2026 Project Description

Go back to the list of available projects

Observing the Signatures of Ambipolar Diffusion: Investigating Neutral versus Ion Line Widths in Molecular Cloud Dense Cores

Keywords:

Radio Astronomy

Single-Dish Telescope

Star Formation

Supervisors

Sheng-Jun Lin, Hsi-Wei Yen, Indrani Das
Find out more about supervisors on ASIAA website

Task Description and Goals

What are the physical mechanisms regulating the collapse of dense cores? In the early stages of star formation, magnetic fields can provide critical support against gravity, maintaining dense cores in a quasi-static equilibrium state under flux-freezing conditions. However, given the low-ionization fraction in molecular clouds, the magnetic field is not perfectly coupled to the cores. Through a process known as ambipolar diffusion, neutral particles could decouple from the magnetic fields. This allows gravity to initiate the collapse to form protostars.

To investigate this fundamental transition, this project utilizes radio observational surveys of nearby star-forming regions. Our study focuses on identifying the kinematic signatures that arise when neutrals drift through ions within dense cores, specifically those in the starless/prestellar stages that have not yet formed a central protostar. The recent data releases from the Green Bank Ammonia Survey (GAS) for NH3 (neutrals) and N2H+ mapping data (ions) from the Nobeyama 45-m telescope provide an ideal multi-tracer sample to search for these signatures.

In this project, students will work with these radio datasets to measure and compare the velocity dispersions (line widths) of ions and neutrals within a sample of starless cores. They will learn the fundamentals of radio astronomy and develop essential skills in spectral line fitting, kinematic data analysis, and source extraction methods. This project provides a practical introduction to radio data analysis and is well-suited for undergraduate students interested in the fields of star formation and observational astronomy.

Required Background

Basic knowledge of Physics and Astronomy. Experience in Linux/Unix systems and programming using Python is desirable.