Gibbs Point Process Model for Young Star Clusters in M33

by   Dayi Li, et al.

We demonstrate the power of Gibbs point process models from the spatial statistics literature when applied to studies of resolved galaxies. We conduct a rigorous analysis of the spatial distributions of objects in the star formation complexes of M33, including giant molecular clouds (GMCs) and young stellar cluster candidates (YSCCs). We choose a hierarchical model structure from GMCs to YSCCs based on the natural formation hierarchy between them. This approach circumvents the limitations of the empirical two-point correlation function analysis by naturally accounting for the inhomogeneity present in the distribution of YSCCs. We also investigate the effects of GMCs' properties on their spatial distributions. We confirm that the distribution of GMCs and YSCCs are highly correlated. We found that the spatial distributions of YSCCs reaches a peak of clustering pattern at  250 pc scale compared to a Poisson process. This clustering mainly occurs in regions where the galactocentric distance > 4.5 kpc. Furthermore, the galactocentric distance of GMCs and their mass have strong positive effects on the correlation strength between GMCs and YSCCs. We outline some possible implications of these findings for our understanding of the cluster formation process.


page 9

page 21


Predicting star formation properties of galaxies using deep learning

Understanding the star-formation properties of galaxies as a function of...

Decoding the age-chemical structure of the Milky Way disk: An application of Copulas and Elicitable Maps

In the Milky Way, the distribution of stars in the [α/Fe] vs. [Fe/H] and...

A case study of hurdle and generalized additive models in astronomy: the escape of ionizing radiation

The dark ages of the Universe end with the formation of the first genera...

Predicting the Radiation Field of Molecular Clouds using Denoising Diffusion Probabilistic Models

Accurately quantifying the impact of radiation feedback in star formatio...

Plasticity as a link between spatially explicit, distance-independent, and whole-stand forest growth models

Models at various levels of resolution are commonly used, both for fores...

Multilayer Adjusted Cluster Point Process Model: Application to Microbial Biofilm Image Data Analysis

A common problem in spatial statistics tackles spatial distributions of ...

Study of star clusters in the M83 galaxy with a convolutional neural network

We present a study of evolutionary and structural parameters of star clu...

Please sign up or login with your details

Forgot password? Click here to reset