to fulfill a number of conditions. First and foremost, the total energy that is released by supernovae has to be sufficient to unbind the DM halo’s central cusp (Peñarrubia et al. 2012). A secondary condition is that SNF needs to be impulsive, i.e. SN-driven gas outflows need to give rise to sizeable changes of the gravitational potential on time-scales which are shorter than the typical dynamical times of DM particles in the inner halo (Pontzen & Governato 2012; Burger & Zavala 2021). From the observational side, there is evidence that starbursts in bright dwarfs, and thus, their associated supernova cycles, happen on time-scales that are comparable to the typical dynamical times of those galaxies (Kauffmann 2014). However, observations still lack the time resolution required to resolve starburst cycles on the smaller dynamical time-scales of the low-mass MW dwarf spheroidals (Weisz et al. 2014). In general, the more energy is injected during a SNF cycle, the shorter the time is over which that energy is injected, and the more concentrated the baryonic mass is to the centre of the DM halo (Burger & Zavala 2021), the more efficient the SNF-induced cusp-core transformation will be. In hydrodynamic simulations of galaxy formation, the implementations of SNF are calibrated to the resulting structural properties of larger galaxies. Recent studies suggest that, in cosmological simulations, the efficiency of SNF at flattening the cusps of dwarf-size DM haloes is mainly determined by one model parameter, the gas density threshold for star formation (Benítez-Llambay et al. 2019; Dutton et al. 2020). In a given dwarf galaxy, larger star formation thresholds lead to more bursty star formation, more concentrated and impulsive feedback, and a stronger contribution of baryons to the central potential, and hence to enhanced core formation (Benítez-Llambay et al. 2019; Bose et al. 2019).
Citation: Burger & Zavala 2021
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Citation: Benítez-Llambay et al. 2019
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Citation: Benítez-Llambay et al. 2019
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Relative time delays between multiple gravitationally lensed images provide a one-step distance anchor of the universe, and thus H
0. This probe is independent of the local distance ladder and the sound-horizon-physics anchors of the CMB and large-scale structure probes. The method, known as the time-delay cosmography, has been proposed more than half a century ago to utilize the transient nature of supernovae (SNe) for measuring the time delays (Refsdal 1964). Time-delay cosmography was first applied by measuring the time delays of multiply lensed quasars with multiseason monitoring campaigns (e.g., Kundić et al. 1997; Schechter et al. 1997; Fassnacht et al. 2002; Tewes et al. 2013; Courbin et al. 2018; Millon et al. 2020a). The discovery of numerous lensed quasar systems, follow-up monitoring, high-resolution imaging, and precise spectroscopic observations have led to a precise measurement of H
0 using seven multiply lensed quasars (Wong et al. 2020; Shajib et al. 2020; Millon et al. 2020b). These measurements assumed particular forms of the mass density profiles of the deflector galaxies. The mass-sheet degeneracy (MSD; see Falco et al. 1985; Schneider & Sluse 2013), an inherent transform leaving the lensing observables invariant while changing the time-delay prediction, poses limits in the precision of H
0 measurements in the absence of additional data. Birrer et al. (2020) introduced an additional degree of freedom to the mass density profiles to avoid constraining the lens model based on the specific form of the mass profiles previously chosen. Birrer et al. (2020) constrained the MSD solely by stellar kinematics observations of the deflector galaxy hierarchically on the deflector population-level mitigating covariances among the assumptions of individual lenses. For the achieved 5% precision measurement of H
0, Birrer et al. (2020) combined the seven TDCOSMO lenses with 33 galaxy–galaxy lenses from the Sloan Lens ACS (SLACS) survey (Bolton et al. 2008; Shajib et al. 2021). The interpretation of the kinematics measurements is impacted by the mass-anisotropy degeneracy (Binney & Mamon 1982; Dejonghe & Merritt 1992), and mitigating this degeneracy requires assumption on the stellar anisotropy distribution or spatially resolved kinematics measurements (e.g., Cappellari 2008; Barnabè et al. 2011; Yıldırım et al. 2020). A forecast for future constraints using kinematics observations in breaking the MSD within the assumptions of the Birrer et al. (2020) analysis is provided by Birrer & Treu (2021).
Citation: Shajib et al. 2020
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Some fraction of the Comptonized photons will be intercepted by the disc and reflected into the line of sight by further Compton scattering and florescence. These processes give rise to a complex spectral component that typically peaks at energies of 3050keV (the so-called Compton hump, see Sunyaev  Titarchuk 1980, figs 10a and c) and adds further fluorescent emission to the spectrum. The reflection component is present in both BH XBs (due to interaction of X-rays with the accretion disc and the surface of the normal star; Basko, Sunyaev  Titarchuk 1974) and active galactic nuclei (AGNs; Nandra  Pounds 1994), and complicates attempts to understand the dominant Comptonized emission owing to proximity of the Compton hump to the plausible location of the high-energy turn-off (corresponding to 3kTe). Typical attempts to take reflection into account involve adding sophisticated reflection components (such as the xspec models pexrav (Magdziarz  Zdziarski 1995) or reflionx (Ross  Fabian 2005)) to unsophisticated models of Comptonization, such as a cut-off power law. This inaccurate representation of the Comptonization means that interesting properties such as the electron temperature or Compton y-parameter are then inferred from the best fit of a cut-off power law to the data, rather than a direct treatment of these quantities. In addition to this, Ibragimov etal. (2005) showed that the strength of the reflected component R (defined in terms of the solid angle  subtended by the portion of the disc in line of sight to the corona) is systematically overestimated by such treatment. It has been known for some time that R correlates strongly with photon index  (Gilfanov, Churazov  Revnivtsev 1999; Revnivtsev, Gilfanov  Churazov 2001; Ibragimov etal. 2005), increasing as spectra become softer (implying a decreasing y-parameter). Similar behaviour has been observed for AGN spectra (Zdziarski, Lubiski  Smith 1999; Gilfanov, Churazov  Revnivtsev 2000; Zdziarski etal. 2003). This relationship clearly favours the accretion disc as the source of the seed photons for Comptonization, as the radiation being intercepted by the disc is increasing in tandem with the seed photon flux incident on the electron cloud. However, there is increasing evidence that at lower luminosities synchrotron photons from the magnetized corona may contribute a significant, perhaps dominant, population of seed photons, motivating the creation of so-called hybrid models. Such models typically comprise both a low-energy thermal population and an additional high-energy non-thermal population of electrons (see, e.g. Coppi 1999; Merloni  Fabian 2001; Del Santo etal. 2013).
Citation: Magdziarz  Zdziarski 1995
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Accretion of diffuse gas onto the disks of galaxies from the intergalactic medium (IGM) is a possible explanation for how the H i content of galaxies has remained relatively constant since z ∼ 2 while the star formation rate (SFR) was up to 10 times higher at high redshifts (Noterdaeme et al. 2012; Madau & Dickinson 2014). The constant H i content implies that galaxies have somehow replenished themselves with enough gas to fuel continuous star formation. And though not directly responsible for star formation, H i is an intermediate phase toward molecular hydrogen, which is the raw ingredient of the star formation fuel. If the star formation is to continue, external gas has to be accreted and pass through the H i phase at some stage in the accretion process. Observationally inferred accretion rates as traced by H i, however, fall between 0.1 and 0.2 





