Modeling JWST MIRI-MRS Observations of T Cha: Mid-IR Noble Gas Emission Tracing a Dense Disk Wind

We use known properties of the T Cha system (Table 1) to determine our density grids. Given a mass of M_* = 1.5 M_⊙ and assuming a maximal wind temperature of T = 10⁴ K (equivalent to a sound speed of c_S ≈ 10 km s⁻¹), the gravitational radius for T Cha is ${r}_{G}:= \tfrac{{{GM}}_{* }}{{c}_{S}^{2}}\approx 13\,\mathrm{au}$. This is the typical length scale outside of which the gravitational potential well of the star does not significantly impede the launch of a wind.

Table 1. Properties of the T Cha System

Property	Value and Unit	Comment	Reference
M*	1.5 M⊙	⋯	Olofsson et al. (2011)
Distance	102.7 ± 0.3 pc	Gaia DR3 Value	Gaia Collaboration et al. (2022)
Inclination	73°	Measured using 3 mm continuum	Hendler et al. (2018)
Rcav (mm)	33 au	⋯	Francis & van der Marel (2020)
Rcav (μm)	15 au	⋯	C. Xie et al. 2024, in preparation
Rout (mm)	44 au	⋯	Francis & van der Marel (2020)
Rout (μm)	58 au	⋯	Pohl et al. (2017)
Rout (gas)	220 au	Measured in 12CO	Huélamo et al. (2015)
${\dot{M}}_{\mathrm{acc}}$	10−8.4 M⊙ yr−1	Using [O i]-Lacc relationship (Nisini et al. 2018)	Cahill et al. (2019)

Note. Where appropriate, values have been rescaled from the original references to use the Gaia DR3 distance. R_cav refers to the outer radius of the dust cavity as measured at each wavelength regime.

Download table as:  ASCIITypeset image

We use the self-similar solutions of Sellek et al. (2021) to produce models of the wind's density and velocity structure. These provide normalized densities $\tilde{\rho }$ and velocities $\tilde{u}$ along each streamline, defined according to

$$\begin{eqnarray}&&\rho ={\rho }_{{\rm{b}}}\tilde{\rho }\end{eqnarray} \tag{ 1 }$$

$$\begin{eqnarray}&&u={{ \mathcal M }}_{{\rm{b}}}{c}_{{\rm{S}},{\rm{b}}}\tilde{u}\end{eqnarray} \tag{ 2 }$$

where ρ_b, ${{ \mathcal M }}_{{\rm{b}}}$ and c_S,b are the density, Mach number, and sound speed at the base of the streamline.

These quantities depend on four key parameters:

• 1.  
  The slope of the density at the base of the wind, ρ_b ∝ r^−b . In such a model, the column density is accumulated at small radii for b > 1 and large radii for b ≤ 1. We focus on b = 1.5, a value motivated both by theory/simulations (Hollenbach et al. 1994; Picogna et al. 2019) as well as previous comparisons to observations of TW Hya (Pascucci et al. 2011; Ballabio et al. 2020). Note that this is also the scaling adopted in various self-similar magnetized wind models (Blandford & Payne 1982; Lesur 2021). In Section 5.1 we justify this further by showing a lower b would produce line profiles that are too narrow.
• 2.  
  The slope of the temperature profile in the wind, T ∝ r^−τ . We assume this to be τ = 0, i.e., an isothermal case. This is typical of EUV-heated winds, but nearly isothermal conditions are also seen in X-ray-heated winds (Picogna et al. 2019, 2021), and Nakatani et al. (2018a) also found τ = 0.319 at solar metallicity for FUV-heated winds. Such small temperature gradients only weakly affect the density and velocity structure (Sellek et al. 2021), changing ${{ \mathcal M }}_{{\rm{b}}}$ by no more than ∼10%. The results of our mocassin calculations also show near isothermal temperatures throughout most of their volume (Figure 1); therefore, neglecting τ ≠ 0 is a small source of uncertainty.
• 3.  
  The elevation of the wind base above the midplane ϕ_b. The elevation of the base is largely controlled by the aspect ratio of the underlying disk (Picogna et al. 2021) and accordingly scales similarly. A rough approximation (effectively assuming M_*-independent disk temperatures) is

  $$\begin{eqnarray}&&{\phi }_{{\rm{b}}}(r;{M}_{* })=8\buildrel{\circ}\over{.} 5{\left(\displaystyle \frac{r}{\mathrm{au}}\right)}^{1/4}{\left(\displaystyle \frac{{M}_{* }}{{M}_{\odot }}\right)}^{-0.5}.\end{eqnarray} \tag{ 3 }$$

  Given T Cha's stellar mass of 1.5 M_⊙, at 10 s au, we expect ϕ_b ≳ 14° and so choose the 18° models of Sellek et al. (2021) for our analysis (the lowest ϕ_b precalculated models fulfilling this criterion).
• 4.  
  The launch angle of the wind with respect to the base χ_b. We assume 90° since we expect large temperature jumps across the base, which will lead to strong acceleration normal to the base only and thus streamlines that emerge approximately perpendicular to the base).

Zoom In Zoom Out Reset image size

For any parameter combination, the self-similar solutions predict a unique ${{ \mathcal M }}_{{\rm{b}}}$ value (Clarke & Alexander 2016; Sellek et al. 2021), applicable to all streamlines (along with an associated velocity and density structure). b = 1.5, τ = 0, ϕ_b = 18°, & χ_b = 90° gives ${{ \mathcal M }}_{{\rm{b}}}=0.437$. Figure 1 shows an example of a cross section through the resulting wind model for a particular density normalization and inner radius; the number density of the gas is shown in the second panel, while the geometry of the resulting streamline is overlaid on the temperature profile (see Section 2.2) in the first panel of Figure 1. Also indicated are the key angles defined above, as well as the opening angle at the base θ_b = ∣90° − χ_b − ϕ_b∣ = 18° and the maximum opening angle along the streamline, measured to be ${\theta }_{\max }=33^\circ$.

The density normalization is the most complicated thing to set. It is connected to the mass-loss rate, which is uncertain by several orders of magnitude between different models for photoevaporation where different parts of the high-energy spectrum drive the mass loss. Assuming b < 2 (as required for valid solutions, Sellek et al. 2021) and r_in < < r_out then for a self-similar isothermal wind, the two are related through

$$\begin{eqnarray}&&{\dot{M}}_{\mathrm{nom}}=\displaystyle \frac{4\pi \cos {\phi }_{{\rm{b}}}}{2-b}\,{{ \mathcal M }}_{{\rm{b}}}\,\displaystyle \frac{{G}^{b}{M}_{* }^{b}}{{c}_{S}^{2b-1}}\,{r}_{\mathrm{out}}^{2-b}\,{\rho }_{G},\end{eqnarray} \tag{ 4 }$$

where ρ_G is the mass density at the gravitational radius and we assume c_S = 10 km s⁻¹. However, since b < 2, this expression diverges to large r_out so the density is sensitive to not only the assumed c_S but also r_out.

We define our models over a spherical region with an outer radius of r_out equal to the ¹²CO disk outer radius of 220 au (Huélamo et al. 2015). This is the most optimistic scenario for an extended wind. Since photons propagate predominantly outward, the inner regions are not affected by the outer parts of a wind, and less extended winds can be explored simply by cropping the outer radius during the analysis (noting as above that this affects the mass-loss rate).

The number density n of the gas (Figure 1, second panel) is then derived from its mass density ρ assuming ρ = μ m_H n with μ = 1.298 for a gas of the composition we use in our radiative transfer simulations (see Section 2.2). For our assumed parameters, this gives a number density at r_G scaling as

$$\begin{eqnarray}&&{n}_{G}=1.6\times {10}^{3}\,{\mathrm{cm}}^{-3}\displaystyle \frac{{\dot{M}}_{\mathrm{nom}}}{{10}^{-10}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}}.\end{eqnarray} \tag{ 5 }$$

For comparison, we list the critical densities for excitation of the lines of interest by electrons and neutral H at 7700 K in Table 2; contours showing where the wind attains these values are overlaid on the second and third panels in Figure 1, respectively. However, note that although we provide values here, mocassin does not yet include neutral H as a collider, as the excitation rates have only just been calculated (Yan & Babb 2024); we explore the impact of this in Appendix C.

2.1.1. Column Density and the Inner Wind

The absorption of photons at small radii can affect the outer disk (for example, in the scenario envisaged by Pascucci et al. 2020, 2023, where an inner wind shields the outer disk until late in its evolution). We must therefore explore the effect of the inner parts of the wind.

The column density of gas in the self-similar models, which will be absorbing and attenuating the photons, may be calculated as

$$\begin{eqnarray}&&N(\phi )={\int }_{{r}_{\mathrm{in}}}^{{r}_{\mathrm{out}}}{n}_{G}\tilde{n}(\phi ){\left(\displaystyle \frac{r}{{r}_{G}}\right)}^{-b}{dr}\end{eqnarray} \tag{ 6 }$$

$$\begin{eqnarray}&&\propto \,{n}_{G}({r}_{\mathrm{out}}^{1-b}-{r}_{\mathrm{in}}^{1-b}).\end{eqnarray} \tag{ 7 }$$

For b > 1, this expression is dominated by small radii near r_in, while for b < 1, the column density is mostly accumulated at large radii. Substituting Equation (4) and assuming our fiducial b = 1.5, then along the wind base:

$$\begin{eqnarray}&&N=\displaystyle \frac{1.1\times {10}^{20}\,{\mathrm{cm}}^{-2}}{{{ \mathcal M }}_{{\rm{b}}}\cos ({\phi }_{{\rm{b}}})}\left(\displaystyle \frac{\dot{M}}{{10}^{-8}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}}\right){\left(\displaystyle \frac{{r}_{\mathrm{in}}}{1\,\mathrm{au}}\right)}^{-1/2}.\end{eqnarray} \tag{ 8 }$$

Hence we can see that the two main parameters determining the optical depth in our models will be the inner radius and the mass-loss rate (the outer radius enters implicitly through the mass-loss rate, e.g., Equation (4)).

