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Iterative Power Algorithm for Global Optimization with Quantics Tensor Trains

Overview of attention for article published in Journal of Chemical Theory and Computation, May 2021
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Mentioned by

twitter
5 X users

Readers on

mendeley
16 Mendeley
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Article details
Title
Iterative Power Algorithm for Global Optimization with Quantics Tensor Trains
Published in
Journal of Chemical Theory and Computation, May 2021
DOI 10.1021/acs.jctc.1c00292
Pubmed ID
Authors

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X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 3 19%
Researcher 3 19%
Unspecified 1 6%
Student > Master 1 6%
Unknown 8 50%
Readers by discipline
Readers by discipline Count As %
Computer Science 2 13%
Physics and Astronomy 2 13%
Chemistry 2 13%
Unspecified 1 6%
Linguistics 1 6%
Other 1 6%
Unknown 7 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 29 May 2021.
All research outputs
#20,997,304
of 32,950,213 outputs
Outputs from Journal of Chemical Theory and Computation
#3,763
of 8,575 outputs
Outputs of similar age
#252,453
of 473,615 outputs
Outputs of similar age from Journal of Chemical Theory and Computation
#85
of 143 outputs
Altmetric has tracked 32,950,213 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,575 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 53% 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 473,615 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 143 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.