DiffEqJump.jl provides methods for simulating jump processes, known as stochastic simulation algorithms (SSAs), Doob's method, Gillespie methods, or Kinetic Monte Carlo methods across different fields of science. It also enables the incorporation of jump processes into hybrid jump-ODE and jump-SDE models, including jump diffusions.

DiffEqJump is a component package in the SciML ecosystem, and one of the core solver libraries included in DifferentialEquations.jl.

The documentation includes


There are two ways to install DiffEqJump.jl. First, users may install the meta DifferentialEquations.jl package, which installs and wraps OrdinaryDiffEq.jl for solving ODEs, StochasticDiffEq.jl for solving SDEs, and DiffEqJump.jl, along with a number of other useful packages for solving models involving ODEs, SDEs and/or jump process. This single install will provide the user with all of the facilities for developing and solving Jump problems.

To install the DifferentialEquations.jl package, refer to the following link for complete installation details.

If the user wishes to separately install the DiffEqJump.jl library, which is a lighter dependency than DifferentialEquations.jl, then the following code will install DiffEqJump.jl using the Julia package manager:

using Pkg


See also the SciML Community page.