Protoplanetary disk cavities with JWST-MIRI: a dichotomy in molecular emission

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Authors: Klaus Pontoppidan
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Abstract

The evolution of planet-forming regions in protoplanetary disks is of fundamental importance to understanding planet formation. Disks with a central deficit in dust emission, a “cavity”, have long attracted interest as potential evidence for advanced disk clearing by protoplanets and/or winds. Before JWST, infrared spectra showed that these disks typically lack the strong molecular emission observed in full disks. In this work, we combine a sample of 12 disks with millimeter cavities of a range of sizes (∼ 2–70 au) and different levels of millimeter and infrared continuum deficits. We analyze their molecular spectra as observed with MIRI on JWST, homogeneously reduced with the new JDISCS pipeline. This analysis demonstrates a stark dichotomy in molecular emission where “molecule-rich” (MR) cavities follow global trends between water, CO, and OH luminosity and accretion luminosity as in full disks, while “molecule-poor” (MP) cavities are significantly sub-luminous in all molecules except sometimes OH. Disk cavities generally show sub-luminous organic emission, higher OH/H2O ratios, and suggest a lower water column density. The sub-thermal excitation of CO and water vibrational lines suggests a decreased gas density in the emitting layer in all cavities, supporting model expectations for C2H2 photodissociation. We discover a bifurcation in infrared index (lower in MR cavities) suggesting that the molecular dichotomy is linked to residual μm-size dust within millimeter disk cavities. Put together, these results suggest a feedback process between dust depletion, gas density decrease, and molecule dissociation. Disk cavities may have a common evolutionary sequence where MR switch into MP over time.

Fields of Study & Subjects

Astrophysics and Star Formation Studies Astro and Planetary Science Stellar planetary and galactic studies

Publication details

Journal / source
JPL Data
Publication date
1 January 2026
Document type
Dataset