 at low redshifts. This is a full order of magnitude lower than what is needed for galaxies to continually form stars at their current rates (Sancisi et al. 2008; Kauffmann et al. 2010). This discrepancy presents two intriguing scenarios: the cycle of star formation will eventually exhaust all of the available fuel within a few Gyr and star formation itself will gradually cease, or processes that refuel galaxies with the necessary gas have been missed by previous surveys. Numerical simulations have shown a likely mechanism for refueling star formation is through a quasi-spherical “hot” mode and filamentary “cold” mode (Birnboim & Dekel 2003; Kereš et al. 2005, 2009). “Cold” in the context of these numerical simulations refers to gas that has not been heated above the virial temperature of the galaxy’s potential well (∼105 K), and “hot” refers to gas that has virialized in a process akin to the classical theory of galaxy formation in which shock-heated, virialized gas with short cooling timescales accretes onto the central galaxy (e.g., Rees & Ostriker 1977). These simulations also suggest cold mode accretion was the dominant form of accretion at z ≥ 1 for all systems, and remains prevalent through z = 0 for galaxies in low-density environments (ngal ≲1 h3 Mpc−3) and Mhalo ≲ 1011.4 





 (or Mbary ≤ 1010.3 





). For perspective, our own Milky Way has a virial (and thus halo) mass on the order of 1012 