To contextualize these values (see also the cross sections in Figure 3), note that the penetration depth of EUV photons in neutral hydrogen is typically 10¹⁷–10¹⁹ cm⁻², hence as expected from the mass-loss rate of EUV-driven winds, the winds will be optically thin for $\dot{M}\lesssim {10}^{-9}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}$. On the other hand, 1 keV X-rays, which may perform K shell photoionization of Ne, can penetrate a neutral hydrogen column of 10²² cm⁻² and the winds are generally optically thin to these even for the highest density normalization we consider. This is also to be expected since Sellek et al. (2022) found that the most effective X-rays for wind driving (which are distinct from the most effective at photoionizing Ne) are those for which the corresponding wind presents an optical depth at that energy of τ ≈ 1, and that this should occur around 500 eV for typical X-ray luminosities.

In order to vary the absorbing column, we thus vary the inner radius r_in of the grid on which we perform the radiative transfer. Thus, we are defining r_in ∈ 0.03, 0.1, 0.3, 1.0, 3.0 r_G as the radius inside of which we set the gas density to be zero. Such r_in values are motivated by the fact that in the photoevaporative scenario, the wind ceases being launched on a scale somewhere in the range 0.1–1 r_G , smoothly transitioning to a hydrostatic atmosphere inside of this point. An MHD disk wind may carry on inside this point, so we also employ a smaller value of 0.03 r_G to crudely explore this scenario, while 3 r_G allows us to consider a case where the wind only launches outside of the mm cavity which is ∼30 au in radius (Francis & van der Marel 2020).

However, we emphasize that in general, since we do not model the underlying disk (only the wind region), these choices of radius do not directly constrain or reflect the presence or location of a gas cavity or gap in the disk. That is to say, the gas may extend closer to the star than r_in at the midplane while stopping approximately at r_in at greater elevations and not affect our results in any way. While this cutoff may result from the absence of gas in the disk to feed the wind inward of some cavity radius, it can also arise as a result of the limited radii at which a wind can lift significant additional material to higher elevations. In reality, the edge of the wind is not likely sharp as modeled here but smoothly transitions to a hydrostatic inner atmosphere. What matters most for our results is where the column density is mostly accumulated. Therefore, only if this happens in the wind will r_in necessarily be a good measure of the wind's true inner radius.

2.1.2. Defining Mass-loss Rates

As discussed, estimates of the mass-loss rate between photoevaporation models vary considerably. One key factor in this is the driving radiation: since X-rays are more penetrating than EUV they are expected to drive much denser winds with mass-loss rates 1–2 orders of magnitude than EUV. For example, given the <4.1 × 10⁴¹ s⁻¹ EUV photon flux of T Cha (Pascucci et al. 2014) and its 1.5 M_☉ mass, the expected EUV photoevaporation rate (Shu et al. 1993) would be ${\dot{M}}_{\mathrm{PE}}\lesssim 1.2\times {10}^{-9}\,{\mathrm{yr}}^{-1}$, while in the other extreme, the X-ray photoevaporation rate predicted by Picogna et al. (2021) for a star of this mass is ${\dot{M}}_{\mathrm{PE}}\sim 5.9\times {10}^{-8}\,{\mathrm{yr}}^{-1}$. We use the outer gas radius of 220 au (Huélamo et al. 2015) for r_out in Equation (4), in order to scale ρ_G so as to produce nominal mass-loss rates ${\dot{M}}_{\mathrm{nom}}\in {10}^{-10},{10}^{-9},{10}^{-8},{10}^{-7}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}$ that span this large range of possible values.

To remedy the issue of the mass-loss rate diverging to a large radius in the self-similar models, we note that the line emissivity in the outer regions of the wind, which will be below the critical density, scales as n² and therefore diverges more slowly, if at all. Thus from now on, we will quote as the "true" mass-loss rate the "observable mass-loss rate" for which we would have evidence from the [Ne ii] line (this being our most confidently detected line) with MIRI-MRS given the absolute flux error of 5% (Argyriou et al. 2023), which dominates over the 1σ statistical uncertainty (Bajaj et al. 2024).

To obtain the observable mass-loss rate, we calculate the observed outer radius as the spherical radius r_f containing a fraction f = 0.95 of the line luminosity. Roughly speaking (assuming the model produces the correct total [Ne ii] luminosity), this is designed to account for the fact that the outer reaches of the wind could not be confidently detected at a statistical level. For this purpose, we also normalize the velocities of the self-similar model to the sound speeds derived from the temperature maps provided by the radiative transfer (even though these are not strictly isothermal). Depending on the assumed inner radius and the irradiating spectrum, this results in observable mass-loss rates for each nominal normalization in the ranges given in Table 3. ⁹ As an example, in Figure 2 we show the calculated $\dot{M}$ as a function of r_in for one of our model sets hiLX_TCha_sUV (see 2.2 for details). The figure also includes equivalent values for f = 0.97 (equivalent to the 5σ level using the statistical uncertainty), showing that the results are not hugely sensitive to the choice of f. The ranges quoted in Table 3 and shown in Figure 2 are both narrow enough and distinct enough to use as labels henceforth.

Zoom In Zoom Out Reset image size

Table 3. The Observable Mass-loss Rates Derived for Each Nominal Mass-loss Rate Normalization

${\dot{M}}_{\mathrm{nom}}/{M}_{\odot }\,{\mathrm{yr}}^{-1}$	$\dot{M}/{M}_{\odot }\,{\mathrm{yr}}^{-1}$
10−10	0.7 − 2 × 10−10 M☉ yr−1
10−9	0.5 − 1 × 10−9 M☉ yr−1
10−7	3 − 5 × 10−9 M☉ yr−1
10−7	1 − 3 × 10−8 M☉ yr−1

Download table as:  ASCIITypeset image

We use the Monte Carlo photoionization radiative transfer code mocassin (Ercolano et al. 2003, 2005, 2008) to calculate the temperature and ionization equilibrium at each point of the wind. As well as the density distributions described above, the other key input to these radiative transfer simulations is one of five high-energy spectra. Details of each spectrum, which were produced using pintofale (Kashyap & Drake 2000), are given in Table 4 and summarized below.

First, we test a spectrum we call "Ercolano_RSCVn"—which is the Ercolano et al. (2009) model FS0H2Lx1—to enable direct comparisons with Ercolano & Owen (2010, 2016). This uses RS CVn binaries (which contain a giant with comparable deep convective zones to T Tauri stars) as a template for a spectrum containing both EUV and X-ray components. We normalize this spectrum to the observed X-ray luminosity of 2.7 × 10³⁰ erg s⁻¹ (Güdel et al. 2010). This results in an EUV flux of 1.2 × 10⁴¹ s⁻¹, consistent with the Pascucci et al. (2014) upper limit of 4.1 × 10⁴¹ s⁻¹.

For a more direct model of T Cha's X-ray emission, we turn to Sacco et al. (2014) who provide two-temperature fits. These were performed for two different abundance patterns, resulting in two possible spectra: a harder, less luminous spectrum results from solar abundances, while a softer, more luminous spectrum results from assuming a pattern similar to TW Hya (Brickhouse et al. 2010). We find the most important differences in our results are due to the luminosities, hence we refer to these as "loLX_TCha" and "hiLX_TCha" respectively (although both have a higher L_X than Güdel et al. 2010). Moreover, since both of these spectra are comfortably below the Pascucci et al. (2014) upper limit on the EUV flux, we create an additional version of each (denoted "loLX_TCha_sUV" and "hiLX_TCha_sUV") which include an additional 10⁴ K soft-EUV component scaled to match this upper limit. Thus we can span the possible contributions from EUV.

For the abundance of each element relative to hydrogen in the wind, we follow typical values in the literature (e.g., Ercolano et al. 2009; Hollenbach & Gorti 2009; Wang & Goodman 2017), which are usually based on the depleted gas phase ISM abundances of Savage & Sembach (1996). These are detailed in Table 5.

mocassin uses the photoionization cross sections from Verner et al. (1996) for the outer (valence) shell ionization and Verner & Yakovlev (1995) for the inner shell ionization (which becomes relevant at X-ray energies). Figure 3 shows the total photoionization cross section for a neutral gas of this composition, along with those of Ne and Ar with their major ionization thresholds indicated. The charge on an ion may be lowered either by charge exchange, for which mocassin uses the values tabulated by Kingdon & Ferland (1996), or recombination, for which mocassin mostly follows (including for our species of interest) Badnell (2006a, 2006b).

Zoom In Zoom Out Reset image size

For each combination of density grid and spectrum, we run mocassin (Ercolano et al. 2003, 2005, 2008) for eight iterations with 10⁸ photon packets, followed by a final iteration with 10¹⁰ photon packets to reduce noisiness in the ionization state. The outputs include gas temperatures (Figure 1, first panel), electron densities (Figure 1, third panel), and emissivities of selected lines of interest in each cell (Figure 1, second row).

