A fast-marching algorithm for non-monotonically evolving fronts

The non-monotonic propagation of fronts is considered. When the speed function $F:\mathbb{R}^{n} \times [0,T]\rightarrow \mathbb{R}$ is prescribed, the non-linear advection equation $ϕ_{t}+F|\nabla ϕ|=0$ is a Hamilton-Jacobi equation known as the level-set equation. It is argued that a small enough neighbourhood of the zero-level-set $\mathcal{M}$ of the solution $ϕ: \mathbb{R}^{n} \times [0,T] \rightarrow \mathbb{R}$ is the graph of $ψ:\mathbb{R}^{n} \rightarrow \mathbb{R}$ where $ψ$ solves a Dirichlet problem of the form $H(\vec{u},ψ(\vec{u}),\nabla ψ(\vec{u}))=0$. A fast-marching algorithm is presented where each point is computed using a discretization of such a Dirichlet problem, with no restrictions on the sign of $F$. The output is a directed graph whose vertices evenly sample $\mathcal{M}$. The convergence, consistency and stability of the scheme are addressed. Bounds on the computational complexity are estimated, and experimentally shown to be on par with the Fast Marching Method. Examples are presented where the algorithm is shown to be globally first-order accurate. The complexities and accuracies observed are independent of the monotonicity of the evolution.

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