Threshold functions in random subgraph counting in the random-connection model
Random-connection model serves as a prominent graph model other than the Erdős-Rényi model and the random geometric graph. The majority of the properties in the random-connection model has yet to be found. This thesis follows on from previous research on the normal approximation of subgraph counts a...
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2024
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sg-ntu-dr.10356-1756282024-05-06T15:37:06Z Threshold functions in random subgraph counting in the random-connection model Chan, Luo Xi Nicolas Privault School of Physical and Mathematical Sciences NPRIVAULT@ntu.edu.sg Mathematical Sciences Random-connection model Threshold Subgraph containment Random-connection model serves as a prominent graph model other than the Erdős-Rényi model and the random geometric graph. The majority of the properties in the random-connection model has yet to be found. This thesis follows on from previous research on the normal approximation of subgraph counts and graph connectivity to explore random subgraph containment in the random-connection model. In the dilute regime, an arbitrary graph G with at least one edge is asymptotically almost surely can be found in the corresponding model G_(H_λ ) (Ξ). While for the sparse regime, the relation between c_λ and λ^(-M(G)) serves as a possible threshold function for the subgraph containment. Bachelor's degree 2024-05-02T02:20:00Z 2024-05-02T02:20:00Z 2024 Final Year Project (FYP) Chan, L. X. (2024). Threshold functions in random subgraph counting in the random-connection model. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175628 https://hdl.handle.net/10356/175628 en application/pdf Nanyang Technological University |
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Mathematical Sciences Random-connection model Threshold Subgraph containment Chan, Luo Xi Threshold functions in random subgraph counting in the random-connection model |
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Random-connection model serves as a prominent graph model other than the Erdős-Rényi model and the random geometric graph. The majority of the properties in the random-connection model has yet to be found. This thesis follows on from previous research on the normal approximation of subgraph counts and graph connectivity to explore random subgraph containment in the random-connection model. In the dilute regime, an arbitrary graph G with at least one edge is asymptotically almost surely can be found in the corresponding model G_(H_λ ) (Ξ). While for the sparse regime, the relation between c_λ and λ^(-M(G)) serves as a possible threshold function for the subgraph containment. |
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Nicolas Privault |
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Nicolas Privault Chan, Luo Xi |
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Final Year Project |
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Chan, Luo Xi |
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Chan, Luo Xi |
title |
Threshold functions in random subgraph counting in the random-connection model |
title_short |
Threshold functions in random subgraph counting in the random-connection model |
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Threshold functions in random subgraph counting in the random-connection model |
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Threshold functions in random subgraph counting in the random-connection model |
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Threshold functions in random subgraph counting in the random-connection model |
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threshold functions in random subgraph counting in the random-connection model |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/175628 |
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