In Figure 4 we show examples of the [Ne ii] and [Ar ii] emission maps from mocassin projected to the inclination and position angle (on the MIRI-MRS detector) of T Cha and integrated both along the line of sight and in wavelength. All the images show diffuse, often extended, emission. Two other sorts of features can be seen. In the bottom row, a ring of emission at r_in—which is bright due to the additional ionization from soft-EUV incident on the inner edge of the wind—can be distinguished when the inner radius is large enough that it can dominate the flux (see also Figure 16). In the second row, distinctive conical shapes are seen which trace the limb-brightened ionization front inside of which the [Ne ii] emission is weak since most of the Ne is in Ne iii (see also Figure 15). This coincides with the τ = 1 surfaces for 20–40 eV photons near the L-shell ionization thresholds of Ne, meaning this wind model is optically thin to EUV at high altitudes but optically thick at the wind base.

Zoom In Zoom Out Reset image size

The most simple product from the radiative transfer simulations is the total luminosity of each emission line. We use the fluxes directly from MOCASSIN, rather than from the synthetic images that we later create. This is because, despite our best efforts (Section A), we were not always able to reliably recover the total input line (or continuum) flux from the synthetic spectrum. To calculate the visible fluxes, we simply integrate over the volume of the wind, including only cells that we consider visible to the observer. For this purpose, we assume that the midplane of the disk is infinitely optically thick (with all other material being optically thin) inside the R_out = 220 au gas disk (Huélamo et al. 2015), except for possibly inside a dust cavity of R_cav = 15 au (C. Xie et al. 2024, in preparation). Thus, any cell in the wind on the far side of the disk is only included if the line of sight does not cross the optically thick midplane. Mathematically this means we mask out cells where z < 0 and

$$\begin{eqnarray}&&{R}_{\mathrm{cav}}^{2}\lt {\left(R\cos (\phi )-z\tan (i)\right)}^{2}+{\left(R\sin (\phi )\right)}^{2}\lt {R}_{\mathrm{out}}^{2}.\end{eqnarray} \tag{ 9 }$$

To obtain the line shape, in each cell we calculate a thermally broadened Gaussian centered on the line of sight velocity v_los (e.g., Rybicki & Lightman 1979)

$$\begin{eqnarray}&&L({\rm{v}};{\boldsymbol{r}})=\displaystyle \frac{1}{\sqrt{2\pi }{{\rm{v}}}_{\mathrm{th}}}\exp \left(-\displaystyle \frac{{\left({\rm{v}}-{{\rm{v}}}_{\mathrm{los}}\right)}^{2}}{2{{\rm{v}}}_{\mathrm{th}}^{2}}\right){\rm{L}}({\boldsymbol{r}}),\end{eqnarray} \tag{ 10 }$$

where ${v}_{\mathrm{th}}=\sqrt{{m}_{H}/{m}_{i}}{c}_{{\rm{S}}}$ (for isothermal sound speed c_S) and

$$\begin{eqnarray}\begin{array}{rcl}{v}_{\mathrm{los}} & = & (-\sin (\theta )\cos (\phi )\sin (i)-\cos (\theta )\cos (i)){v}_{r}\\ & & +\ (-\cos (\theta )\cos (\phi )\sin (i)+\sin (\theta )\cos (i)){v}_{\theta }\\ & & +\ \sin (\phi )\sin (i){v}_{\phi }.\end{array}\end{eqnarray} \tag{ 11 }$$

v_r and v_θ are obtained from the self-similar models by normalizing to the local c_S calculated from the mocassin temperatures. We assume the azimuthal component equals the Keplerian velocity v_ϕ = v_K at the base and conservation of angular momentum along each streamline.

The contribution of all visible cells to the line profile is then summed, and the resulting profile convolved with a Gaussian of width 10 km s⁻¹ in order to degrade the profile to the typical R = 30,000 spectral resolution of high-resolution [Ne ii] spectra (Pascucci et al. 2020). Somewhat higher resolution [O i] spectra are available, so for comparison to those, we assume R = 45,000.

To produce synthetic JWST observations, we use the MIRISim python package Version 2.4.2 (Klaassen et al. 2021). MIRISim allows a "scene" to be built from several components. It then simulates an observation of this scene by the MIRI instrument of choice suitable for input into the pipeline: in our case, detector images from the Medium Resolution Spectrometer. In so doing, it accounts for several distortions and transformations due to both the optics and detectors. A few features were missing or needed correcting or updating in MIRISim. We briefly summarize the modifications we made in Appendix A. We note that MIRISim does not yet model the contribution of stray light (so we disable this step when reducing the data) and that there is a known inconsistency with the handling of reference pixels as of Version 2.4.2.

The simulation settings, such as the dither pattern, number of integrations, and groups per integration were kept the same as the observational settings (Pascucci et al. 2021; Bajaj et al. 2024) such that the spatial sampling and exposure are comparable to the real data.

2.4.1. Scenes

2.4.2. Reduction

In order that initially we are not sensitive to overall scalings such as abundances, we start by comparing the predicted Ne ([Ne iii] 15.55 μm to [Ne ii] 12.81 μm) and Ar ([Ar iii] 8.99 μm to [Ar ii] 6.98 μm) line ratios from our models. We expect these quantities to provide information about the levels of ionization and EUV heating in the wind (Hollenbach & Gorti 2009) as well as about the shape of the EUV/X-ray spectra.

In Figure 5, we compare the predictions of our T Cha models with these data. The equilibrium ionization should result from balancing the rate of photoionizations (collisional ionization is largely negligible at wind temperatures, Glassgold et al. 2007), which depends on the spectrum, and the rate of recombinations or charge exchange to lower ionization states, which depends largely on density. Therefore, each panel shows a different density normalization (expressed in terms of the observable mass-loss rate), while each series of points shows a different spectrum.

Zoom In Zoom Out Reset image size

We first consider low mass-loss rates $\dot{M}\lesssim {10}^{-9}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}$ (upper panels of Figure 5). In the photoevaporative scenario, these are the rates typically achievable by EUV-driven photoevaporation (Shu et al. 1993; Hollenbach et al. 1994; Wang & Goodman 2017), including considering the upper limit on the EUV photon flux of T Cha (see Section 2.1.2). This is because for EUV to drive the wind launching throughout the wind, the whole wind must be optically thin to the EUV photons, and as such must have a low density. In turn, at these low densities, only the EUV in the spectrum is effectively absorbed, while the X-rays in the spectrum will pass through the wind almost unnoticed. These EUV winds always have ionization fractions of essentially unity and temperatures of ∼10⁴ K.

We see that for all spectra considered, these low mass-loss rate models have L_{[Ne III]}/L_{[Ne II]} > 1 and L_{[Ar III]}/L_{[Ar II]} > 1, in complete contrast to all of the data. The reason can be understood by comparing the spectra to the outer shell ionization energies of Ne i (21.56 eV), Ne ii (40.96 eV), Ar i (15.76 eV), and Ar ii (27.63 eV), which all correspond to photon energies in the EUV. Since the wind has temperatures far exceeding the ∼1000 K excitation temperatures of the mid-IR emission lines, the line ratio will be proportional to the ratio of the abundances of each ion. Moreover, the ionization balance will be between the direct photoionization by hard-EUV photons of Ne ii to Ne iii (or Ar ii to Ar iii) at rate Φ₂₃ and the recombination of free electrons with the ions at electron-density-dependent rate ${R}_{32}^{\mathrm{rec}}({n}_{{\rm{e}}})$:

$$\begin{eqnarray}&&\displaystyle \frac{{n}_{\mathrm{III}}}{{n}_{\mathrm{II}}}=\displaystyle \frac{{{\rm{\Phi }}}_{23}}{{R}_{32}^{\mathrm{rec}}({n}_{{\rm{e}}})}.\end{eqnarray} \tag{ 13 }$$

Since in these highly ionized environments the electron fraction (and temperature) will have more or less saturated, the ratio of the ion abundances becomes simply a measure of the ionizing photons. To produce abundant Ne ii in the wind but not Ar iii, one would require a spectrum with abundant photons above 21.56 eV but negligible photons above 27.63 eV. Such a spectrum can only be achieved if the emitting plasma is all ≲10⁴ K, but not in the presence of hot ∼10⁷ K X-ray emitting plasma—as is required to explain T Cha's X-ray spectrum—since that has a continuum tail that extends into the EUV. While one might be able to screen out the EUV by some attenuating material near to the star, the only radiation available to drive the wind would be X-rays which are expected to produce much denser winds and hence higher mass-loss rates (despite the slightly lower temperatures); such a model would not be self-consistent.

Moreover, note how, in line with Equation (13), the ratios predicted by the loLX_TCha, Ercolano_RSCVn, and hiLX_TCha spectra are so arranged in order of their EUV photon fluxes. However, the additional T₃ = 10⁴ K EUV component added to the loLX_TCha_sUV and hiLX_TCha_sUV spectra mostly contributes flux below 20 eV (i.e., it is quite soft). Hence, in line with the ionization energies discussed above, it does not contribute to Φ₂₃ and thus cannot contribute to the secondary ionization of Ne or Ar (this is similar to the argument of Hollenbach & Gorti 2009, that to produce L_{[Ne III]}>L_{[Ne II]} requires a hard-EUV spectrum). Consequently, these spectra do not produce significantly different results for the ionization in this regime from their counterparts with no explicit EUV component.

Moving to the higher densities, we see that the line ratios are much lower as the denser gas can lower its ionization through recombination or charge exchange more easily. Henceforth we should therefore consider only winds with nominal mass-loss rates ≳0.3 × 10⁻⁸ M_⊙ yr⁻¹, which will be X-ray-heated winds (though their innermost regions may be EUV-heated) as the only self-consistent scenario able to produce line ratios that are remotely consistent with the range 0.045 < L_{[Ne III]}/L_{[Ne II]} < 0.13 observed for most sources, including T Cha. The highest density $\dot{M}=1\mbox{--}3\times {10}^{-8}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}$ models are particularly favored as they most closely cluster around the observed range.

