# TREVR: A general $N log^2 N$ radiative transfer algorithm

**Authors:** J. J. Grond, R. M. Woods, J. W. Wadsley, H. M. P. Couchman

arXiv: 1902.08083 · 2019-03-06

## TL;DR

TREVR is a versatile, tree-based radiative transfer algorithm that efficiently computes radiation fields in astrophysical simulations, handling absorption and large source numbers with controlled accuracy.

## Contribution

It introduces a novel tree-based method for radiative transfer that scales as N log^2 N, enabling efficient simulations with absorption and large source populations.

## Key findings

- Accurately computes fluxes, ionization fronts, and shadows.
- Achieves N log N source handling speed without absorption.
- Maintains accuracy through a unique absorption-depth refinement criterion.

## Abstract

We present TREVR (Tree-based REVerse Ray Tracing), a general algorithm for computing the radiation field, including absorption, in astrophysical simulations. TREVR is designed to handle large numbers of sources and absorbers; it is based on a tree data structure and is thus suited to codes that use trees for their gravity or hydrodynamics solvers (e.g. Adaptive Mesh Refinement). It achieves computational speed while maintaining a specified accuracy via controlled lowering of the resolution of both sources and rays from each source. TREVR computes the radiation field in order ${N\log N_{source}}$ time without absorption and order ${N \log N_{source} \log{N}}$ time with absorption. These scalings arise from merging sources of radiation according to an opening angle criterion and walking the tree structure to trace a ray to a depth that gives the chosen accuracy for absorption. The absorption-depth refinement criterion is unique to TREVR. We provide a suite of tests demonstrating the algorithm's ability to accurately compute fluxes, ionization fronts and shadows.

## Full text

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## Figures

17 figures with captions in the complete paper: https://tomesphere.com/paper/1902.08083/full.md

## References

45 references — full list in the complete paper: https://tomesphere.com/paper/1902.08083/full.md

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Source: https://tomesphere.com/paper/1902.08083