. These cold flows should exist in the form of vast filaments of cold, diffuse gas that permeate through the hot halo (Kereš et al. 2005). Comparisons by Nelson et al. (2013) between the smoothed particle hydrodynamic (SPH) numerical scheme employed in Kereš et al. (2005, 2009) and more sophisticated adaptive mesh refinement (AMR) simulations revealed the relative contribution of the cold mode is likely overestimated in earlier SPH simulations due to inherent numerical deficiencies. Nevertheless, the AMR simulations do show some fraction of gas is accreted cold.
Citation: Sancisi et al. 2008
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With the ALMA results, we now estimate such physical parameters as the temperature, density, and volume filling factor of warm ionized gas in the IRS 13E region. Assuming that that this gas is under the local thermodynamic equilibrium and its 232 GHz continuum and H30α line emissions are optically thin, the electron temperature Te can be expressed as
(4)$$\begin{eqnarray*}
T_{\rm e}({\rm K}) &amp;=&amp; \left[ \frac{6985}{\alpha (\nu ,T_{\rm e})} \left(\frac{\nu }{\rm GHz}\right)^{1.1} \frac{1}{1+N({\rm He})/N({\rm H})}\right. \nonumber\\
&amp;&amp;\left.\times \, \left(\frac{S_{\rm C}}{S\Delta V_{\rm H30\alpha }} \right) \right]^{0.87},
\end{eqnarray*}$$where the elemental number density ratio of $N({\rm He})/N(\rm H) \sim 0.08$ and α(ν, Te) ∼ 0.85 at ν = 232 GHz and Te ∼ 104 K (Mezger & Henderson 1967). For E3, the total flux densities of the continuum and H30α line emissions are SC = 28.5 ± 1.8 mJy and SΔVH30α = 2.37 ± 0.12 Jy km s−1. We thus have Te = 9260 ± 650 K, which is consistent with previous estimates, ranging from 6000 to 12 000 K (Zhao et al. 2010; Moser et al. 2017; Tsuboi et al. 2019). We can also obtain the volume emission measure (EM) as (Murchikova et al. 2019)
(5)$$\begin{eqnarray*}
{\rm EM} = S\Delta V_{\rm H30\alpha }\frac{4\pi D^2}{\epsilon _{\rm H30\alpha }(T_{\rm e},n_{\rm e})} \frac{\nu }{c} \sim 1 \times 10^{60}\rm ~cm^{-3},
\end{eqnarray*}$$where the H30α emissivity $\epsilon _{\rm H30\alpha }=1.25\times 10^{-31} \rm ~erg~s^{-1}$ for Te = 104 K and $n_{\rm e}=10^4\sim 10^7 \rm ~cm^{-3}$ (Storey & Hummer 1995) and the speed of light c are used. Furthermore, we find that both the continuum and H30α emission intensities of E3 can be characterized by a Gaussian with a deconvolved size of ∼0.01 pc, assuming a spherical symmetry. This together with the above EM value leads to the estimate of $n_{\rm e} \sim 3 \times 10^5\rm ~cm^{-3} f_V^{-1/2}$. By further assuming a thermal pressure balance between the warm and hot gases (e.g. P/k ∼ 2 × 1010 K cm−3; Section 3.2), we estimate the volume filling factor fV ∼ 0.1 and hence $n_{\rm e} \sim 10^6\rm ~cm^{-3}$. If similar temperature and pressure could be assumed for warm ionized gas on larger scales, its filling factor has to be very small. We estimate that the total H30α flux within a circular region of 1 arcsec radius centred on E3 (Fig. 7B) is ${\sim}12 \rm ~Jy~km~s^{-1}$, which corresponds to ${\rm EM} = 6\times 10^{60}\rm ~cm^{-3}$. The filling factor is then ∼8 × 10−4, while the mass of the warm ionized gas in this region is ∼mpEM/ne ∼ 1 × 10−2 M⊙. These estimates indicate that the volume is indeed dominated by hot gas and that warm gas traces dense clumps, probably their surfaces exposed to the ionizing radiation from massive stars in the region.
Citation: Murchikova et al. 2019
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Still, to further rule out a stellar origin, we attempt to fit the transit spectrum with a stellar contamination model. Following Rackham et al. (2018) we consider the hypothesis that the observed transit depth variations are due to inhomogeneities on the stellar surface. The observed wavelength-dependent transit depths 






