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| Natura: | Preprint |
| Pubblicazione: |
2023
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| Accesso online: | https://arxiv.org/abs/2312.15655 |
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| _version_ | 1866916111606349824 |
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| author | Arakawa, Sota |
| author_facet | Arakawa, Sota |
| contents | Understanding the geodesic properties of fractal aggregates is essential, as their thermal and mechanical properties are characterized by their geodesics. In this study, we investigate the root mean square (RMS) of the geodesic between two constituent particles within fractal aggregates prepared by ballistic cluster-cluster aggregation (BCCA), diffusion-limited aggregation (DLA), and growing self-avoiding walk (GSAW) processes in two- and three-dimensional spaces. We find that the dependence of the RMS of the geodesic on the number of constituent particles is given by the following equation: $N \approx k_{\rm g} {D_{\rm RMS}}^{d_{\rm g}}$, where $N$ is the number of constituent particles and $D_{\rm RMS}$ is the RMS of the geodesic. We numerically obtain the prefactor $k_{\rm g}$ and exponent $d_{\rm g}$ for these fractal aggregates. We name the exponent ``the geodesic dimension'', and it is compared with the fractal dimension. Our findings show that the difference between fractal and geodesic dimensions varies significantly depending on the preparation procedure for fractals. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_15655 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Root mean squares of distance and geodesic between two constituent particles within fractal aggregates prepared by BCCA, DLA, and GSAW procedures Arakawa, Sota Soft Condensed Matter Disordered Systems and Neural Networks Understanding the geodesic properties of fractal aggregates is essential, as their thermal and mechanical properties are characterized by their geodesics. In this study, we investigate the root mean square (RMS) of the geodesic between two constituent particles within fractal aggregates prepared by ballistic cluster-cluster aggregation (BCCA), diffusion-limited aggregation (DLA), and growing self-avoiding walk (GSAW) processes in two- and three-dimensional spaces. We find that the dependence of the RMS of the geodesic on the number of constituent particles is given by the following equation: $N \approx k_{\rm g} {D_{\rm RMS}}^{d_{\rm g}}$, where $N$ is the number of constituent particles and $D_{\rm RMS}$ is the RMS of the geodesic. We numerically obtain the prefactor $k_{\rm g}$ and exponent $d_{\rm g}$ for these fractal aggregates. We name the exponent ``the geodesic dimension'', and it is compared with the fractal dimension. Our findings show that the difference between fractal and geodesic dimensions varies significantly depending on the preparation procedure for fractals. |
| title | Root mean squares of distance and geodesic between two constituent particles within fractal aggregates prepared by BCCA, DLA, and GSAW procedures |
| topic | Soft Condensed Matter Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2312.15655 |