Protoplanetary Disk

Protoplanetary disks are rotating disks of gas and dust surrounding young stars, where planets form. Current research heavily utilizes machine learning, particularly deep convolutional neural networks and Bayesian methods, to analyze observational data (e.g., spectral energy distributions, molecular line emission, and radio continuum images) and infer disk properties, including planet masses and locations. This work aims to overcome the computational challenges and inherent degeneracies in traditional methods, enabling faster and more robust characterization of planet formation environments. The resulting improved understanding of planet formation processes has significant implications for exoplanet research and our broader knowledge of planetary system architectures.

Papers

September 25, 2024

Disk2Planet: A Robust and Automated Machine Learning Tool for Parameter Inference in Disk-Planet Systems
Shunyuan Mao, Ruobing Dong, Kwang Moo Yi, Lu Lu, Sifan Wang, Paris Perdikaris
Parameter Inference Disc LawLLM Protoplanetary Disk

June 16, 2024

Advancing Solar Flare Prediction using Deep Learning with Active Region Patches
Chetraj Pandey, Temitope Adeyeha, Jinsu Hong, Rafal A. Angryk, Berkay Aydin
Deep Learning Solar Flare Protoplanetary Disk Active Region Flare Forecasting

February 19, 2024

DBNets: A publicly available deep learning tool to measure the masses of young planets in dusty protoplanetary discs
Alessandro Ruzza, Giuseppe Lodato, Giovanni Pietro Rosotti
BRIO Tool Protoplanetary Disk Network Metric Stationary Mass

December 8, 2023

Disentangling CO Chemistry in a Protoplanetary Disk Using Explanatory Machine Learning Techniques
Amina Diop, Ilse Cleeves, Dana Anderson, Jamila Pegues, Adele Plunkett
Machine Learning Protoplanetary Disk Abundance Estimation Cosmic Ray Co Pyrolysis

November 29, 2023

Bayesian Imaging for Radio Interferometry with Score-Based Priors
Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Pablo Lemos, Anna M. M. Scaife, Yashar Hezaveh, Laurence Perreault-Levasseur
Score Based Radio Astronomy Protoplanetary Disk Bayesian Imaging Inverse Imaging Radio Interferometric

October 11, 2023

Orbital Polarimetric Tomography of a Flare Near the Sagittarius A* Supermassive Black Hole
Aviad Levis, Andrew A. Chael, Katherine L. Bouman, Maciek Wielgus, Pratul P. Srinivasan
Solar Flare Protoplanetary Disk Spectro Polarimetric FLAIR Embeddings Black Hole

May 18, 2023

PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systems
Shunyuan Mao, Ruobing Dong, Lu Lu, Kwang Moo Yi, Sifan Wang, Paris Perdikaris
Deep Operator Network Protoplanetary Disk Prediction Speed Steady State

March 24, 2023

Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes
Ryan-Rhys Griffiths
Financial Application Gaussian Process Known Molecule High Energy Physic Experimental Data Protoplanetary Disk Black Hole Latent Theme

February 9, 2023

Analysing the SEDs of protoplanetary disks with machine learning
T. Kaeufer, P. Woitke, M. Min, I. Kamp, C. Pinte
Machine Learning Radiative Transfer Spectral Energy Distribution Protoplanetary Disk

January 12, 2023

Kinematic Evidence of an Embedded Protoplanet in HD 142666 Identified by Machine Learning
J. P. Terry, C. Hall, S. Abreau, S. Gleyzer
Machine Learning Orbital Motion Protoplanetary Disk Kinematic Data

November 17, 2022

Locating Hidden Exoplanets in ALMA Data Using Machine Learning
Jason Terry, Cassandra Hall, Sean Abreau, Sergei Gleyzer
Machine Learning Computer Vision Large Scale Learning Exoplanet Detection Protoplanetary Disk

November 8, 2022

A Neural Network Subgrid Model of the Early Stages of Planet Formation
Thomas Pfeil, Miles Cranmer, Shirley Ho, Philip J. Armitage, Tilman Birnstiel, Hubert Klahr
Numerical Simulation Subgrid Scale Protoplanetary Disk Early Stage Dust Removal Planet Formation

September 27, 2022

Machine learning-accelerated chemistry modeling of protoplanetary disks
Grigorii V. Smirnov-Pinchukov, Tamara Molyarova, Dmitry A. Semenov, Vitaly V. Akimkin, Sierk van Terwisga, Riccardo Francheschi, Thomas Henning
New Machine Chemical Space Protoplanetary Disk

February 23, 2022

Using Bayesian Deep Learning to infer Planet Mass from Gaps in Protoplanetary Disks
Sayantan Auddy, Ramit Dey, Min-Kai Lin, Daniel Carrera, Jacob B. Simon
Filling Gap Bayesian Deep Learning Protoplanetary Disk Bayesian Deep

November 30, 2021

PGNets: Planet mass prediction using convolutional neural networks for radio continuum observations of protoplanetary disks
Shangjia Zhang, Zhaohuan Zhu, Mingon Kang
Convolutional Neural Network Evolving Observation Protoplanetary Disk

Protoplanetary Disk

Papers

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

Advancing Solar Flare Prediction using Deep Learning with Active Region Patches

DBNets: A publicly available deep learning tool to measure the masses of young planets in dusty protoplanetary discs

Disentangling CO Chemistry in a Protoplanetary Disk Using Explanatory Machine Learning Techniques

Bayesian Imaging for Radio Interferometry with Score-Based Priors

Orbital Polarimetric Tomography of a Flare Near the Sagittarius A* Supermassive Black Hole

PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systems

Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holes

Analysing the SEDs of protoplanetary disks with machine learning

Kinematic Evidence of an Embedded Protoplanet in HD 142666 Identified by Machine Learning

Locating Hidden Exoplanets in ALMA Data Using Machine Learning

A Neural Network Subgrid Model of the Early Stages of Planet Formation

Machine learning-accelerated chemistry modeling of protoplanetary disks

Using Bayesian Deep Learning to infer Planet Mass from Gaps in Protoplanetary Disks

PGNets: Planet mass prediction using convolutional neural networks for radio continuum observations of protoplanetary disks