D


λ
,
obs




 are modeled as:
4






D


λ
,
obs


=





D


λ




1
−


f


spot





1
−





F


λ
,
spot






F


λ
,
phot








−


f


fac





1
−





F


λ
,
fac






F


λ
,
phot











,


where Dλ is the geometric radius ratio 










R


p



/



R


⋆






2




, assumed here to be constant with wavelength (=D), fspot and ffac are the spot and faculae covering fractions, and the Fλ refer to bandpass-integrated PHOENIX model spectra of the photosphere, spots, and faculae (Hauschildt et al. 1999). Using K2-18b stellar parameters (Table 2), we explore a wide range of possible stellar contamination spectra for M2–M3 stars with spot and faculae covering fractions consistent with 1% I-band variability. Based on Rackham et al. (2018), we then explore scenarios with giant spots and solar-like spots as well as with and without faculae, resulting in spot fractions of up to 20%. However, none of those models can explain the amplitude of the observed transit spectrum. The amplitude of resulting transit depth variations due to the stellar inhomogeneities are up to 3–8 parts-per-million (ppm), about an order of magnitude smaller than the observed 80–90 ppm transit depth variations in the observed WFC3 spectrum (Figure 3). Finally, we also explore the most extreme scenarios where the spot and faculae covering fractions can be as high as 100%, but even those stellar inhomogeneity models fail to explain the amplitude of the observed transit depth variation. They deliver an absolute maximum of 20 ppm at 1.4 μm, which still only corresponds to less than a quarter of the transit depth variation in the observations. We conclude that stellar inhomogeneities and activity cannot explain the measured transmission spectrum.
Citation: Hauschildt et al. 1999
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The results presented in this work answer a number of questions regarding the character of the GG Tau A system, while raising others and leaving others untouched. First among the questions raised by our results are the questions of whether the detailed morphology of features in the circumbinary torus as seen in our simulations are actually present in the GG Tau A system. The current best resolution observations of the torus provide tantalizing hints that such features do exist, but a definitive statement that such features are present must await higher resolution observations of quality similar to those described by the ALMA Partnership (2015), for the HL Tau circumstellar disk. Another important question concerns planet formation in multiple systems. Whether or not any theoretical mechanism presently exists to explain the formation of giant planets in binary systems, the fact remains that at least a few binary systems, such as γ Cephei (Neuhauser et al. 2007), GI86 (Queloz et al. 2000), and HD 41004 (Zucker et al. 2004), do harbor planets. Therefore, some formation mechanism does in fact exist. While we find that accretion into the circumstellar disks occurs rapidly enough so that they can survive for the comparatively long timescales needed to form planets, other conditions, such as temperatures, remain quite unfavorable. What are the mechanisms still missing from our models that permit such objects to form? Finally, our simulations model the evolution of the “A” component of the full GG Tau system over a time span extending over only a tiny fraction of its formation timescale and in only two spatial dimensions. We neglected the full dynamical effects expected to be present in the system, insofar as our results include neither the distant binary “B” component of the GG Tau system, nor the newly discovered tight binary nature of the GG Tau Ab component. Even so, we find large scale morphological changes even over this short time span, and restricted dimensionality and physical system. Given the vigor of the activity over such a short timescale, we would expect activity of similar scale to occur over longer time spans as well, with correspondingly large consequences on the system morphology. To what extent will 3D effects also play a role in the evolution? What will be the end state configuration of the GG Tau system as a whole? Will the components eventually break apart? Merge? Future investigations extending the work presented here will be required in order to answer these questions.
Citation: Zucker et al. 2004
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Our formula can be used to confront the curvature effect with observations and estimate the decay timescale of the steep decay phase. In observations, the steep decay phase has been observed in the decay phase of the prompt emission phase and flares in GRBs. Since the value of E0 (




∼
0.3
–
1

MeV


) in the prompt emission phase is significantly larger than 




10

keV


, the β in the steep decay phase of prompt emission would be a linear function of observer time based on Equation (38). This behavior has been observed in a number of bursts, such as GRBs 050814 (Zhang et al. 2009, please see the spectral evolution in the 




β
−


t


obs




 space), 051001 etc. The linear relation between β and 








t







obs




 is also found in the steep decay of flares (e.g., Mu et al. 2016). For a linear function β of 








t







obs




, one can obtain the slope of the linear function, which is equal to 




7.9


κ


ˆ



/





t







c


=
2.37

keV

/

[


E


0


(




t







obs


=
0
)




t







c


]


 based on Equations (38) or (39). Then, the decay timescale 








t







c




 of our studying phase can be estimated if the value of 






E


0


(




t







obs


=
0
)


 is known. We fit the spectral evolution in the decay phase of a flare (




∼
172

s


) in GRB 060904B (Mu et al. 2016) with a linear function. The fitting result, i.e., 




β
=
0.84
+
0.020




t







obs




 with 








t







obs


=


t


obs


−


t


p




, is shown in the left panel of Figure 4 with  a red solid line. Then, we have 






E


0


(




t







obs


=
0
)




t







c


=
119

keV

s


, which is around that found in Mu et al. (2016), i.e., 




2.54

keV
×
65.39

s


. For a flare (




∼
116

s


) in GRB 131030A, the spectrum at the beginning of the steep decay phase can be fitted with a Band function. With the fitting result found in Mu et al. (2016), i.e., 






α


ˆ


=
−
0.91


, 






β


ˆ


=
−
3.19


, and 






E


0


(




t







obs


=
0
)
=
1.95


, we plot the evolution of β based on Equation (38) in the right panel of Figure 4 with a red solid line. Here, we adopt 








t







c


=
54

s


 (Mu et al. 2016), which can also be roughly estimated based on the flux evolution. It can be found that Equation (38) describes the spectral evolution approximately, which may reveal that a more appropriate value of parameters (e.g., 








t







c




) may be required for this source. The agreement of our analytical formula and observational data shows that the assumption (2) given at the beginning of Section 2 (i.e., the jet shell has no θ-dependent spectral parameters or Lorentz factor) is applicable in reality.
Citation: Mu et al. 2016
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Citation: Mu et al. 2016
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