Nevertheless, these models still somewhat overpredict the Ar line ratio for T Cha. At these densities, the abundance of Ar iii is controlled by the balance of its production via inner (L) shell ionization by photons with energies ≳250 eV and charge exchange with hydrogen (or recombination with free electrons) forming Ar ii, while that of the Ar ii is results from the balance of its production from charge exchange between Ar iii and its recombination with free electrons. Therefore, the overall ionization balance of Ar may, similar to that of Ne (Glassgold et al. 2007), obey $\tfrac{{n}_{\mathrm{III}}}{{n}_{\mathrm{II}}}\propto {L}_{{\rm{X}}}^{1/2}$. To lower the degree of ionization, the spectrum must contain somewhat fewer soft X-ray photons, though not so few that we no longer reproduce the observed Ar ii luminosity. The weaker dependence of the Ar ii abundance on the X-ray luminosity means that this is a reasonable way to lower the [Ar iii] flux without strongly affecting the [Ar ii] flux. Thus, it is likely that the spectra we utilize contain slightly too many soft X-ray photons (while having the appropriate number of hard X-ray photons ≳870 eV to produce the right ratio of the Ne lines). This is not surprising since the soft end of the spectrum is the most easily absorbed and thus the hardest to constrain accurately observationally; it could also be more easily screened between the star and disk. Since the [Ar iii] line is only fairly weakly detected and does not play a critical role in the arguments we make henceforth, we do not try to adjust the spectrum.

Note that the addition of a soft-EUV component at these higher mass-loss rates lowers the line ratios (as is most easily seen by comparing the loLX_TCha spectra). This results since these winds are in a partially ionized regime, where additional soft-EUV flux raises the electron density (which scales with the square root of the ionization rate Φ: Glassgold et al. 1997; Igea & Glassgold 1999; Glassgold et al. 2007), and thus the recombination rates of Ne iii to Ne ii and Ar iii to Ar ii (while being unable to directly produce the doubly ionized species as discussed above, see also Hollenbach & Gorti 2009). Given the low observed line ratios, it is therefore generally favorable to include the additional soft-EUV component. This, along with the suggestion that our models may contain excessive soft X-ray, is in line with the argument presented by Bajaj et al. (2024) that the high L_{[Ar II]}/L_{[Ar III]} suggests EUV ionization of Ar, not (just) soft X-ray ionization.

We can now turn our attention to the absolute luminosities, focusing, as argued above, on higher (nominal) mass-loss rates as appropriate to an X-ray regime. The luminosities of the two Ne lines are compared in Figure 6. For each spectrum, we show models with five different inner radii (as indicated by the point size).

Zoom In Zoom Out Reset image size

At each point in the wind, the line emissivities should scale with the abundance of the relevant species. In turn, the total amount of these species across the whole wind will correlate positively with the amount of ionizing X-ray absorbed: L_X,abs = L_X(1 − e^−τ ). So long as the gas remains optically thin to these X-rays (as is the case for Ne as argued above), then ${L}_{{\rm{X}},\mathrm{abs}}\approx {L}_{{\rm{X}}}\tau \propto {{NL}}_{{\rm{X}}}\propto {L}_{{\rm{X}}}\dot{M}$. We therefore expect that models with both higher luminosity and high mass-loss rates should produce brighter [Ne ii] emission.

Comparing the panels of Figure 6, we see that indeed the 1–3 × 10⁻⁸ M_⊙ yr⁻¹ models are more luminous in [Ne ii] than the 3–5 × 10⁻⁹ M_⊙ yr⁻¹ models as there is a greater column of gas to absorb the X-rays and produce ionized Ne emission. While the most luminous of the latter set does approach the [Ne ii] luminosity of T Cha, it does so at much too high a [Ne iii] luminosity as these are disks with large inner radii and low peak densities that can reach a higher degree of ionization. ¹⁰ Thus, we favor 1–3 × 10⁻⁸ M_⊙ yr⁻¹ as the only models capable of reaching the observed [Ne ii] luminosity of T Cha at the right [Ne iii] luminosity.

Comparing the performance of the different spectra, we can see that the observed value is straddled by the higher luminosity spectra hiLX_TCha and hiLX_TCha_sUV and the other lower luminosity spectra. This means that a key component of a favored model is a high L_X as found in the hiLX_TCha or hiLX_TCha_sUV spectra.

Since all of our models remain optically thin to the hard X-rays that ionize Ne, each point in the wind receives essentially the same X-ray luminosity regardless of the assumed r_in and thus total column density. Conversely, the EUV ionization is confined to a thin Strömgren layer close to wherever most of the column density is accumulated (in our case the inner boundary of the simulation). The EUV-ionized layer can become considerably ionized, with electron fractions close to unity, i.e., n_e ∼ n_gas. Given Equation (5) and the r^−1.5 profile in our models, the gas density at the base reaches n_gas ∼ n_crit for r ∼ 1.9 r_G . Thus, so long as r_in ≲ 1.9 r_G , then in the EUV-heated region n_e ∼ n_gas > n_crit. On the other hand, the X-ray heated region has n_e ≪ n_H and so achieves n_e > n_crit only at a radius r_crit ≪ r_G . Consequently, the critical density of electrons is usually reached in the EUV-ionized inner parts of the wind only and thus r_crit ∼ r_in.

The result is that the [Ne ii] emissivity in the X-ray-heated regions is not sensitive to critical density effects or the inner radius. The contribution of these regions decreases slightly as the inner radius is increased simply because of the loss of flux from small radii. The much more important dependence on the inner radius comes through the EUV-heated region. Since this region is mostly supercritical, then its flux depends as ${r}_{\mathrm{crit}}^{3-b}$. The contribution from this thin inner ring—which can be seen clearly in the bottom row of Figure 4—thus grows strongly as the inner radius is increased, only saturating at r ≳ r_G once the gas density is too low for even a fully ionized gas to reach the critical density. As a consequence, increasing r_in typically has a positive effect on the luminosity at 1–3 × 10⁻⁸ M_⊙ yr⁻¹ (a stronger effect is seen for 3–5 × 10⁻⁹ M_⊙ yr⁻¹ where the contribution of the EUV-heated region is relatively larger since less of the X-ray is absorbed). However, despite this dependence, we cannot use Ne line luminosities alone to constrain r_in as whether a large or small radius is preferred depends on whether the wind spectrum has a low or high L_X, respectively, and there is enough observational uncertainty in this value.

Although not tuned for either of the other systems, this set of high $\dot{M}$ models is also broadly consistent with the [Ne ii] and [Ne iii] fluxes for V4046 Sgr, CS Cha, and TW Hya. Taken at face value, TW Hya would appear to require a lower luminosity spectrum, a reasonable outcome given its later spectral type than the other stars. Moreover, it is also known to have a softer spectrum in which the hardest 2–3 × 10⁷ K component usually present in the X-ray spectrum of T Tauri stars (e.g., Preibisch et al. 2005) is absent (Nomura et al. 2007). Hence it will likely produce fewer photons at ∼1 keV that are able to ionize Ne and should be studied more in the future with more tailored spectra.

We can get a better constraint by comparing the [Ne ii] and [Ar ii] luminosities (Figure 7). At $\dot{M}=1\mbox{--}3\times {10}^{-8}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}$, we see a much stronger dependence on the inner radius for the [Ar ii] than for the [Ne ii]. There is generally little difference between the models with and without soft EUV, showing that [Ar ii] is mostly produced by soft X-rays. The r_in dependence then arises since these soft X-rays are more easily absorbed, and thus the contribution of the X-ray-ionized region now depends on the assumed inner radius because of its effect on the attenuating column density (Equation (8)). Thus, for our high L_X spectra, the [Ar ii] flux taken in combination with the [Ne ii] suggests that an inner radius of around 0.1 r_G gives the appropriate column density. Lower luminosity spectra with large inner radii would tend to overpredict [Ar ii] relative to [Ne ii]. However, one caveat is the possibility, as discussed above, that our spectra contain slightly too many soft X-ray photons, which might make the larger inner radii less unfavorable.

Zoom In Zoom Out Reset image size

For comparison, we also include in Figure 6 the luminosities calculated by Ercolano & Owen (2010) by postprocessing radiation hydrodynamic simulations of both full ("primordial") disks and those with a transparent gas cavity ("inner hole," which show significant emission near the midplane from the flow emanating from the directly irradiated cavity rim). Although designated a transition disk (on account of an inner hole in its dust emission), T Cha shows no evidence for a significant inner gas cavity (Wölfer et al. 2023), and hence the appropriate model for comparison is the L_X = 2 × 10³⁰ erg s⁻¹ primordial disk, with L_{[Ne II]}=2.07 × 10²⁸ erg s⁻¹ and L_{[Ne III]} = 4.06 × 10²⁷ erg s⁻¹ (indicated by the blue, borderless, square near the center of each panel). The underlying simulation had a mass-loss rate of 1.36 × 10⁻⁸ M_☉ yr⁻¹. We see that for comparable estimated observable mass-loss rates ≳10⁻⁸ M_☉ yr⁻¹ (right-hand panel), this point lies close to our Ercolano_RSCVn models (blue circles) with a relatively large wind radius (the closest model predictions are for an inner radius ∼r_G ). Thus despite the simplified hydrodynamic model we use, our results are in concordance with more sophisticated treatments of X-ray-driven photoevaporation and suggest that despite mass-loss extending somewhat further in, the column density may be mostly accumulated around r_G .

