This model demonstrates photoevaporation's role in producing wind features in protoplanetary disks, indicating vital implications for planet formation.
Understanding the dispersal of protoplanetary disks remains a central challenge in planet formation theory. Disk winds driven by magnetohydrodynamics (MHD) and/or photoevaporation are now recognized as primary agents of dispersal. With the advent of the James Webb Space Telescope (JWST), spatially resolved imaging of these winds, particularly in pure rotational lines, have become possible, revealing X-shaped morphologies and integrated fluxes of ∼ 10^ H2 -16 --10^ -15 -2 . However, the lack of theoretical models suitable for direct comparison has limited the interpretation of these features. To address this, we present the first model of photoevaporative winds tailored for direct comparison with JWST observations. H2 Using radiation hydrodynamics simulations coupled with chemistry, we derived steady-state wind structures and post-processed them to compute -level populations and line radiative transfer, including collisional excitation and spontaneous decay. H2 Our synthetic images reproduce the observed X-shaped morphology with radial extents of ≳ 50--300 and SY Cha. While the predicted line fluxes are somewhat lower than the observed values, they remain broadly consistent for lower J transitions despite the model not being specifically tailored to these sources. and semi-opening angles of ∼ 37^̧irc--50^̧irc, matching observations of These results suggest that photoevaporation is a viable mechanism for reproducing key features of observed winds, including morphology and fluxes, though conclusive identification of the wind origin requires source-specific modeling. This conclusion challenges the reliance on geometrical structures alone to distinguish between MHD winds and photoevaporation. Based on our findings, we also discuss alternative diagnostics of photoevaporative winds. This work provides a critical first step toward interpreting spatially resolved winds and motivates future modeling efforts.
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Nakatani et al. (2026) studied this question.
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