# ExponentialUtilities.jl: High-Performance Matrix Exponentiation and Products

ExponentialUtilities is a package of utility functions for matrix functions of exponential type, including functionality for the matrix exponential and phi-functions. The tools are used by the exponential integrators in OrdinaryDiffEq.

## Installation

To install ExponentialUtilities.jl, use the Julia package manager:

using Pkg
Pkg.add("ExponentialUtilities")

## Example

using ExponentialUtilities

A = rand(2,2)
exponential!(A)

v = rand(2); t = rand()
expv(t,A,v)

## Matrix-phi-vector product

The main functionality of ExponentialUtilities is the computation of matrix-phi-vector products. The phi functions are defined as

ϕ_0(z) = exp(z)
ϕ_(k+1)(z) = (ϕ_k(z) - 1) / z

In exponential algorithms, products in the form of ϕ_m(tA)b is frequently encountered. Instead of computing the matrix function first and then computing the matrix-vector product, the common alternative is to construct a Krylov subspace K_m(A,b) and then approximate the matrix-phi-vector product.

### expv and phiv

expv(t,A,b;kwargs) -> exp(tA)b
phiv(t,A,b,k;kwargs) -> [ϕ_0(tA)b ϕ_1(tA)b ... ϕ_k(tA)b][, errest]

For phiv, all ϕ_m(tA)b products up to order k is returned as a matrix. This is because it's more economical to produce all the results at once than individually. A second output is returned if errest=true in kwargs. The error estimate is given for the second-to-last product, using the last product as an estimator. If correct=true, then ϕ_0 through ϕ_(k-1) are updated using the last Arnoldi vector. The correction algorithm is described in [1].

You can adjust how the Krylov subspace is constructed by setting various keyword arguments. See the Arnoldi iteration section for more details.