Hollenbach & Gorti 2009 studied the same line ratios as here, showing how they depend on the ionizing spectrum. They argued that a "hard-EUV" spectrum, where there are a substantial number of photons at energies above 41 eV (the second ionization energy of Ne), was necessary to get L_{[Ne III]}>L_{[Ne II]}. On the contrary, a "'soft-EUV" spectrum such as produced by blackbody emission up to a few × 10⁴ K or an X-ray spectrum, which produces weakly ionized gas, would result in L_{[Ne III]}<L_{[Ne II]}. This has been used by Szulágyi et al. (2012) and Bajaj et al. (2024) to argue against a hard-EUV model. Moreover, due to a cancellation of the effects of many atomic parameters, L_{[Ne II]}/L_{[Ar II]} ∼ 1 in either a soft-EUV case or soft X-ray case, whereas a hard X-ray spectrum is much better at ionizing Ne than Ar and should produce a ratio ∼2.5 (Hollenbach & Gorti 2009; Szulágyi et al. 2012).

Our spectra contain both soft and hard X-rays, as well as hard EUV (in the low-energy tail of the X-ray spectrum), and, in the case of the Ercolano_RSCVn, hiLX_TCha_sUV and loLX_TCha spectra, soft EUV from plasma at ∼10⁴K. The outcome is thus determined by which parts of these spectra are absorbed and where. At low mass-loss rates, the wind is optically thin to the EUV, and X-ray is barely absorbed, so we find ratios that are as expected for a hard-EUV model. Our higher mass-loss rate models are not well penetrated by the EUV, so most of the wind ends up with the ratios predicted by an X-ray model. When the inner radius is large, the wind is optically thin to both soft and hard X-rays, so we get L_{[Ne II]}/L_{[Ar II]} ∼ 1. However, Figure 7 shows that when the inner radius becomes small enough (r_in ≲ 0.1 r_G ), L_{[Ne II]}/L_{[Ar II]} > 1. This happens because the soft X-rays (and EUV) are absorbed close to the star, meaning that most of the wind is now absorbing only hard X-rays, thus raising the value of L_{[Ne II]}/L_{[Ar II]}, Nevertheless, in the r_in = 0.1 r_G case, this ratio is only just more than 1, so is still just within the range of soft X-ray models. Thus our results are all in line with those of Hollenbach & Gorti (2009).

In conclusion, the information obtained from the line ratios should be understood as tracing which parts of the spectrum are being absorbed and hence as a constraint on the wind's column density. Being optically thin to hard X-rays but optically thick to soft X-rays (and EUV) suggests a column density 3 × 10²⁰ ≲ N / cm⁻² ≲ 10²².

We synthesize and analyze MIRI-MRS observations of the [Ne ii] and [Ar ii] lines based on our model set hiLX_TCha_sUV with $\dot{M}=1\mbox{--}3\times {10}^{-8}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}$ using MIRISim (Klaassen et al. 2021) as described in Section 2.4. We choose this set as it generally best reproduces the Ne line luminosities and thus requires minimal rescaling of the fluxes (to ensure we are equally as sensitive as the observations). We investigate models both with and without a transparent 15 au cavity in the dust disk (which determines whether emission from the backside can be seen or not). Example synthetic images of the two lines for the model with r_in = 0.1 r_G and including a cavity are shown in the central panels of Figure 8. These may be compared to the unconvolved models of the lines in the left-hand panels; evidently, the morphology of the underlying emission is not apparent, and the image more closely resembles the PSF. The images look broadly similar to the observations presented by Bajaj et al. (2024) of the lines for T Cha (right-hand panels), although some details of the PSF shape are somewhat different, and the synthetic PSF (Gaussian fit indicated in green) is slightly larger, a known issue with MIRISim. Nevertheless, we will now show that useful information can still be derived from these images.

Zoom In Zoom Out Reset image size

For each synthetic image, 2D Gaussian fitting is performed using the imfit task from the Common Astronomy Software Application (CASA, McMullin et al. 2007) package in the wavelength channels with peak line emission as described in Section 3.2.1 of Bajaj et al. (2024). We use a Gaussian for simplicity, to be consistent with the observational analysis in Bajaj et al. (2024), and to make estimates of the deconvolved size tractable. Moreover, from an observational perspective, a more appropriate morphology would not be known a priori, although since the PSF dominates the morphology, a rounded shape that can describe its core is more suitable than any function more closely describing the underlying wind morphology or PSF side lobes. The same fitting procedure is applied to the simulated PSF at the line wavelength. Each fit is described by the FWHM along the major and minor axes and the position angle (PA) of the major axis, which we report in Table 7. These Gaussian fits for the synthetic images, and observations are superposed on the central and right-hand panels of Figure 8 as the white dashed lines and by eye do an adequate job of describing the core of the emission.

Table 7. The FHWM and PA Resulting from 2D Gaussian Fitting to the (Synthetic) Observations of the Line Emission and PSF (Convolved Values) and that Estimated for the Underlying Emission Using the Eigenvector Analysis on Equation (14) Described above (Deconvolved Values)

	[Ne ii]				[Ar ii]
	Convolved		Deconvolved		Convolved		Deconvolved
	Major/Minor Axis	PA	Major/Minor Axis	PA	Major/Minor Axis	PA	Major/Minor Axis	PA
	(mas)	(°)	(mas)	(°)	(mas)	(°)	(mas)	(°)
HD37962	552/543	99 ± 25			366/294	61 ± 2
HD167060	557/530	64 ± 75			373/294	63 ± 3
Simulated Standard Star	710/675	134 ± 5			500/320	98 ± 1
Observed Continuum		115 ± 3
Simulated Continuum		147 ± 1
T Cha (HD37962)	614/583	55 ± 8	279/199	48	376/295	64 ± 2	<91	82
(HD167060)			263/238	33			52/13	88
rin = 0.03 rG	767/741	93 ± 10	343/245	65	547/356	98 ± 1	222/156	98
rin = 0.1 rG	770/743	95 ± 8	348/254	66	537/346	98 ± 1	196/132	98
rin = 0.3 rG	798/767	92 ± 10	406/317	68	562/373	99 ± 1	257/191	104
rin = 1 rG	785/753	112 ± 7	361/306	79	619/440	102 ± 1	369/297	115
rin = 3 rG	1139/956	63 ± 2	915/644	61	1192/866	70 ± 2	1100/780	64
rin = 0.03 rG , Rcav = 15 au	738/716	102 ± 10	271/173	64	519/345	97 ± 1	145/123	66
${{\boldsymbol{r}}}_{\mathrm{in}=0.1\,{r}_{G}}$, R cav=15 au	740/718	103 ± 11	267/162	64	512/340	98 ± 1	115/110	8
rin = 0.3 rG , Rcav = 15 au	768/742	94 ± 9	345/289	65	536/363	98 ± 1	193/171	98
rin = 1 rG , Rcav = 15 au	780/750	109 ± 8	354/293	75	597/436	101 ± 2	331/291	120
rin = 3 rG , Rcav = 15 au	1136/953	63 ± 2	911/639	61	1180/857	69 ± 2	1088/769	63

Note. For the observations, two sets of deconvolved values are given corresponding to each standard star model. To provide a reference direction, the PA of the continuum in the same wavelength channel as the [Ne ii] line is given for both the observations and synthetic images. r_in is the inner edge of the wind, while R_cav is the size of the transparent dust cavity. The bold rows highlight the relevant observed values and the overall best-fitting model for comparison.

Download table as:  ASCIITypeset image

Within the formula for a 2D Gaussian, the FWHM and PA may be summarized in the correlation matrix C . Under the assumption that the underlying emission and PSF can both reasonably be modeled by such a Gaussian, the correlation matrix of the observed (convolved) emission is simply the sum of the correlation matrices of these two (unconvolved) components. Thus, the deconvolved correlation matrix of the underlying emission may be estimated as the difference between the correlation matrices of the line emission and the PSF:

$$\begin{eqnarray}&&{{\boldsymbol{C}}}_{\mathrm{dec}}={{\boldsymbol{C}}}_{\mathrm{obs}}-{{\boldsymbol{C}}}_{\mathrm{PSF}},\end{eqnarray} \tag{ 14 }$$

where each matrix has the form:

$$\begin{eqnarray}{{\boldsymbol{C}}}_{i}=\left[\begin{array}{cc}{F}_{i,1}^{2}{c}_{i}^{2}+{F}_{i,2}^{2}{s}_{i}^{2} & ({F}_{i,1}^{2}-{F}_{i,2}^{2}){c}_{i}{s}_{i}\\ ({F}_{i,1}^{2}-{F}_{i,2}^{2}){c}_{i}{s}_{i} & {F}_{i,1}^{2}{s}_{i}^{2}+{F}_{i,2}^{2}{c}_{i}^{2}\end{array}\right]\end{eqnarray} \tag{ 15 }$$

for major- and minor-axis FWHM F₁ and F₂ and where we use the shorthand ${c}_{i}=\cos ({{PA}}_{i})$, ${s}_{i}=\sin ({{PA}}_{i})$.

The major- and minor-axis extents of this component can be calculated as the square roots of the eigenvalues of the estimated deconvolved correlation matrix C _dec. The position angle of the emission is obtained from the direction of the eigenvector of C _dec corresponding to the larger eigenvalue. Assuming the eigenvalues are both positive, then since the emitting area at half maximum of the Gaussian is given by $\tfrac{\pi }{4}{\mathrm{FWHM}}_{\mathrm{maj}}\ast {\mathrm{FWHM}}_{\min }$, we may calculate the effective emitting size from the eigenvalues as ${\mathrm{HWHM}}_{\mathrm{eff}}=0.5\sqrt{{\mathrm{FWHM}}_{\mathrm{maj}}\ast {\mathrm{FWHM}}_{\min }}$. If, however, one of the eigenvalues is negative, our deconvolved matrix no longer represents a Gaussian. We take this as an indication that the emission is unresolved; where we require a value to include in the figures, we use an upper limit based solely on the single positive eigenvalue.

