Discrete Problems

# Discrete Problems

## Mathematical Specification of a Discrete Problem

To define an Discrete Problem, you simply need to give the function \$f\$ and the initial condition \$u₀\$ which define a function map:

\[u_{n+1} = f(u,p,t_n)\]

`f` should be specified as `f(u,p,t)` (or in-place as `f(du,u,p,t)`), and `u₀` should be an AbstractArray (or number) whose geometry matches the desired geometry of `u`. Note that we are not limited to numbers or vectors for `u₀`; one is allowed to provide `u₀` as arbitrary matrices / higher dimension tensors as well.

Note that if the discrete solver is set to have `scale_by_time=true`, then the problem is interpreted as the map:

\[u_{n+1} = u_n + dtf(u,p,t_n)\]

## Problem Type

### Constructors

`DiscreteProblem{isinplace}(f,u0,tspan)` : Defines the discrete problem with the specified functions.

### Fields

• `f`: The function in the map.

• `u0`: The initial condition.

• `tspan`: The timespan for the problem.

• `callback`: A callback to be applied to every solver which uses the problem. Defaults to a black CallbackSet, which will have no effect.

Note that if no `dt` and not `tstops` is given, it's assumed that `dt=1` and thus `tspan=(0,n)` will solve for `n` iterations. If in the solver `dt` is given, then the number of iterations will change. And if `tstops` is not empty, the solver will revert to the standard behavior of fixed timestep methods, which is "step to each tstop".