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Unsupervised strategies for identifying optimal parameters in Quantum Approximate Optimization Algorithm

Overview of attention for article published in EPJ Quantum Technology , May 2022
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Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
8 Mendeley
Title
Unsupervised strategies for identifying optimal parameters in Quantum Approximate Optimization Algorithm
Published in
EPJ Quantum Technology , May 2022
DOI 10.1140/epjqt/s40507-022-00131-4
Authors

Charles Moussa, Hao Wang, Thomas Bäck, Vedran Dunjko

Twitter Demographics

The data shown below were collected from the profiles of 2 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 25%
Student > Ph. D. Student 1 13%
Student > Master 1 13%
Unknown 4 50%
Readers by discipline Count As %
Computer Science 3 38%
Physics and Astronomy 1 13%
Unknown 4 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 May 2022.
All research outputs
#17,475,049
of 22,412,863 outputs
Outputs from EPJ Quantum Technology
#84
of 109 outputs
Outputs of similar age
#236,784
of 343,206 outputs
Outputs of similar age from EPJ Quantum Technology
#1
of 1 outputs
Altmetric has tracked 22,412,863 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 109 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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 343,206 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them