mlsanityData to 14 Oct 2026

Disk2Planet: A Robust and Automated Machine Learning Tool for Parameter Inference in Disk-Planet Systems

arXiv 2409.17228 ↗First posted 25 Sep 2024astro-ph.EP cs.AI cs.LGcited by 3

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Abstract (arXiv)

We introduce Disk2Planet, a machine learning-based tool to infer key parameters in disk-planet systems from observed protoplanetary disk structures. Disk2Planet takes as input the disk structures in the form of two-dimensional density and velocity maps, and outputs disk and planet properties, that is, the Shakura--Sunyaev viscosity, the disk aspect ratio, the planet--star mass ratio, and the planet's radius and azimuth. We integrate the Covariance Matrix Adaptation Evolution Strategy (CMA--ES), an evolutionary algorithm tailored for complex optimization problems, and the Protoplanetary Disk Operator Network (PPDONet), a neural network designed to predict solutions of disk--planet interactions. Our tool is fully automated and can retrieve parameters in one system in three minutes on an Nvidia A100 graphics processing unit. We empirically demonstrate that our tool achieves percent-level or higher accuracy, and is able to handle missing data and unknown levels of noise.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 50 references that are in the map. First posted on arXiv 25 Sep 2024.

Builds on

6 of 50 references.

References · 6

  1. 2023PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systemscited by 19
  2. 2021DPNNet-2.0 Part I: Finding hidden planets from simulated images of protoplanetary disk gapscited by 7
  3. 2021PGNets: Planet mass prediction using convolutional neural networks for radio continuum observations of protoplanetary diskscited by 7
  4. 2022Using Bayesian Deep Learning to infer Planet Mass from Gaps in Protoplanetary Diskscited by 4
  5. 2022Locating Hidden Exoplanets in ALMA Data Using Machine Learningcited by 3
  6. 2024DBNets: A publicly available deep learning tool to measure the masses of young planets in dusty protoplanetary discscited by 2

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Cited by year

Citing papers per year: 2024: 1; 2025: 2.

3 papers.

  1. 2025Active operator learning with predictive uncertainty quantification for partial differential equationscited by 12
  2. 2024DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuningcited by 11
  3. 2025RED-DiffEq: Regularization by denoising diffusion models for solving inverse PDE problems with application to full waveform inversioncited by 5