Approximate von Neumann entropy for directed graphs
- Submitting institution
-
University of York
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 54874555
- Type
- D - Journal article
- DOI
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10.1103/PhysRevE.89.052804
- Title of journal
- Physical Review E
- Article number
- 052804
- First page
- -
- Volume
- 89
- Issue
- 5
- ISSN
- 1539-3755
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 30
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The first paper to establish a rigorous framework for evaluating the entropy of directed graphs based on ideas from quantum information theory. It then proceeds to develop an approximate practical measure for very large directed networks. Evaluated on a large number of datasets both for accuracy of approximation and usefulness in examining complex networks. The work is the result of a funded UoY/FAPESP collaboration with University of Sao Paulo.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -