J/A+A/698/A297 IC 1396 members HSC and UKIDSS photometry (Das+, 2025)
Subaru Hyper-Supreme Cam observations of IC 1396:
Source catalogue, member population, and sub-clusters of the complex.
Das S.R., Gupta S., Jose J., Samal M., Herczeg G.J., Guo Z., More S.,
Prakash P.
<Astron. Astrophys. 698, A297 (2025)>
=2025A&A...698A.297D 2025A&A...698A.297D (SIMBAD/NED BibCode)
ADC_Keywords: Clusters, open ; Photometry, infrared
Keywords: methods: statistical - stars: pre-main sequence -
Abstract:
Identifying members of star-forming regions is an initial step to
analyse the properties of a molecular cloud complex. In such a
membership analysis, the sensitivity of a dataset plays a significant
role in detecting stellar mass up to a specific limit, which is
crucial for understanding various stellar properties, such as disc
evolution and planet formation across different environments.
IC 1396 is a nearby classical HII region dominated by feedback-driven
star formation activity. In this work, we aim to identify the low-mass
member populations of the complex using deep optical multi-band
imaging with Subaru-Hyper Suprime Cam (HSC) over ∼7.1deg2 in r2 ,
i2 , and Y bands. The optical dataset is complemented by UKIDSS
near-infrared data in the J, H, and K bands. Through this work, we
evaluate the strengths and limitations of machine learning techniques
when applied to such astronomical datasets.
To identify member populations of IC 1396, we employed the random
forest (RF) classifier of machine learning technique. The RF
classifier is an ensemble of individual decision trees suitable for
large, high-dimensional datasets. The training set used in this work
is derived from previous Gaia-based studies, in which the member stars
are younger than ∼10Myr. However, its sensitivity is limited to
∼20mag in the r2 band, making it challenging to identify
candidates at the fainter end. In this analysis, in addition to
magnitudes and colours, we incorporated several derived parameters
from the magnitude and colour of the sources to identify candidate
members of the star-forming complex. By employing this method, we were
able to identify promising candidate member populations of the
star-forming complex. We discuss the associated limitations and
caveats in the method and improvements for future studies.
In this analysis, we identify 2425 high-probability low-mass stars
distributed within the entire star-forming complex, of which 1331 are
new detections. A comparison of these identified member populations
shows a high retrieval rate with Gaia-based literature sources, as
well as sources detected through methods based on optical
spectroscopy, Spitzer, Hα/X-ray emissions, optical photometry,
and 2MASS photometry. The mean age of the member populations is
∼2-4Myr, consistent with findings from previous studies. Considering
the identified member populations, we present preliminary results by
exploring the presence of sub-clusters within IC 1396, assessing the
possible mass limit of the member populations, and providing a brief
discussion on the star formation history of the complex.
The primary aim of this work is to develop a method of identifying
candidate member populations from a deep, sensitive dataset such as
Subaru-HSC by employing machine learning techniques. Although we
overcome some limitations in this study, the method requires further
improvements to address the caveats associated with such a membership
analysis.
Description:
This work presents the deepest photometric observations of the
star-forming complex IC 1396 with the Subaru-HSC. By combining the
optical and NIR data from Pan-STARRS and UKIDSS catalogues with the
HSC catalogue, we conduct a comprehensive membership analysis of
this star-forming complex.
The table provides the positions, magnitude values, and their errors
in HSC and UKIDSS bands along with PRF values of 2425 stars identified
with the RF classifier in this work.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table2.dat 126 2425 Details of the candidate members identified in
this work using the RF method
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Byte-by-byte Description of file: table2.dat
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Bytes Format Units Label Explanations
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1- 4 I4 --- No Serial number of the stars
5 A1 --- n_No [*] * for new detections in this work
7- 14 F8.4 deg RAdeg Right Ascension J2000
16- 23 F8.4 deg DEdeg Declination J2000
26- 31 F6.3 mag r2mag Magnitude in HSC-r2 band
34- 39 F6.4 mag e_r2mag Magnitude error in HSC-r2 band
42- 47 F6.3 mag i2mag Magnitude in HSC-i2 band
50- 55 F6.4 mag e_i2mag Magnitude error in HSC-i2 band
58- 63 F6.3 mag Ymag Magnitude in HSC-Y band
66- 71 F6.4 mag e_Ymag Magnitude error in HSC-Y band
74- 79 F6.3 mag Jmag Magnitude in UKIDSS-J band
82- 87 F6.4 mag e_Jmag Magnitude error in UKIDSS-J band
90- 95 F6.3 mag Hmag Magnitude in UKIDSS-H band
98-103 F6.4 mag e_Hmag Magnitude error in UKIDSS-H band
106-111 F6.3 mag Kmag Magnitude in UKIDSS-K band
114-119 F6.4 mag e_Kmag Magnitude error in UKIDSS-K band
122-126 F5.3 mag PRF [0.8/1] RF membership probability
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Acknowledgements:
Swagat Das, dasswagat77(at)gmail.com
(End) Patricia Vannier [CDS] 04-Jun-2025