Hierarchical Quantum Information Splitting of an Arbitrary Two-Qubit State Based on a Decision Tree
Round 1
Reviewer 1 Report
The authors study the tree algorithm of machine learning with quantum communication to solve the problem of channel particle allocation in quantum communication. They define the level of communication participants using the decision tree algorithm based on “honesty,” “dishonesty,” and availability. Finally, they describe a hierarchical quantum information splitting scheme for an arbitrary two-qubit state based on a multi-qubit state. It is almost impossible to read and understand the manuscript, not only due to poor English but mainly due to the presentation. I will mention only the most striking points. At the start of subsection 3.2, the authors write, “the decision tree will generate the decision tree after learning the data set”. Maybe this sentence has some meaning for the authors, but it provides zero information to the reader. The following description of the decision tree is absolutely unclear. It is impossible to understand how probabilities of honesty and dishonesty are defined and calculated, the difference between models, or what these models are. But let us suppose that the reader has succeeded in understanding how the level of correspondents is defined and has started to read the quantum section. Beginning with the definition of a two-qubit state – is it normalized to one? Why do the authors choose these particular sixteen states for an eight-qubit state when there are $2^8$ possible combinations for eight positions? There is no explanation for why particular results of Alice’s measurements lead to the states of the remaining particles. It takes many pages of reading to find out that the receiver is chosen from the correspondents. Finally, the receiver performs unitary transformations – are they applied on his two particles, and what is the information they provide?
To summarize, I strongly do not recommend the publication of this manuscript.
Author Response
Dear reviewer，
Thank you for your suggestions. All your suggestions are very important to me, and those comments are valuable and very helpful.
We have read through comments carefully and have made corrections. And then, here are my answers to each comment. Revisions in the text are highlighted with red text and yellow to indicate changes.
We would like to thank you for allowing us to resubmit a revised copy of the manuscript and we highly appreciate your time and consideration.
Please see the attachment.
Thank you and best regards.
Yours sincerely,
Yundan Zheng
Author Response File: 
Author Response.docx
Reviewer 2 Report
Please see the attachment.
Comments for author File: 
Comments.pdf
Author Response
Dear reviewer，
Thank you for your suggestions. All your suggestions are very important to me, and those comments are valuable and very helpful.
We have read through comments carefully and have made corrections. And then, here are my answers to each comment. Revisions in the text are highlighted with red text and yellow to indicate changes.
We would like to thank you for allowing us to resubmit a revised copy of the manuscript and we highly appreciate your time and consideration.
Please see the attachment.
Thank you and best regards.
Yours sincerely,
Yundan Zheng
Author Response File: Author Response.docx
Reviewer 3 Report
The authors reported a more complicated method in this paper, compared with the earlier work like this one for example: "Hierarchical quantum-information splitting" by Wang et. al.
The paper seems reasonable and I would recommend to accept with minor revisions. The following are the revisions I would recommend:
1. English needs to be improved significantly. Here are just some examples of the parts that need to be corrected, revised or clarified:
line 97: "judge" the level of communication or evaluation the level of communication?
line 103: "decide" -> "to decide"
line 113: "number of honesty"? Do you mean "value of accuracy"?
line 121: "...the decision tree will generate the decision tree..."
line 123: "need optimizing" -> "need to optimize..."
line 147: "we need only the decision tree is restricted..." incorrect grammar.
"Matlab" needs to be capitalized consistently.
2. From conclusion"Compared with the previous hierarchical quantum information splitting scheme, our advantage is to design the scheme according to the decision, which makes the scheme more effective in practical applications, and can transmit more particle information with fewer particles." The author could have cited which they were comparing to.
Author Response
Dear reviewer，
Thank you for your suggestions. All your suggestions are very important to me, and those comments are valuable and very helpful.
We have read through comments carefully and have made corrections. And then, here are my answers to each comment. Revisions in the text are highlighted with red text and yellow to indicate changes.
We would like to thank you for allowing us to resubmit a revised copy of the manuscript and we highly appreciate your time and consideration.
Please see the attachment.
Thank you and best regards.
Yours sincerely,
Yundan Zheng
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The only revision the authors provided is the change of "tree" to "model". They still do not explain neither the correct definition of honesty nor the particular form of equation 1.
I do not recommend the publication of this manuscript.
Author Response
First of all, thank you very much for your kindly comments on our manuscript. There is no doubt that these comments are valuable and very helpful for revising and improving our manuscript. Please see the attachment.
Author Response File: Author Response.docx
