2024
DOI: 10.1051/0004-6361/202348239
|View full text |Cite
|
Sign up to set email alerts
|

Galaxy merger challenge: A comparison study between machine learning-based detection methods

B. Margalef-Bentabol,
L. Wang,
A. La Marca
et al.

Abstract: Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. Our aim is to benchmark the relative performance of merger detection methods based on machine learning (ML). We explore six leading ML methods using three main datasets. The first dataset consists of mock observations from the IllustrisTNG simulations, which acts as the training data and allows us to quantify the performance metrics of the detection methods. The second dataset… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
references
References 130 publications
0
0
0
Order By: Relevance