The parameters of all of the 2D fits are reported in Table 7 as the "convolved" values, while the values that we estimate as described in the preceding paragraphs are reported as the "deconvolved" values. We also report the parameters for a fit to the continuum emission. This allows us to quote the estimated deconvolved position angle of the line emission relative to the continuum in order to account for differences between MIRISim's assumed direction of north and that of the observations.

Note that we also tested using the horizontal and vertical cuts, as shown in Figure 3 of Bajaj et al. (2024), but these performed much less well at matching the observed PA, which we attribute to differences in the shape of the PSF between the MIRISim model and observations. The 2D Gaussian fits are able to average over any such differences and are also somewhat more sensitive to the extended emission.

In Figure 9 we show the results of the Gaussian fitting to the [Ne ii] 12.81 μm emission for our hiLX_TCha_sUV model set as a function of r_in, with uncertainty estimates produced by propagating the uncertainty on the PA in each Gaussian fit. To contextualize the values, the right-hand axis shows the calibration to a projected distance R_eff from T Cha, assuming a distance of 102.7 pc. The horizontal black lines represent the value from the real observations using two different standard stars—HD37962 and HD167060—as models for the PSF for the deconvolution. Comparison to the propagated statistical errors suggests that the PSF model is likely the dominant source of uncertainty in our derived values. The estimated sizes correspond to a scale of 12–13 au, a value which lies intriguingly close to T Cha's gravitational radius.

Zoom In Zoom Out Reset image size

To facilitate further interpretation, the solid gray line in each figure panel indicates where the projected separation of the effective half width at half maximum (HWHM) R_eff (from now on, the "effective radius") is equal to the inner radius of the model. For r_in ≳ r_G , the R_eff of the synthetic images lies close to this line. This suggests that for winds restricted to large radii, the extent of the emission traces the inner radius of the wind: this is the case discussed in Sections 2.2 and 3.2 where a bright inner ring of EUV-heated material near the inner radius dominates the emission.

One reason for targeting T Cha was that the continuum emission shows a large ∼33 au cavity at mm wavelengths (Francis & van der Marel 2020), equivalent to ∼3 r_G . Since the [Ne ii] profile has a net blueshift, the redshifted wind from the far side of the disk must be obscured by dust, which may imply little to no emission at radii inside the mid-IR dust cavity. Thus, if the dust cavity were the same size at mid-IR wavelengths, we should expect to resolve the emission. Our models confirm that if the wind's [Ne ii] emission only started beyond 30 au, then we would indeed be able to recover this scale from the observations. However the observations suggest emission that is more compact R_eff ≲ r_G (as expected for photoevaporation from a full disk). Moreover (although not believed to be the case for T Cha, Wölfer et al. 2023, and hence not included in our model), even if there were an optically thin gas cavity in the underlying disk extending to radii R_cav ≳ 30 au, emission could still be found at radii R < R_cav (e.g., Ercolano & Owen 2010) since material launched sonically from the cavity wall flows inward initially, reaching roughly r_G (Alexander et al. 2006; Owen et al. 2010).

On the other hand, we see that (for cases both with or without a dust cavity) there is a very shallow dependence of R_eff on r_in for r_in ≲ r_G , with R_eff ∼ 10–20 au in all cases. This means that the extent of the Ne ii emission can only place a relatively unconstraining upper limit on the innermost extent of the wind, and a much more compact inner radius <r_G could also be consistent with the observations. That said, given the relatively small uncertainties, it may still be possible to distinguish: the closest agreement is with our model with r_in = 0.1 r_G and including a 15 au dust cavity, consistent with the rest of our picture of this source.

The reason for this shallow dependence is that, as discussed in Section 3.2, the extended emission due to X-ray photoionization dominates for small inner radii. Indeed the deconvolved Gaussian estimate overlaid on Figure 8 shows that the size retrieved contains a little more than just the bright central core, indicating that extended emission contributes to the effective size. Since it can be argued that a) for our density normalization, the strongly inner-radius-dependent EUV-ionized component stops dominating the flux for r_in ≲ r_G on the basis of critical density arguments and b) once the extended X-ray-ionized component comes to dominate, there is weak dependence on the inner radius as all the models are optically thin to the >870.1 eV photons needed to ionize Ne, then it is logical that the scale that is preserved is similarly on the order of r_G . While the X-ray-induced emission has no direct sensitivity to this scale, the intrinsic scale of this emission would have to be much smaller and its flux contribution correspondingly lower for the strongly r_in-dependent EUV component to dominate and produce an overall r_in dependence at much smaller sizes.

The measured sizes thus suggest that the [Ne ii] emission traces an X-ray-ionized wind extended to at least ∼12 au. We can achieve this in our models with appropriate densities and inner radii such that the column of material inside 12 au is no more than ∼10²² cm^−2. The agreement with the observed scale suggests that these models are a decent representation of T Cha and that the same constraint on column density also applies to the observations. Were the column density on these scales any higher, then Ne could only be ionized (and thus produce 12.81 μm emission) at radii smaller than those observed. This would happen in the case of a higher mass-loss rate (or the same mass-loss rate spread over a smaller extent, thus resulting in a higher density) or an even smaller inner radius than those explored.

It is notable that all the r_in that can be consistent with the data are ≲r_G and thus also ≲R_cav ≈ 15 au inferred from the SED fits. Thus, we also showed in Figure 9 (as the cyan points) the effective radius for models with a transparent dust cavity (this is simply a condition on which parts of the wind can be seen; we do not change the gas structure) and noted above that a model with a cavity is the best fit for the measured size. For r_in ≳ r_G , the results are unaffected since most or all of the emission originates outside of the cavity radius and hence cannot be seen through the cavity. However, for smaller r_in, the radius is reduced as the emission becomes more centrally concentrated in the presence of a cavity. The fact that a change can be seen emphasizes that the measured size is also sensitive to extended emission on scales larger than the cavity: if we were only measuring emission inside the cavity radius, then hiding emission from the backside with an optically thick disk would not make the emission more extended but simply fainter.

In the right-hand panel of Figure 9 we also show the PA of the emission. The observations show a PA offset of 113° and 98° between the wind and disk when HD37962 and HD167060 respectively are used as the PSF model. The simulations—with or without a dust cavity—are generally in very good agreement with HD167060 while the r_in = 0.1 r_G has better agreement with HD37962. In all cases, these values are relatively close to 90° and the deconvolved Gaussian estimate overlaid on Figure 8 is clearly approximately perpendicular to the disk plane. This is reasonable for a source viewed close to edge-on since winds involve the launch of material away from the disk plane; cancellations due to symmetry about the rotation axis should then lead to an average PA of 90°. Note that since for any morphology that is symmetric about the rotation axis, the PA should average out to either 0° or 90°. The fact that we retrieve a value consistent with one of these is a vindication of the 2D Gaussian fits and our deconvolution estimate being a sufficient way to derive information about the intrinsic emission structure. Moreover, we also consider that 90° is the direction separating the red- and blueshifted lobes of emission from the backside and frontside of the disk, respectively. However, the two lobes are clearly not resolved in the synthetic image, and the recovered scale is slightly less than their separation. This suggests that the PA and effective size are not negatively affected by this bipolar structure. In the worst case it is simply part of the extended emission component and does not prevent a Gaussian being a sufficiently good fit to retrieve sensible information about the overall presence of this component.

However, the PA values do seem to be somewhat biased toward slightly larger angles than 90°. This suggests some asymmetry is at hand. One possible physical explanation may be that the fits are performed on the brightest wavelength channel at 12.8138 μm, which is slightly redward of the rest wavelength and thus also the blueshifted line centroid. Given the sense of the rotation of the disk (Huélamo et al. 2015), the southwest of the image is slightly less blueshifted—as this material is rotating away from us—than the southeast of the image, which is rotating toward us. Though the line is spectrally unresolved, the southwest should still contribute slightly more on the redshifted side of the line. The rotation of the wind material could thus be biasing the fits toward the southwest of the image and increasing the PA from 90° slightly. On the other hand, if, unlike the Gaussian assumed in the fitting, the PSF is not symmetric about the major axis, then this could also bias the measured PA.

For [Ar ii], no extension is detected in the observations according to our deconvolution method and eigenvalue analysis for either PSF. As such, although a PA can be calculated for the eigenvector corresponding to the positive eigenvalue, it is not very physical and is very uncertain as indicated by the large shaded error regions.

For models with larger r_in ≳ r_G , Figure 10 shows similar behavior for [Ar ii] as seen for the [Ne ii], where the effective radius is a good measure of the inner radius. These are cases with a significant contribution from the EUV-ionized inner regions. However, while the dependence of R_eff on r_in initially flattens off a little at small radii, there is more dependence than was seen for [Ne ii]. The closest agreement with the observed sizes is again for r_in = 0.1 r_G , though the larger value seen for r_in = 0.03 r_G possibly results from sensitivity issues. The position angles have very large error bars since the emission is barely resolved, allowing essentially any orientation of the underlying emission to be consistent with the synthetic image.

