Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA using JWST Observations: Tracing Organic Refractories and Beyond
Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, K. Willacy, D. C. Lis, Y. Chen, P. D. Klaassen

TL;DR
This paper introduces INDRA, a new Python tool for analyzing JWST infrared spectra of young stellar objects, expanding ice inventories by identifying complex organic refractory features and improving spectral decomposition methods.
Contribution
The paper presents INDRA, a novel global spectral fitting algorithm that enhances ice composition analysis in JWST data, revealing organic refractory components previously unquantified.
Findings
Confirmed presence of simple ice species and COMs in NGC 1333 IRAS 2A
Expanded ice inventory with additional CO2 and NH4+ features
Identified organic refractory contributions up to 9.6% in the 5-8 micron range
Abstract
In the era of JWST, with its unprecedented sensitivity and spectral resolution, infrared spectral surveys have revealed a rich inventory of ices, including complex organic molecules (COMs), in young stellar objects (YSOs). However, robust methods to decompose and quantify these absorption features particularly across broad spectral ranges, are still under investigation. We present INDRA (Ice-fitting with NNLS-based Decomposition and Retrieval Algorithm), a fully Python-based tool that performs continuum and silicate removal, global ice fitting using Weighted Non-Negative Least Squares (NNLS), and estimates column densities and statistical significance. We apply INDRA to NGC 1333 IRAS 2A, a target from the JWST Observations of Young protoStars (JOYS+) program previously studied using local fitting. We derive optical depths via polynomial continuum subtraction and remove silicate…
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Taxonomy
TopicsAstronomical Observations and Instrumentation · Calibration and Measurement Techniques · Gamma-ray bursts and supernovae
