NISQ-Ready Community Detection Based on Separation-Node Identification

Round 1

Reviewer 1 Report

The paper is very interesting and suggests a new approach (well-founded in theory) for a central problem in which there has been no progress in the past few years.

My main comment is - please rearrange the results part. It's hard to follow all the box plot figures and compare across methods and datasets. Please arrange it in one big table (rows are algorithms, columns are datasets).

Also, please explain how you measure accuracy, what is the ground truth in the dataset, and how it was labeled. More generally, add a table that summarizes all the datasets (size, etc)

A reference that I would add to the introduction is "Simple statistics are sometimes too simple: A case study in social media data", which suggest another approach to clustering based in dimensionality reduction.

Author Response

Dear reviewer,

thank you for providing helpful feedback on our article. Please find our response in the .pdf file enclosed.

Sincerely,
The authors

Author Response File: Author Response.pdf

Reviewer 2 Report

Attached

 

Comments for author File: Comments.pdf

Needs English revision in some parts of the article.

 

Author Response

Dear reviewer,

thank you for providing helpful feedback on our article. Please find our response in the .pdf file enclosed.

Sincerely,
The authors

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The authors addressed my previous comments, I don't have issues with the article in the current form.

 

Please run another proof-reading.