Extraction of Physical Parameters of RRab Variables Using Neural Network Based Interpolator Article Swipe
Nitesh Kumar
,
Harinder P. Singh
,
O. Yu. Malkov
,
Santosh Joshi
,
Kefeng Tan
,
P. Prugniel
,
Anupam Bhardwaj
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/universe11070207
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/universe11070207
Determining the physical parameters of pulsating variable stars such as RR Lyrae is essential for understanding their internal structure, pulsation mechanisms, and evolutionary state. In this study, we present a machine learning framework that uses feedforward artificial neural networks (ANNs) to infer stellar parameters—mass (M), luminosity (log(L/L⊙)), effective temperature (log(Teff)), and metallicity (Z)—directly from Transiting Exoplanet Survey Satellite (TESS) light curves. The network is trained on a synthetic grid of RRab light curves generated from hydrodynamical pulsation models spanning a broad range of physical parameters. We validate the model using synthetic self-inversion tests and demonstrate that the ANN accurately recovers the input parameters with minimal bias. We then apply the trained model to RRab stars observed by the TESS. The observed light curves are phase-folded, corrected for extinction, and passed through the ANN to derive physical parameters. Based on these results, we construct an empirical period–luminosity–metallicity (PLZ) relation: log(L/L⊙) = (1.458 ± 0.028) log(P/days) + (–0.068 ± 0.007) [Fe/H] + (2.040 ± 0.007). This work shows that ANN-based light-curve inversion offers an alternative method for extracting stellar parameters from single-band photometry. The approach can be extended to other classes of pulsators such as Cepheids and Miras.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/universe11070207
- https://www.mdpi.com/2218-1997/11/7/207/pdf?version=1750763189
- OA Status
- gold
- References
- 75
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411607065
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https://doi.org/10.3390/universe11070207Digital Object Identifier
- Title
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Extraction of Physical Parameters of RRab Variables Using Neural Network Based InterpolatorWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-06-24Full publication date if available
- Authors
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Nitesh Kumar, Harinder P. Singh, O. Yu. Malkov, Santosh Joshi, Kefeng Tan, P. Prugniel, Anupam BhardwajList of authors in order
- Landing page
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https://doi.org/10.3390/universe11070207Publisher landing page
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https://www.mdpi.com/2218-1997/11/7/207/pdf?version=1750763189Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2218-1997/11/7/207/pdf?version=1750763189Direct OA link when available
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Physics, Artificial neural network, Extraction (chemistry), Artificial intelligence, Computer science, Chromatography, ChemistryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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