arXiv subjects

Shu Ishibashi

Publications and source records attributed to Shu Ishibashi.

3 recordsLinked to original sources

arXiv2026

A Hybrid Origin for the Multiple Ring-Gap Structures in the Large Protoplanetary Disk V1094 Sco: A Low-Mass Planet and Secular Gravitational Instability

High spatial resolution observations reveal that some protoplanetary disks host multiple ring-gap pairs at large stellocentric radii, yet their physical origin remains unsettled. We present a multi-wavelength analysis of the V1094~Sco disk using Atacama Large Millimeter/submillimeter Array Band~6 continuum and $^{12}$CO and $^{13}$CO $J=2-1$ emission, together with a Very Large Telescope/SPHERE near-infrared scattered light image. The continuum image shows four narrow dust ring-gap pairs extending to exceptionally large radii ($r \sim 380$ au), while the CO isotopologues trace a spatially extended gas disk ($r \sim 760$ au) in Keplerian rotation. From the dust ring widths, we place conservative upper limits on the turbulent viscosity parameter, $α\lesssim 10^{-3}$ and potentially $\lesssim 10^{-4}$, implying weak turbulence. The ensemble of gap widths and depths is inconsistent with a simple one-planet-per-gap interpretation. At $r \simeq 100$~au, a double gap and its scattered light counterpart are consistent with multi-gap excitation by a single low-mass companion of $(55 \pm 35)\,M_{\oplus}$. At $r \simeq 170$-$230$~au, the outer ring system shows regular spacing and no clear scattered light counterpart, indicating mechanisms that operate primarily at the disk midplane. These outer rings are quantitatively compatible with secular gravitational instability. V1094~Sco therefore supports a hybrid pathway in which weak turbulence in an extended disk allows secular gravitational instability to assemble long-lived midplane dust concentrations that can cradle planet formation beyond $\sim100$~au, alongside planet-driven substructures at intermediate radii.

astro-ph.EP↗

arXiv2026

ALMA 2D super-resolution imaging survey of Ophiuchus Class I/flat spectrum/II disks. II. Statistical analysis of stellar and disk properties

We present a statistical study of stellar and dust disk properties for young stellar objects in the Ophiuchus star-forming region. Building on our previous paper (Shoshi et al. 2025b), which applied two-dimensional super-resolution imaging with PRIISM to ALMA archival Band 6 continuum data and spatially resolved 78 disks, we analyze a sample of 67 systems with robust dust-radius measurements. We combine stellar parameters from the literature, including bolometric temperature $T_{\rm bol}$, stellar mass $M_\ast$, and mass accretion rate $\dot{M}_{\rm acc}$, with disk parameters derived from the super-resolution images, including inclination $i_{\rm disk}$, millimeter luminosity $L_{\rm mm}$, and dust radius $R_{95\%}$. We quantify pairwise correlations and compare their behavior across evolutionary stages (Class I/FS and Class II) and between disks with and without detectable substructures. We identify substructure dependencies in $L_{\rm mm}$ and $R_{95\%}$, indicating that substructures tend to be found preferentially in relatively massive and extended disks. Moreover, we find a tight size-luminosity relation between $R_{95\%}$ and $L_{\rm mm}$. In particular, only Class II disks with substructures exhibit a steeper scaling, $R_{95\%}\propto L_{\rm mm}^{0.8}$, while the other subsamples are broadly consistent with $R_{95\%}\propto L_{\rm mm}^{0.4\text{-}0.5}$. This behavior is qualitatively consistent with disk evolution models in which disks with planet-induced pressure bumps follow a steeper size-luminosity relation than smooth disks. Overall, our results suggest that disk substructures play an important role in shaping the evolution of dust and global disk properties, while providing empirical constraints on accretion, dust trapping, and possible gravitational instability in young disks.

astro-ph.EP↗

arXiv2026

Predicting dust temperature from molecular line data using machine learning

We conducted experiments with machine learning techniques to construct dust temperature maps from the CO isotopologue molecular line data in the Orion A molecular cloud. In the classical astrophysical methodology, multi-band continuum data are required to derive the dust temperature. The present study aims to investigate the capability and limitations of machine learning techniques to derive dust temperatures in regions without multi-band dust continuum data. We investigated how the number of pixels used for training influences prediction accuracy, and how the dust temperatures sampled in the training area influence prediction accuracy. We found that $\sim$5\% of the total number of pixels in the observational region is sufficient for training to obtain accurate predictions. Furthermore, a dust temperature sample within the training area should cover the whole temperature range and have a similar sample distribution to that of the entire observing region for an accurate prediction. The $^{12}$CO / $^{13}$CO ratio is often found to be the most important feature in predicting the dust temperature. As the $^{12}$CO / $^{13}$CO ratio is a tracer of PDR, the machine learning technique could connect the dust temperatures to the PDRs. We also found that the condition of thermal gas-dust coupling is not required for accurate prediction of the dust temperature from the molecular line data, and that machine learning is capable of capturing information more than classical astrophysical concepts.

astro-ph.GA↗