Random Recursive Hypergraphs
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arXiv
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| Format: | Preprint |
| Published: |
2022
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| _version_ | 1866911392290832384 |
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| author | Krapivsky, P. L. |
| author_facet | Krapivsky, P. L. |
| contents | Random recursive hypergraphs grow by adding, at each step, a vertex and an edge formed by joining the new vertex to a randomly chosen existing edge. The model is parameter-free, and several characteristics of emerging hypergraphs admit neat expressions via harmonic numbers, Bernoulli numbers, Eulerian numbers, and Stirling numbers of the first kind. Natural deformations of random recursive hypergraphs give rise to fascinating models of growing random hypergraphs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_07371 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Random Recursive Hypergraphs Krapivsky, P. L. Combinatorics Disordered Systems and Neural Networks Statistical Mechanics Random recursive hypergraphs grow by adding, at each step, a vertex and an edge formed by joining the new vertex to a randomly chosen existing edge. The model is parameter-free, and several characteristics of emerging hypergraphs admit neat expressions via harmonic numbers, Bernoulli numbers, Eulerian numbers, and Stirling numbers of the first kind. Natural deformations of random recursive hypergraphs give rise to fascinating models of growing random hypergraphs. |
| title | Random Recursive Hypergraphs |
| topic | Combinatorics Disordered Systems and Neural Networks Statistical Mechanics |
| url | https://arxiv.org/abs/2212.07371 |