Composition of stochastic B-series with applications to implicit Taylor methods
Kristian Debrabant, Anne Kv{\ae}rn{\o}

TL;DR
This paper develops a new representation formula for stochastic B-series, enabling the derivation of order conditions for implicit Taylor methods, and introduces a family of strong order 1.5 methods for Itô SDEs.
Contribution
It provides the first order conditions for implicit Taylor methods using rooted trees and constructs a family of strong order 1.5 methods for Itô SDEs.
Findings
Derived order conditions for implicit Taylor methods
Constructed a family of strong order 1.5 Taylor methods
Applied the conditions to develop new numerical schemes
Abstract
In this article, we construct a representation formula for stochastic B-series evaluated in a B-series. This formula is used to give for the first time the order conditions of implicit Taylor methods in terms of rooted trees. Finally, as an example we apply these order conditions to derive in a simple manner a family of strong order 1.5 Taylor methods applicable to It\^o SDEs.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
