TreeCol: a novel approach to estimating column densities in astrophysical simulations
Paul C. Clark, Simon C.O. Glover, Ralf S. Klessen

TL;DR
TreeCol is a fast, efficient, and accurate tree-based method for estimating column densities in astrophysical simulations, enabling improved modeling of radiation attenuation with minimal additional computational cost.
Contribution
TreeCol introduces a novel, scalable, and easy-to-implement scheme for calculating column densities using a HEALPix sphere, compatible with existing tree-based solvers.
Findings
Achieves better than 10% accuracy in column density estimates.
Computational cost scales as N log N, much faster than traditional methods.
Produces dust temperature results comparable to full Monte Carlo simulations.
Abstract
We present TreeCol, a new and efficient tree-based scheme to calculate column densities in numerical simulations. Knowing the column density in any direction at any location in space is a prerequisite for modelling the propagation of radiation through the computational domain. TreeCol therefore forms the basis for a fast, approximate method for modelling the attenuation of radiation within large numerical simulations. It constructs a HEALPix sphere at any desired location and accumulates the column density by walking the tree and by adding up the contributions from all tree nodes whose line of sight contributes to the pixel under consideration. In particular when combined with widely-used tree-based gravity solvers the new scheme requires little additional computational cost. In a simulation with resolution elements, the computational cost of TreeCol scales as , instead of…
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.
