I currently work primarily in X-ray astrophysics. I am also starting to learn more about physics-informed machine learning.
I am interested in understanding the nature of multi-phase galactic outflows.
The CC85 model assumes energy and mass is injected from supernovae uniformly within a sphere. This drives a hot stable supersonic spherical galactic outflow. Throughout the years there have been many modifications by others. The observationally-motivated changes I have considered are:
- allow additional mass injection & non-spherical expansion outside the sphere (mnras 2021)
- assume energy and mass injection uniformly within a ring (apjL 2022)
- assume non-uniform energy and mass injection in a sphere (mnrasL 2023)
to better understand the interpretability of trained neural networks embedded in differential equations (neural partial differential equations) using the geophysical KdV equation as a case study (with Arvind Mohan)
applications of ML in dynamic astrophysical optimization problems
You can find my publications listed here on arXiv or sao/nasa ads.
Nguyen, D. D., Thompson, T. A., Schneider, E. E., Lopez, S., Lopez, L. A., Dynamics of hot galactic winds launched from spherically-stratified starburst cores, 2023, Monthly Notices of the Royal Astronomical Society Letters, 518, 1,
Nguyen, D. D., Thompson, T. A., Galactic winds and bubbles from nuclear starburst rings, 2022, The Astrophysical Journal Letters, 935, 2,
Nguyen, D. D., Thompson, T. A., Mass-Loading and Non-Spherical Divergence in Hot Galactic Winds: Implications for X-Ray Observations, 2021, Monthly Notices of the Royal Astronomical Society, 508, 4,
- Lopez, S., Lopez, L. A., Nguyen, D. D., Thompson, T. A., Mathur, S., Bolatto, A. D., Vulic, N., Sardone, A., X-ray Properties of NGC 253’s Starburst-Driven Outflow, 2022, submitted (accepted ApJ),
- Lopez, L. A., Mathur, S., Nguyen, D. D., Thompson, T. A., Olivier, G. M., Temperature and Metallicity Gradients in the Hot Outflows of M82, 2020, The Astrophysical Journal, 904, 2,