Theoretical and Natural Science
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Theoretical and Natural Science
Vol. 13, 30 November 2023
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Deciphering dark matter: A computational analysis of stellar velocity distributions
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Abstract
This study examines the dark matter density in the Galaxy by fitting recent data on stellar rotational velocities. We employ a model including the disk, the bulge, and the dark matter halo. The disk’s density is parameterized using a modified Bessel function, and the bulge is modeled using both the De Vaucouleurs and Exponential Sphere functions to better fit large and small radii respectively. The dark halo is modeled using the generalized Navarro-Frenk-White profile, with slope parameters for standard NFW and Moore profiles, and an Isothermal profile for comparison. The fit of the model parameters is established using local Dark Matter density and total Dark Matter mass as boundary conditions, with circular velocities derived via a Newtonian approach. The least chi-square (χ 2 ) method is used for rotation curve fitting. Results demonstrate successful fitting of rotational velocity data and significant influence of the DH at large radial distances from the Galactic center.
Keywords
Dark Matter, Dark Halo, Rotation Curve Fitting, Milky Way
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-189-6
- ISBN (Online)
- 978-1-83558-190-2
- Published Date
- 30 November 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/13/20240717
- Copyright
- © 2023 The Author(s)
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited