JumpProblem(prob,aggregator,jumps...) come in two forms. The first major form is if it does not have a
RegularJump. In this case, it can be solved with any integrator on
prob. However, in the case of a pure
JumpProblem over a
DiscreteProblem), there are special algorithms available. The
SSAStepper() is an efficient streamlined algorithm for running the
aggregator version of the SSA for pure
MassActionJump problems. However, it is not compatible with event handling. If events are necessary, then
FunctionMap does well.
If there is a
RegularJump, then specific methods must be used. The current recommended method is
TauLeaping if you need adaptivity, events, etc. If you just need the most barebones fixed time step leaping method, then
SimpleTauLeaping can have performance benefits.
If you are using jumps with a differential equations, use the same methods as in the case of the differential equation solving. However, the following algorithms are optimized for pure jump problems.
SSAStepper: a stepping algorithm for pure
JumpProblems. Does not support event handling, but does support saving controls like
These methods support mixing with event handling, other jump types, and all of the features of the normal differential equation solvers.
TauLeaping: an adaptive tau-leaping algorithm with post-leap estimates.
SimpleTauLeaping: a tau-leaping algorithm for pure
JumpProblems. Requires a choice of
RegularSSA: a version of SSA for pure
Regular jump diffusions are
JumpProblems where the internal problem is an
SDEProblem and the jump process has designed a regular jump.
EM: Explicit Euler-Maruyama.
ImplicitEM: Implicit Euler-Maruyama. See the SDE solvers page for more details.