Chrome Extension
WeChat Mini Program
Use on ChatGLM

The Dust Polarisation and Magnetic Field Structure in the Centre of NGC253 with ALMA

Davide Belfiori,Rosita Paladino,Annie Hughes,Jean-Philippe Bernard, Dana Alina, Ivana Bešlić,Enrique Lopez Rodriguez, Mark D. Gorski, Serena A. Cronin,Alberto D. Bolatto

arXiv · Astrophysics of Galaxies(2025)

Cited 0|Views0
Abstract
Magnetic fields have an impact on galaxy evolution at multiple scales. They are particularly important for starburst galaxies, where they play a crucial role in shaping the interstellar medium (ISM), influencing star formation processes and interacting with galactic outflows. The primary aim of this study is to obtain a parsec scale map of dust polarisation and B-field structure within the central starburst region of NGC253. This includes examining the relationship between the morphology of B-fields, galactic outflows and the spatial distribution of super star clusters (SSC), to understand their combined effects on the galaxy's star formation and ISM. We used ALMA full polarisation data in Bands 4 (145 GHz) and 7 (345 GHz) with resolution of 25 and 5 pc scale, respectively. According to our SED fitting analysis, the observed Band 4 emission is a combination of dust, synchrotron and free-free, while Band 7 traces only dust. The polarisation fraction (PF) of the synchrotron component is 2 in both bands at common resolution show that the same B-fields structure is traced by dust and synchrotron emission at scales of 25 pc. The B-field morphology suggests a coupling with the multiphase outflow, while the distribution of PF in Band 7 showed to be correlated with the presence of SSC. We observed a significant anti-correlation between polarisation fraction and column density in both Bands 4 and 7. A negative correlation between PF and dispersion angle function was observed in Band 4 but was nearly absent in Band 7 at native resolution, suggesting that the tangling of B-field geometry along the plane of the sky is the main cause of depolarisation at 25 pc scales, while other factors play a role at 5 pc scales.
More
Translated text
PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest