We show a way to improve properties of a ODE integrators, by introducing a composition of the methods with a different steps.

This post is based on the work of the Ernst Harrier [1] and doesn’t contain any additional research work.

Here we want to solve a system of equations that can we written as:

\[ \dot{y} = f(y). \]

In order to solve it we are introducing a mapping from an old state at \(t0\) to a new one at \(t_1 = t_0 + dt\):

\[\Phi_h: y_{n} \rightarrow y_{n+1}\]

In order to increase the order of the solution while preserving some desirable properties of the base method we may prepare a compositional method:

\[\Psi_h = \Phi_{\gamma_1h} \circ \ldots \circ \Phi_{\gamma_nh},\]

where \(\gamma_i\) is a coefficient from \(\mathbb R\). This approach was studied by Suzuki, Yoshina, McLackcan in 1990th. Here we compose a base method at a different points in time.

We have a theorem about this approach to compositional methods.

Theorem

Let \(\Phi_h\) be a one-step method of order \(p\). If

\[ \begin{eqnarray} \gamma_1 + \ldots + \gamma_s = 1 \\ \gamma_1^{p+1} + \ldots + \gamma_s^{p+1} = 0 \\ \end{eqnarray} \] then the compositional method \(\Psi_h\) is at least of the order \(p+1\).

This gives theorem gives us a nice way to improve properties of the existing method. The question now is how to find a good coefficients \(\gamma_i\).

The first notice is that equations does not have a real solution for the odd \(p\), so we can improve only solutions with even \(p\).

The smallest number \(s\) where a solution in reals exists is \(3\). And coefficients are defined as:

\[ \gamma_1 = \gamma_3 = \frac{1}{2 - 2^{\frac{1}{p+1}}} \]

\[ \gamma_2 = - \frac{2^{\frac{1}{p+1}}}{2 - 2^{\frac{1}{p+1}}} \]

This method is called tripple jump. Lets check how does it work.

At first we will introduce a coefficients

g1 :: Int -> Double
g1 p = 1 / (2 - 2**(1/(fromIntegral p+1)))
g2 :: Int -> Double
g2 p = - 2**(1/(fromIntegral p+1)) / ( 2 - 2**(1/(fromIntegral p+1)))
g3 :: Int -> Double
g3 = g1

Having a method of an order 2 (for example standard Runge-Kutta method) we may use a composition a points defined by \(\gamma_i\) with \(p=2\). Let step be a \(dt = 1\) for simplicity.

> t :: Int -> Double -> [Double]
> t p dt = map (*dt) [g1 p, g2 p, g3 p]
*Main> t 2 1
[1.3512071919596578,-1.7024143839193153,1.3512071919596578]

We have 3 points. If we will take a compositional method \(\Psi\) in the points we got then we will have a method of order \(3\). However if you method is symmetric then it’s order is \(4\) and we can apply a tripple jump once again to our composed method.

> ut :: Int -> [Double] -> [Double]
> ut p xs = xs >>= (\x -> t (p+2) x)
*Main> ut 4 (t 2 1)
[1.5081944151591316,-1.665181638358605,1.5081944151591316,-1.900205890992877
,2.097997398066439,-1.900205890992877,1.5081944151591316,-1.665181638358605,1.5081944151591316]

This is a coefficients for a compositional method of order \(5\), (\(6\) due to symmetry. Applying tripple jump nce again:

*Main> ut 6 \$ ut 4 (t 2 1)
[1.639448210847001,-1.77070200653487,1.639448210847001,-1.8100975778074668
,1.955013517256328,-1.8100975778074668,1.639448210847001,-1.77070200653487
,1.639448210847001,-2.0655753110586246,2.2309447311243717,-2.0655753110586246
,2.2805800406433505,-2.4631626832202618,2.2805800406433505,-2.0655753110586246
,2.2309447311243717,-2.0655753110586246,1.639448210847001,-1.77070200653487
,1.639448210847001,-1.8100975778074668,1.955013517256328,-1.8100975778074668
,1.639448210847001,-1.77070200653487,1.639448210847001]

this is a compositional method of order 8.

To see a places where function will be evaluated we can use:

*Main> scanl (+) 0 $ ut 6 $ ut 4 (t 2 1)
[0.0,1.639448210847001,-0.131253795687869,1.508194415159132,-0.30190316264833483
,1.6531103546079933,-0.15698722319947356,1.4824609876475274,-0.28824101888734255
,1.3512071919596584,-0.7143681190989661,1.5165766120254056,-0.548998699033219
,1.7315813416101316,-0.7315813416101302,1.5489986990332203,-0.5165766120254043
,1.7143681190989675,-0.3512071919596571,1.2882410188873439,-0.4824609876475261
,1.156987223199475,-0.6531103546079919,1.3019031626483362,-0.5081944151591307
,1.1312537956878703,-0.6394482108469997,1.0000000000000013]

This way we may obtain a method of any order by the price of a terrible zig-zag of the step points.

Another approach to a compositional method is using Suzuki`s Fractals.

The same schema exists for Suzuki`s Fractals, however how we have a diffierent coefficients:

\[ \begin{eqnarray} \gamma_1 = \gamma_2 = \gamma_4 = \gamma_5 = \frac{1}{4-4^{\frac{1}{p+1}}} \\ \gamma_3 = - \frac{4^{\frac{1}{p+1}}}{4-4^{\frac{1}{p+1}}} \end{eqnarray} \]

However \(t\) and \(ut\) methods looks quite ugly and we may want to improve this situation.

{-# LANGUAGE DataKinds #-}
{-# LANGUAGE KindSignatures #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE TypeOperators #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE UndecidableInstances #-}
import GHC.TypeLits
import GHC.Exts (Constraint)
import Data.Proxy
-- Coefficients
g1 :: Integer -> Double
g1 p = 1 / (2 - 2**(1/(fromIntegral p+1)))
g2 :: Integer -> Double
g2 p = - 2**(1/(fromIntegral p+1)) / ( 2 - 2**(1/(fromIntegral p+1)))
g3 :: Integer -> Double
g3 = g1
-- Description of the method
data RK2 = RK2
-- Description of the method order
type family Order a :: Nat
type instance Order RK2 = 2
-- Description of symmetric properties of the method
type family IsSymmetric a :: Constraint
type instance IsSymmetric RK2 = ()
-- One level composition
buildComposePoints :: forall p . KnownNat (Order p)
=> p -> Double -> [Double]
buildComposePoints p dt = map (*dt) [g1 o, g2 o, g3 o]
where
o = natVal (Proxy :: Proxy (Order p))
-- Composition for the symmetric method
buildComposePointsSym :: forall p n . (UpdateCompose (Order p + 2) n, IsSymmetric p, KnownNat (Order p), KnownNat n)
=> p -> Proxy n -> Double -> [Double]
buildComposePointsSym p pn dt = update (Proxy :: Proxy ((Order p) + 2)) pn (buildComposePoints p dt)
class UpdateCompose (k :: Nat) (v::Nat) where
update :: Proxy k -> Proxy v -> [Double] -> [Double]
class UpdateComposeCase (leq :: Bool) (k :: Nat) (v :: Nat) where
updateCase :: Proxy leq -> Proxy k -> Proxy v -> [Double] -> [Double]
instance UpdateComposeCase (k <=? v) k v => UpdateCompose k v where
update = updateCase (Proxy :: Proxy (k <=? v))
instance UpdateComposeCase False k v where
updateCase _ _ _ = id
instance (KnownNat k, UpdateCompose (k+2) v) => UpdateComposeCase True k v where
updateCase _ k v ds = update (plus2 k) v (ds >>= \x -> map (*x) [g1 o, g2 o, g3 o])
where
o = natVal k
plus2 :: Proxy n -> Proxy (n+2)
plus2 _ = Proxy



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