A self-consistent approach to measure preferential attachment in networks and its application to an inherent structure network
Preferential attachment is one possible way to obtain a scale-free network. We develop a self-consistent method to determine whether preferential attachment occurs during the growth of a network, and to extract the preferential attachment rule using time-dependent data. Model networks are grown with...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
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Elsevier
2005
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| _version_ | 1826261659463712768 |
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| author | Massen, C Doye, J |
| author_facet | Massen, C Doye, J |
| author_sort | Massen, C |
| collection | OXFORD |
| description | Preferential attachment is one possible way to obtain a scale-free network. We develop a self-consistent method to determine whether preferential attachment occurs during the growth of a network, and to extract the preferential attachment rule using time-dependent data. Model networks are grown with known preferential attachment rules to test the method, which is seen to be robust. The method is then applied to a scale-free inherent structure network, which represents the connections between minima via transition states on a potential energy landscape. Even though this network is static, we can examine the growth of the network as a function of a threshold energy (rather than time), where only those transition states with energies lower than the threshold energy contribute to the network.For these networks we are able to detect the presence of preferential attachment, and this helps to explain the ubiquity of funnels on energy landscapes. However, the scale-free degree distribution shows some differences from that of a model network grown using the obtained preferential attachment rules, implying that other factors are also important in the growth process. |
| first_indexed | 2024-03-06T19:24:50Z |
| format | Journal article |
| id | oxford-uuid:1b5a2c1b-25c7-4077-a828-1dd47785b6f1 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:24:50Z |
| publishDate | 2005 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:1b5a2c1b-25c7-4077-a828-1dd47785b6f12022-03-26T10:59:55ZA self-consistent approach to measure preferential attachment in networks and its application to an inherent structure networkJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1b5a2c1b-25c7-4077-a828-1dd47785b6f1EnglishSymplectic Elements at OxfordElsevier2005Massen, CDoye, JPreferential attachment is one possible way to obtain a scale-free network. We develop a self-consistent method to determine whether preferential attachment occurs during the growth of a network, and to extract the preferential attachment rule using time-dependent data. Model networks are grown with known preferential attachment rules to test the method, which is seen to be robust. The method is then applied to a scale-free inherent structure network, which represents the connections between minima via transition states on a potential energy landscape. Even though this network is static, we can examine the growth of the network as a function of a threshold energy (rather than time), where only those transition states with energies lower than the threshold energy contribute to the network.For these networks we are able to detect the presence of preferential attachment, and this helps to explain the ubiquity of funnels on energy landscapes. However, the scale-free degree distribution shows some differences from that of a model network grown using the obtained preferential attachment rules, implying that other factors are also important in the growth process. |
| spellingShingle | Massen, C Doye, J A self-consistent approach to measure preferential attachment in networks and its application to an inherent structure network |
| title | A self-consistent approach to measure preferential attachment in
networks and its application to an inherent structure network |
| title_full | A self-consistent approach to measure preferential attachment in
networks and its application to an inherent structure network |
| title_fullStr | A self-consistent approach to measure preferential attachment in
networks and its application to an inherent structure network |
| title_full_unstemmed | A self-consistent approach to measure preferential attachment in
networks and its application to an inherent structure network |
| title_short | A self-consistent approach to measure preferential attachment in
networks and its application to an inherent structure network |
| title_sort | self consistent approach to measure preferential attachment in networks and its application to an inherent structure network |
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