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A fast offline/online forward solver for stationary transport equation with multiple inflow boundary conditions and varying coefficients

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arxiv 2401.03147 v1 pith:BC4N7FZC submitted 2024-01-06 math.NA cs.NA

classification math.NAcs.NA
keywords offlineonlinesolverproblemsolvestagevarywhen
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It is of great interest to solve the inverse problem of stationary radiative transport equation (RTE) in optical tomography. The standard way is to formulate the inverse problem into an optimization problem, but the bottleneck is that one has to solve the forward problem repeatedly, which is time-consuming. Due to the optical property of biological tissue, in real applications, optical thin and thick regions coexist and are adjacent to each other, and the geometry can be complex. To use coarse meshes and save the computational cost, the forward solver has to be asymptotic preserving across the interface (APAL). In this paper, we propose an offline/online solver for RTE. The cost at the offline stage is comparable to classical methods, while the cost at the online stage is much lower. Two cases are considered. One is to solve the RTE with fixed scattering and absorption cross sections while the boundary conditions vary; the other is when cross sections vary in a small domain and the boundary conditions change many times. The solver can be decomposed into offline/online stages in these two cases. One only needs to calculate the offline stage once and update the online stage when the parameters vary. Our proposed solver is much cheaper when one needs to solve RTE with multiple right-hand sides or when the cross sections vary in a small domain, thus can accelerate the speed of solving inverse RTE problems. We illustrate the online/offline decomposition based on the Tailored Finite Point Method (TFPM), which is APAL on general quadrilateral meshes.

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Cited by 1 Pith paper

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  1. Synthetic Acceleration Preconditioners for Parametric Radiative Transfer Equations based on Trajectory-Aware Reduced Order Models

    math.NA 2025-09 conditional novelty 6.0 of 10

    A trajectory-aware reduced-order preconditioner fixes the offline-online residual mismatch in ROMSAD and solves parametric RTE in 2-3 online iterations on a lattice test.

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