Numba-Accelerated 2D Diffusion-Limited Aggregation: Implementation and Fractal Characterization

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Hauptverfasser: Herho, Sandy H. S., Fajary, Faiz R., Anwar, Iwan P., Khadami, Faruq, Trilaksono, Nurjanna J., Suwarman, Rusmawan, Irawan, Dasapta E.
Format: Preprint
Veröffentlicht: 2026
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author Herho, Sandy H. S.
Fajary, Faiz R.
Anwar, Iwan P.
Khadami, Faruq
Trilaksono, Nurjanna J.
Suwarman, Rusmawan
Irawan, Dasapta E.
author_facet Herho, Sandy H. S.
Fajary, Faiz R.
Anwar, Iwan P.
Khadami, Faruq
Trilaksono, Nurjanna J.
Suwarman, Rusmawan
Irawan, Dasapta E.
contents We present dla-ideal-solver, a high-performance framework for simulating two-dimensional Diffusion-Limited Aggregation (DLA) using Numba-accelerated Python. By leveraging just-in-time (JIT) compilation, we achieve computational throughput comparable to legacy static implementations while retaining high-level flexibility. We investigate the Laplacian growth instability across varying injection geometries and walker concentrations. Our analysis confirms the robustness of the standard fractal dimension $D_f \approx 1.71$ for dilute regimes, consistent with the Witten-Sander universality class. However, we report a distinct crossover to Eden-like compact growth ($D_f \approx 1.87$) in high-density environments, attributed to the saturation of the screening length. Beyond standard mass-radius scaling, we employ generalized Rényi dimensions and lacunarity metrics to quantify the monofractal character and spatial heterogeneity of the aggregates. This work establishes a reproducible, open-source testbed for exploring phase transitions in non-equilibrium statistical mechanics.
format Preprint
id arxiv_https___arxiv_org_abs_2601_15440
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Numba-Accelerated 2D Diffusion-Limited Aggregation: Implementation and Fractal Characterization
Herho, Sandy H. S.
Fajary, Faiz R.
Anwar, Iwan P.
Khadami, Faruq
Trilaksono, Nurjanna J.
Suwarman, Rusmawan
Irawan, Dasapta E.
Pattern Formation and Solitons
Computational Physics
82C24, 60G50, 28A80, 82C80
We present dla-ideal-solver, a high-performance framework for simulating two-dimensional Diffusion-Limited Aggregation (DLA) using Numba-accelerated Python. By leveraging just-in-time (JIT) compilation, we achieve computational throughput comparable to legacy static implementations while retaining high-level flexibility. We investigate the Laplacian growth instability across varying injection geometries and walker concentrations. Our analysis confirms the robustness of the standard fractal dimension $D_f \approx 1.71$ for dilute regimes, consistent with the Witten-Sander universality class. However, we report a distinct crossover to Eden-like compact growth ($D_f \approx 1.87$) in high-density environments, attributed to the saturation of the screening length. Beyond standard mass-radius scaling, we employ generalized Rényi dimensions and lacunarity metrics to quantify the monofractal character and spatial heterogeneity of the aggregates. This work establishes a reproducible, open-source testbed for exploring phase transitions in non-equilibrium statistical mechanics.
title Numba-Accelerated 2D Diffusion-Limited Aggregation: Implementation and Fractal Characterization
topic Pattern Formation and Solitons
Computational Physics
82C24, 60G50, 28A80, 82C80
url https://arxiv.org/abs/2601.15440