| Name: | Rittik Bhattacharjee |
| Affiliation: | Tezpur University |
| Conference ID: | ASI2025_374 |
| Title: | Integrated Modeling of Diffuse FUV and Dust Processed IR Emissions in the 30 Doradus Star Forming Region |
| Authors: | Rittik Ram Bhattacharjee 1, Gautam Saikia 2, Olag Pratim Bordoloi 1,4, P. Shalima 3, Rupjyoti Gogoi 1 |
| Authors Affiliation: | 1 Tezpur University, Tezpur - 784028, India
2 North Gauhati College, Assam - 781031, India
3 Manipal Centre for Natural Sciences Manipal Academy of Higher Education Manipal, Manipal - 576104, India
4 Cotton University, Guwahati - 781001, India |
| Mode of Presentation: | Poster |
| Abstract Category: | Stars, Interstellar Medium, and Astrochemistry in Milky Way |
| Abstract: | The extinction of starlight in molecular clouds is crucial for understanding dust evolution within the interstellar medium (ISM). Far-ultraviolet (FUV) emissions provide insights into how starlight scatters off interstellar dust grains, while infrared (IR) emissions reveal details about dust composition and distribution. These observations are particularly valuable in HII regions experiencing starburst activity, as they help trace star formation processes and feedback mechanisms within these dense, active areas of the ISM. This study focuses on modeling the diffuse, dust-scattered FUV emissions surrounding the R136 star cluster, located at the heart of the 30 Doradus HII region—one of the most active star-forming regions in the Local Group, situated within the Large Magellanic Cloud (LMC). Using the SKIRT radiative transfer code, which employs a Monte Carlo algorithm, we simulate FUV emissions and compare them with observational data from the Far Ultraviolet Spectroscopic Explorer (FUSE). Our model incorporates a 3D distribution of 305 stars within a 70 parsec radius, identified through the VLT Flames Tarantula Survey (VFTS) and the Hubble Tarantula Treasury Project (HTTP). To represent the stellar population, we employ the Starburst99 (SB99) model, which includes the Kroupa mass function. Our findings suggest that accurately positioning radiation sources significantly improves the precision of FUV and IR simulations. Additionally, initial results indicate that varying the mass concentration within clumps in the model affects the UV emission, with a higher concentration resulting in more intense UV emission . We also observe that dust grain size distribution, modeled through SKIRT’s ability to categorize silicate, graphite, and PAH particles by size, strongly impacts IR emissions. |
