activity
20172025
most citedForecasting Solar Cycle 25 using Deep Neural Networks

76 citations · 237 across the 15 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

astro-ph.SR202015 cited

Magnetic reconnections in the presence of three-dimensional magnetic nulls and quasi-separatrix layers

Sanjay Kumar, Sushree S. Nayak, Avijeet Prasad +1

Three-dimensional (3D) magnetohydrodynamic simulations are carried out to explore magnetic reconnections in the presence of 3D magnetic nulls and quasi-separatrix layers (QSLs). Th…

astro-ph.SR2020

Magnetohydrodynamic Simulation of Magnetic Null-point Reconnections and Coronal dimmings during the X2.1 flare in NOAA AR 11283

Avijeet Prasad, Karin Dissauer, Qiang Hu +4

The magnetohydrodynamics of active region NOAA 11283 is simulated using an initial non-force-free magnetic field extrapolated from its photospheric vector magnetogram. We focus on…

astro-ph.SR202030 cited

An Eruptive Circular-ribbon Flare with Extended Remote Brightenings

Chang Liu, Avijeet Prasad, Jeongwoo Lee +1

We study an eruptive X1.1 circular-ribbon flare on 2013 November 10, combining multiwavelength observations with a coronal field reconstruction using a non-force-free field method.…

astro-ph.SR2020

A data-driven MHD model of the weakly-ionized chromosphere

Mehmet Sarp Yalim, Avijeet Prasad, Nikolai Pogorelov +2

The physics of the solar chromosphere is complex from both theoretical and modeling perspectives. The plasma temperature from the photosphere to corona increases from ~5,000 K to ~…

astro-ph.SR202016 cited

Effects of Cowling Resistivity in the Weakly-Ionized Chromosphere

Mehmet Sarp Yalim, Avijeet Prasad, Nikolai Pogorelov +2

The physics of the solar chromosphere is complex from both theoretical and modeling perspectives. The plasma temperature from the photosphere to corona increases from ~5,000 K to ~…

astro-ph.SR202076 cited

Forecasting Solar Cycle 25 using Deep Neural Networks

B. Benson, W. D. Pan, A. Prasad +2

With recent advances in the field of machine learning, the use of deep neural networks for time series forecasting has become more prevalent. The quasi-periodic nature of the solar…