[Loops] New paper: Understanding Heating in Active Region Cores through Machine Learning. I. Numerical Modeling and Predicted Observables

[Will Barnes]

Dear loops enthusiasts,

We’re happy to announce that our new paper on modeling time lag and EM slope signatures of impulsively heated loops was recently published in ApJ. This work was presented during my talk at the most recent Loops workshop. The links to the ApJ and arXiv papers are included below. A link to the GitHub repository for this project is also included.

A follow up paper looking at quantitative comparisons between observations and models is in the works. Stay tuned!

Best,

Will

Dr. Will Barnes
Postdoctoral Research Scientist
Lockheed Martin Solar and Astrophysics Laboratory
barnes at lmsal.com

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Title:  Understanding Heating in Active Region Cores through Machine Learning. I. Numerical Modeling and Predicted Observables

Authors: W. T. Barnes, S. J. Bradshaw, and N. M. Viall

ApJ: https://iopscience.iop.org/article/10.3847/1538-4357/ab290c <https://iopscience.iop.org/article/10.3847/1538-4357/ab290c>

arXiv: https://arxiv.org/abs/1906.03350 <https://arxiv.org/abs/1906.03350>

GitHub: https://github.com/rice-solar-physics/synthetic-observables-paper-models <https://github.com/rice-solar-physics/synthetic-observables-paper-models>


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