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Easily Repairable Networks: Reconnecting Nodes after Damage

Overview of attention for article published in Physical Review Letters, September 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
12 tweeters
facebook
3 Facebook pages

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
62 Mendeley
citeulike
1 CiteULike
Title
Easily Repairable Networks: Reconnecting Nodes after Damage
Published in
Physical Review Letters, September 2014
DOI 10.1103/physrevlett.113.138701
Pubmed ID
Authors

Robert S. Farr, John L. Harer, Thomas M. A. Fink

Abstract

We introduce a simple class of distribution networks that withstand damage by being repairable instead of redundant. Instead of asking how hard it is to disconnect nodes through damage, we ask how easy it is to reconnect nodes after damage. We prove that optimal networks on regular lattices have an expected cost of reconnection proportional to the lattice length, and that such networks have exactly three levels of structural hierarchy. We extend our results to networks subject to repeated attacks, in which the repairs themselves must be repairable. We find that, in exchange for a modest increase in repair cost, such networks are able to withstand any number of attacks.

Twitter Demographics

The data shown below were collected from the profiles of 12 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
United Kingdom 2 3%
Brazil 1 2%
Italy 1 2%
Israel 1 2%
Netherlands 1 2%
Germany 1 2%
Unknown 52 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 29%
Student > Ph. D. Student 16 26%
Student > Master 7 11%
Professor > Associate Professor 6 10%
Professor 5 8%
Other 9 15%
Unknown 1 2%
Readers by discipline Count As %
Physics and Astronomy 22 35%
Engineering 10 16%
Computer Science 6 10%
Agricultural and Biological Sciences 6 10%
Mathematics 4 6%
Other 8 13%
Unknown 6 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 35. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 October 2014.
All research outputs
#534,305
of 14,291,367 outputs
Outputs from Physical Review Letters
#2,086
of 28,641 outputs
Outputs of similar age
#9,250
of 211,752 outputs
Outputs of similar age from Physical Review Letters
#66
of 624 outputs
Altmetric has tracked 14,291,367 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 28,641 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.4. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 211,752 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 624 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.