DiffEqJump.jl is a component package in the SciML ecosystem. It holds the utilities for building jump equations, like stochastic simulation algorithms (SSAs), Gillespie methods or Kinetic Monte Carlo methods; and for building jump diffusions. It is one of the core solver libraries included in DifferentialEquations.jl. Users interested in using this functionality should see the DifferentialEquations.jl documentation. The documentation includes a tutorial and details on using DiffEqJump to simulate jump processes via SSAs (i.e. Gillespie methods), a reference on the types of jumps and available simulation methods, and a FAQ with information on changing parameters between simulations and using callbacks.
xiaomingfu2013/DiffEqJump.jl
Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)
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