Zoom In Zoom Out Reset image size

Earlier, we argued that the line ratio of [Ne ii] and [Ar ii] was at the higher end of what is considered achievable with soft X-rays (Hollenbach & Gorti 2009) and best reproduced if we were moving toward a regime where a large part of the outer wind is only penetrated and ionized by hard X-rays and soft X-rays are screened out by its inner parts. The behavior seen here also occurs because unlike Ne ii, which is produced by hard (≳870 eV) X-rays that can penetrate all our wind models, Ar ii is produced by soft (∼250 eV) X-rays (and EUV). For r_in ≤ 0.1 r_G , the wind becomes optically thick to these photons, which penetrate only its inner parts, thus restricting the emitting area of [Ar ii] significantly (and reducing the line flux). The overlaid deconvolved Gaussian estimate in Figure 8 illustrates this point, that in this case the emission is dominated by the bright inner core, with any extended component being relatively insignificant. This makes the [Ar ii] emission more strongly dependent on the inner radius, and thus a more sensitive probe of the inner parts of the wind where the column density is accumulated than the [Ne ii]. Indeed, the extent provides stronger evidence than the line fluxes as it is not subject to uncertainties in the elemental abundances, which are challenging to determine even for our own Sun (see Asplund et al. 2021 for a discussion).

Figure 11 demonstrates that when the combination of the emitting extents of [Ne ii] and [Ar ii] are used together, the [Ar ii] being less extended than the [Ne ii] only occurs when r_in ≲ 0.3 r_G , thus allowing [Ar ii] to help break the degeneracy between different r_in present when considering [Ne ii] alone. Through the right-hand panel of the figure, we confirm that this is a behavior of the underlying simulations, which is preserved in the synthetic images. We show the spherical radius enclosing different fractions f of the flux in the model before it is converted into a synthetic image, including the 97% and 95% levels used to define the observable mass-loss rate (Section 2). We also show the 50% level, which is the flux contained within the HWHM of a 2D Gaussian, and is thus the most direct comparison to the parameters we infer from the synthetic images. For each f, we see the same picture as for the effective radii resulting from the deconvolution: inner radii r_in ≲ 0.1–0.3 r_G (and also higher mass-loss rates) are required to produce [Ar ii], which is intrinsically more compact than the [Ne ii]. This can also be seen directly in the emission maps in Figure 4: only the combination of a high mass-loss rate and small inner radius (third row) produces a significant difference between the extent of the two lines. Moreover, comparing the f = 95%/97% radii to the f = 50% radius reveals significant emission from scales ∼10 × that traced by the effective radius.

Zoom In Zoom Out Reset image size

Constraints on the origin of line emission can also be derived from spectrally resolved line profiles. In particular, the (deprojected) HWHM is an indicator of the innermost emitting region under the assumption of Keplerian broadening. We thus check how well our preferred models agree with high-resolution [Ne ii] (R = 30,000) and [O i] (R = 45,000) line profiles of T Cha (Pascucci & Sterzik 2009; Pascucci et al. 2020).

Initially we assume that the disk is optically thick throughout the midplane and the complete emission from the near side only is seen (Figure 12, left panels). We then consider two further effects. First, we assess how the presence of an optically thin dust cavity at <15 au affects the line profile (Figure 12, right panels). Second, we reassess both of these cases, taking into account the finite 04 width of the slit (Figure 13). Since the position angle of the slit was 0° (Pascucci & Sterzik 2009) and that of the disk is 113° (i.e., fairly close to perpendicular to the slit), then this means that emission separated by more than ∼20 au along the major axis may be missed.

Zoom In Zoom Out Reset image size

Zoom In Zoom Out Reset image size

In Figure 12 we see that as one would expect, especially for such a highly inclined disk, the smaller the inner radius, the broader the line profile. However, the modeled line profiles in the bottom panels when no dust cavity is included are visibly narrower than observed for all inner radii. This is confirmed in the upper panels where we compare the FWHM and centroid shift measured from our profiles to that of the data (as calculated by Pascucci et al. 2020). More encouragingly, our profiles are relatively consistent within uncertainties with the centroid blueshift. Nevertheless, the broad profile supports the case favored in Sections 3 and Sections 4 where the inner radius r_in of the wind is small (∼0.1 r_G ).

However, for the cases with r_in < R_cav, the introduction of a dust cavity leads to significant emission from the receding wind becoming visible. While this helps a little to broaden the profiles, it also shifts them toward no net centroid shift. Since the fractional error on the centroid shift (which for bright lines is dominated by the uncertainty of the stellar radial velocity, Pascucci et al. 2020) is larger than that on the FWHM, this may be a worthwhile trade-off. We also note that the normalized line profiles with a cavity actually agree very well with the red wing of the observed line for r_in ≤ 3.90 au. Our poor fit is a result of too strongly peaked emission near the line center and not enough on the blue wing of the line, i.e., insufficient emission at high velocities. Although T Cha is thought to have a smaller inner disk of ≲1 au—and even though our modeling prefers more compact inner radii where there is emission on these scales—in practice, since the emission is extended out to ∼10 au, plenty of the redshifted emission will still be visible through the cavity, and its effect on the line shape is not significantly reduced.

It is thus clear that T Cha's [Ne ii] line is broader than we can explain; this is consistent with previous works where it seems to be an outlier among similar disks in its breadth (Ballabio et al. 2020; Pascucci et al. 2020). It is not obvious how to create more emission at higher velocities within a photoevaporative model where the line kinematics are closely tied to the sound speed. In principle, part of the answer could be a greater sound speed: Ballabio et al. (2020) found that c_S = 10 km s⁻¹ was preferred for the [Ne ii] line. However, such values are only achieved globally in EUV-driven winds, which we have ruled out on the basis of line ratios. Our sound speed is already typically c_S ≈ 7 km s⁻¹ averaged across the wind, and our model already accounts for EUV heating, raising the temperature in the inner parts and using the temperature from the photoionization calculations to determine the sound speed locally. Thus there is limited scope to perfect the agreement with the data with hotter gas. On the other hand, emission could be removed from the line center if, for example, the outer regions are cooler than assumed here and do not reach the 1123 K excitation temperature of the 12.81 μm line (A. D. Sellek et al. 2024, in preparation).

Conversely, if a magnetocentrifugally launched wind achieves poloidal velocities v_p ∼ v_K(r < r_G ) then these will by definition be greater than the sound speed since r_G is defined as the location where the Keplerian orbital velocity and sound speed are equal. While the significant amount of material inside r_G suggested by our modeling probably can be explained with photoevaporation, if magnetocentrifugal forces contribute instead of or as well as thermal pressure force, the deviation of the kinematics there from those of a purely thermal wind may be sufficient to explain the observed line profile being broader and more blueshifted than our models can achieve. As simulations of MHD winds continue to be developed and improved—particularly with regard to their thermochemistry—they should be tested against these sorts of observations to see if they indeed provide a remedy. Nemer & Goodman (2024) provided a first step toward this using the simple analytic magnetothermal model of Bai et al. (2016) and indeed see that such models produce a much more extended blue wing of the [Ne ii] line than the same models in the purely photoevaporative limit. Nevertheless, these models underpredict the luminosity of the line by an order of magnitude compared to typically observed values.

The finite slit width may also contribute to the overprediction of flux near the line center. The material excluded by the narrow slit should be mostly at large radii in the disk where the Keplerian broadening is less, meaning this emission should appear near the line center. Indeed in Figure 13 we see that with or without a dust cavity, removing this emission makes the profiles more flat topped. It therefore also increases the FWHM of the line as a result of lowering the peak flux and making the line less centrally concentrated.

Note that in Figures 12 and 13 we also show the FWHM and centroid shift for profiles for models with b = 1.0 as the square points. These have a shallower density profile and consequently relatively more material (and attenuation of X-rays) at larger radii and less at smaller radii. This results in less Keplerian broadening of the line and thus a smaller FWHM, increasing the tension between our models and the data. It is for this reason that we did not further explore such models in this work.

Finally—although the focus of this work is on the mid-IR emission from Ne and Ar—in Figure 14 we also check the consequences of our models for the [O i] 6300 Å line. ¹¹ We compare them to the R = 45,000 profile analyzed by Pascucci et al. (2020). While the models without a dust cavity in this case overpredict the blueshift, the presence of a cavity makes them consistent with the very low observed blueshift of the [O i] line (as argued for TW Hya by Pascucci et al. 2011). Moreover, with or without a cavity, since in all cases the emission is constrained to the hottest inner parts of the wind, there is an even stronger dependence of the FHWM on r_in. The full line profiles show that our model actually does a surprisingly good job of reproducing the observed flat-topped profile for radii ≲0.3 r_G . The model with the smallest r_in = 0.03 r_G and a dust cavity does the best job, almost exactly reproducing the line profile. r_in = 0.1 r_G does a similarly good job of matching the shape and width of the central parts of the line, though it misses flux in the line wings. The data strongly prefer b = 1.5 over b = 1.0. Thus, the broad [O i] emission also supports the scenario of a small r_in in the disk wind from T Cha. We reiterate that T Cha is not the typical disk and that, like other transition disks with [Ne ii] LVCs, it lacks a [O i] HVC, and the [O i] LVC can be fit by a single component, rather than necessitating separate broad and narrow contributions with potentially separate origins.

Zoom In Zoom Out Reset image size

First, we restate the conclusions of our models. The low ratio of the line luminosities of double-ionized species to those of singly ionized species excludes low-density winds such as might result from EUV photoevaporation. The bright [Ne ii] and [Ar ii] lines require a wind of reasonably high density/mass-loss rate ≳10⁻⁸ M_☉ yr⁻¹ which is photoionized by a sufficiently large X-ray luminosity ∼3.7 × 10³¹ erg s⁻¹. Finally, in order to achieve L_{[Ne II]}/L_{[Ar II]} moderately less than unity and, crucially, more compact [Ar ii] emission than [Ne ii], then assuming a power-law wind profile with a sharp cutoff at an inner radius r_in, we require a small enough inner radius r_in ≲ 0.1 r_G such that photons with energies ∼250 eV are screened from reaching the outer reaches of the wind by its inner parts.

