Monte-Carlo Simulation of Solar Active-Region Energy
M.S. Wheatland

TL;DR
This paper introduces a Monte-Carlo simulation method for modeling active-region energy in solar physics, enabling efficient analysis of flare statistics and time-dependent behaviors, and compares results with observed solar flare data.
Contribution
It presents a new Monte-Carlo approach to solve stochastic models of solar active-region energy, improving efficiency and enabling detailed event and waiting-time analysis.
Findings
Models with energy-dependent transition rates show non-Poisson waiting times.
The original energy-independent model aligns best with observed flare statistics.
Monte-Carlo simulations effectively explore flare event distributions.
Abstract
A Monte-Carlo approach to solving a stochastic jump transition model for active-region energy (Wheatland and Glukhov, Astrophys. J. 494, 1998; Wheatland, Astrophys. J. 679, 2008) is described. The new method numerically solves the stochastic differential equation describing the model, rather than the equivalent master equation. This has the advantages of allowing more efficient numerical solution, the modelling of time-dependent situations, and investigation of details of event statistics. The Monte-Carlo approach is illustrated by application to a Gaussian test case, and to the class of flare-like models presented in Wheatland (2008), which are steady-state models with constant rates of energy supply, and power-law distributed jump transition rates. These models have two free parameters: an index (), which defines the dependence of the jump transition rates on active-region…
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