Note that this large L_X is just within the range of values quoted in the literature (Sacco et al. 2014). Additionally, we note that the [Ne ii] emission observed with JWST is around 55% brighter than the Spitzer value (Bajaj et al. 2024), which may indicate variability in the X-ray flux reaching the disk, either because the X-ray luminosity has itself increased or because the shadowing of the outer disk by an inner "warp" (C. Xie et al. 2024, in preparation) has reduced. ¹²

Such conditions are probably achievable within the framework of photoevaporation. Models for X-ray or FUV photoevaporation can achieve mass-loss rates ≳10⁻⁸ M_☉ yr⁻¹ (e.g., Owen et al. 2012; Nakatani et al. 2018a, 2018b; Picogna et al. 2021). Moreover, although the simplest energetic arguments would suggest mass is lost from r ≳ r_G , hydrodynamic simulations demonstrate that significant mass loss extends inward to r = 0.1–0.2 r_G (e.g., Liffman 2003; Font et al. 2004; Dullemond et al. 2007; Alexander et al. 2014), exactly as we prefer here. The FUV photoevaporation simulations of Komaki et al. (2021), while having a local peak around the typical cutoff at ∼0.2–0.3 r_G , even suggest mass loss in as far as 0.05 au. Finally, Sellek et al. (2022) argued that assuming the cooling is dominated by atomic emission lines at typical luminosities, the X-rays that could most effectively drive a wind were ∼500 eV (though this value may shift to higher energies at higher luminosities) and these should achieve τ ∼ 1. Winds resulting from X-ray photoevaporation should hence indeed, be optically thick to the ∼250 eV photons that ionize Ar, but potentially not to the ∼870 eV photons that ionize Ne.

However, attributing the wind to photoevaporation is not without caveats. First, such high mass-loss rates, as we infer, are not universal to photoevaporation simulations with other treatments finding lower values (Komaki et al. 2021, A. D. Sellek et al. 2024, in preparation), albeit at X-ray luminosities somewhat below that used in our best-fitting hiLX_TCha_sUV spectrum (which might be expected to drive a higher mass-loss rate). This is in agreement with studies of disk population synthesis and evolution on secular timescales, where many authors have argued that the higher photoevaporation rates cannot be sustained across the whole population (Sellek et al. 2020; Somigliana et al. 2020; Appelgren et al. 2023; Emsenhuber et al. 2023) in order to explain the lifetimes of disks and the observation of disks with large amounts of (dust) mass depletion. The most statistical constraint was calculated by Alexander et al. (2023), who showed that the observed distribution of accretion rates is incompatible with a simulated population if the photoevaporation rate exceeds ∼10⁻⁹ M_☉ yr⁻¹. This arises since once the photoevaporation rate exceeds the accretion rate, photoevaporation is expected to quickly open a gas cavity around r_G (Clarke et al. 2001), leading to the rapid dispersal of the inner disk and the quenching of accretion.

Our inferred mass-loss rate ≳10⁻⁸ M_☉ yr⁻¹ for T Cha would be somewhat higher than its measured accretion rate ∼4 × 10⁻⁹ M_☉ yr⁻¹ and is thus subject to the above issue. While in principle this could be rescued if the photoevaporative wind is less extended than assumed here (which would lower our estimate of the mass-loss rate since it diverges to large radii), the required extent would be so small as to make it unlikely that we would detect an extension in the [Ne ii] emission. Therefore, it may be that we are observing the disk during the final stages of dispersal outlined above. Such a scenario would be supported by the changes in the SED, which suggest a significant reduction in the inner disk mass (C. Xie et al. 2024, in preparation), although there is no clear evidence for a gas cavity in the disk around T Cha (Wölfer et al. 2023).

Finally, although in photoevaporation models, some mass-loss continues as far as 0.1 r_G , it is not clear that the power-law profile of density assumed in the self-similar model also extends thus far: if the density gradient becomes shallower than r⁻¹ it will become hard to match the constraints on column density we infer from the observations. The fact that the Ne line ratios predicted by Ercolano & Owen (2010) are closest to those produced by our r_in = r_G models may suggest that our models with a smaller inner radius do somewhat overestimate how close to the star EUV is absorbed compared to photoevaporation simulations.

MHD winds may solve many of the above problems for the wider protoplanetary disk population: as a transition disk with only weakly blueshifted lines, T Cha is not representative of this overall population. The blueshift of the [O i] line is found to reduce with the accretion luminosity of the source (Banzatti et al. 2019); therefore, many disks with higher accretion rates have lines that imply wind velocities higher than can be achieved in photoevaporative winds. Moreover, the broad components of the lines in these disks can only be obtained by Keplerian broadening at ≲0.5 au (Simon et al. 2016; Banzatti et al. 2019), which is too close to the star to be produced in a photoevaporative wind. Likewise, higher accretion rate sources frequently show [Ne ii] HVCs representative of a jet (Pascucci et al. 2020). These line features are thus attributed to inner MHD winds/jets. MHD winds may thus be one way to explain the breadth of the [Ne ii] line, which we were not able to reproduce adequately in this work.

MHD winds also provide benefits as they can extract angular momentum from disks and drive accretion: they thus form an attractive alternative to viscous accretion (Manara et al. 2023), especially in the context of several developing lines of evidence for weak turbulence at large radii in protoplanetary disks (Rosotti 2023). Photoevaporation on the other hand does not produce accretion torques, so it is unclear if accretion can be explained within a purely photoevaporative context. Moreover, extended MHD winds can sustain total mass-loss rates somewhat higher than the accretion rate onto the star (e.g., Ferreira & Pelletier 1995), potentially helping to explain the inferred wind mass-loss rate being higher than the measured accretion rate (Cahill et al. 2019). They may also sustain rapid gas accretion through a cavity (e.g., Martel & Lesur 2022), allowing accretion to continue during disk dispersal. Global MHD simulations (e.g., Rodenkirch et al. 2020) generally suggest that magnetic fields boost the mass-loss rate over those obtained with photoevaporation alone, which may further explain the high mass-loss rates we find for T Cha.

Overall, while MHD winds are attractive from the population perspective, we can more or less adequately explain the observations of T Cha with a photoevaporation model, and it is not clear that MHD winds are needed to explain this disk (a transition disk with a large dust cavity potentially near the end of its lifetime). This is consistent with one suggested picture of MHD winds dominating for most of the disk lifetime before giving way to photoevaporation toward the end for the final disk dispersal (Kunitomo et al. 2020; Pascucci et al. 2020; Weder et al. 2023). Nevertheless, it would be useful for future work to more explicitly model MHD winds in a similar framework to that we use here in order to establish how the observational signatures, such as the relative extents of the [Ne ii] and [Ar ii] emission would differ from photoevaporation.

5.2.1. What Absorbs the Soft X-Rays and EUV?

Given the evolutionary and demographic implications of the high mass-loss rates inferred in our work, it is important to understand if similar conclusions would be drawn across the protoplanetary disk population or if T Cha is something of an outlier, perhaps due to its higher stellar mass (1.5 M_☉) compared to most T Tauri stars, or its status as a more-evolved disk. Our GO 2260 program has also observed V4046 Sgr, and programs GO 1676 (Espaillat et al. 2021) and GO 3983 (Thanathibodee et al. 2023) will constrain [Ne iii] to [Ne ii] ratios (particularly in lower accretors)—a good measure of whether the mass-loss rate is low enough for EUV to penetrate and ionize the wind. Such efforts should help establish whether other, more-evolved disks appear to have dense photoevaporative winds. In addition, since photoevaporation is known to be insufficient to explain the broader or more strongly blueshifted line profiles observed for many disks, and in order to test the evolutionary perspective outlined by Pascucci et al. (2020), it would also be informative to compare to a sample of younger, full disks to see if the [Ne ii] is more compact as would be expected if the hard X-rays are screened out by a more substantial inner wind.

A recent parallel advance is the use of the Multi Unit Spectroscopic Explorer (MUSE) instrument on the Very Large Telescope (VLT) to perform high-spatial-resolution spectral mapping of [O i] emission (Fang et al. 2023; Flores-Rivera et al. 2023). For example, for another transition disk that has a low-velocity [Ne ii] component—TW Hya—these efforts yielded the first conclusive detection of a blueshift (−0.8 km s⁻¹) in the [O i] (Fang et al. 2023). Since 80% of the emission originates within 1 au of the star, these observations were considered consistent with the magnetohydrodynamic models of Wang et al. (2019). However, they can also be fit with a photoevaporative wind (Rab et al. 2023), albeit with the emitting region of the [O i] line lying mostly in the bound, static atmosphere just inside of the wind (thus explaining its lack of a significant blueshift without the need for a dust cavity, the explanation proposed by Pascucci et al. 2011). [O i] emission was also described as predominantly originating in an almost hydrostatic atmosphere in the photoevaporative models by Nemer & Goodman (2024). This restricted emitting region is due to the higher excitation temperature of the [O i] line, which can only be produced in the hottest, innermost regions where the EUV penetrates (Ercolano & Owen 2016). This would suggest a picture where a photoevaporative wind extends in to ∼1 au much like our models suggest fits T Cha. Comparing the two complementary approaches to resolving line emission would be a fruitful avenue for future work, and MIRI-MRS observations of TW Hya are included within the GTO program MINDS (1282; Henning et al. 2017).