Hi, quantum researchers and authors! Some friendly, informal, totally non-binding advice from your Editor in Chief at IEEE Transactions on Quantum Engineering (TQE). (Written in November 2025, posted here with small edits June 2026; my term as EiC will expire in March 2028. My policies may change before I step down, and the next EiC will certainly have their own policies, so the content here is only provisional; however, most of it will be helpful at any point in time and for any journal, I believe.)
The number of submissions to TQE has been climbing rapidly this year. (Hoo boy -- I wrote that in late 2025, and it's doubly true in mid-2026!). Thanks to every who reads, submits to, reviews for, edits, and produces TQE! The professional IEEE staff are amazing, and the editors tireless at a thankless job, so let me thank them publicly here.
With the increase in submissions, there are also naturally more papers with relatively easy to fix problems that slow down my share of the processing, and in turn slow down the whole journal.
So, when submitting a paper, ask yourself three questions:
- Is my paper going to generate a "clean" report in the plagiarism checker?
- Is my paper going to be easy for reviewers to work with?
- Is my paper tuned for this journal?
If every submission was clean on these fronts, my workload would go down at least 20-30%, and stalls in the pipeline would decrease even more.
1. So what is a "clean" report in the plagiarism checker?
Well, the checker returns a number, expressed as a percentage, that is very roughly the fraction of the paper for which it found matches with other materials in its stash (which includes almost everything in English on the web, not just other research papers in journals).
No paper ever written returns zero, so it's always a matter of making a judgment call. No one is going to ding you for boilerplate or generic text like "A graph G={V,E} comprises a set of vertices V and a set of edges E," but that's a human call, not something the system can automatically handle. If a paper has a moderately high score, I often set it aside for a deeper look later, slowing the movement of your paper through the system. So, if your paper will have a high score, please explain why in a cover letter.
The checker will pick up arXiv and other preprints as well as shorter IEEE conference versions of the same paper. Those are entirely legit, but I have to check; calling them out in a letter smooths the process.
If your paper draws on your own previously published work, YOU MUST SAY SO in a cover letter, and if this paper is an extended version of a conference paper, also in a footnote in the paper. i.e, "Portions of this paper previously appeared in x," or "This paper is an extended version of y."
In IEEE, there is no such thing as self-plagiarism. You are allowed to reuse your own work, with credit, of course. But a couple of issues come up: if the work is substantially the same, why bother republishing it? Explain what is new in this version.
And, as noted, there is the issue of copyright. PLEASE EXPLAIN THE COPYRIGHT STATUS OF THE PRIOR WORK. Without permission, IEEE cannot republish work where the copyright is held by others. If you still hold the copyright, or IEEE holds the copyright, we're good, but please tell me!
If you transferred the copyright to another company or organization, you also need to let me know, but we are probably going to ask you to rewrite it. If you really want to reuse the same text (or figure), it is your responsibility to get permission and make sure it is credited properly.
All of the above could have been written any time in the last two decades. The new twist is, of course, AI.
I'm not going to discuss a fully general AI policy here; that's for another time.
I get a lot of papers these days that have one sentence copied (generally but not always with one adjective or adverb switched for a synonym) from paper A, a sentence copied from paper B, a sentence from paper C...I don't think a human is deliberately copying from ten or twenty or even thirty separate sources. I'm pretty convinced that it's an LLM "helping" with the text, perhaps when translating from another language.
Of course more than half of the authors (and readers) of TQE aren't native English speakers, and using tools that help with English is legit. But you're still responsible for the final product.
(No, unfortunately, I don't have a pointer to a free plagiarism checker; building and running them is expensive, so they are paid services. If you're using an LLM, try asking it! If you are at a university, most of them have access to a checker, but it may or may not be available to you as a researcher rather than for use in checking classroom work.)
To recap, anything that makes the report complicated slows down the process.
2. Look at your paper.
I mean, LOOK at your paper, then ask yourself if someone who hasn't seen it before will find it appealing and easy to read, and therefore be favorably disposed toward the material.
Here I mean formatting and presentation: figures, text, and equations. (I don't mean the style. To submit to TQE, you don't have to put it in TQE style; we will review papers submitted in RevTeX, basic IEEE journal or conference format, ACM conference format, etc. The paper will have to be reformatted to TQE style later, though.)
A pet peeve of mine is figures with fonts that are too small to read. If I have to zoom in to 200-300% before the fonts become legible, there is a good chance I will desk reject the paper and ask you to redraw and resubmit. That delays your paper by weeks, and makes more work for everybody. Generally, the font in a figure should be the same size as the font in the caption. This problem is exacerbated if the figures are bitmap rather than vector graphics, which suddenly seems to be a problem. If I zoom in and I can't tell A from R, the paper is definitely going back to you. Not only is bitmap worse for print and scalability, it's also worse for searchability and perhaps for accessibility for visually impaired readers. Vector graphic text is usually searchable with ctrl-F, which can be handy. (Photos of equipment, of course, are okay in bitmap format.) Unless it affects readability, I generally won't send a paper back just because some plots are in bitmap format, but we will usually ask you to provide vector format for final typesetting.
This applies to equations, too; I sometimes get papers where the equations are bitmaps inserted from some other program. This is a pretty big no-no. Microsoft Word's equations aren't as pretty as LaTeX's, IMO, but they are fine when done carefully. Learn to use your tools.
Equations and figures should be numbered. Figures should have a caption and be floating, not inline. It's also friendly to compare your figures against recommended practices for different kinds of vision impairments such as the different types of color blindness.
I sometimes get papers that are just plain ugly: lots of changes of fonts and even font sizes, different line spacing sometimes even within the same page, etc. Except when it's REALLY bad, I won't desk reject a paper for that, but you can be sure it starts reviewers with a negative impression.
Check your references; particularly using BibTeX, different style files will leave out different fields, and I get a lot of papers with incomplete references. Clickable DOIs aren't required but are helpful, and if you confirm that they work then you save yourself the embarrassment of sending me an LLM-hallucinated reference.
Think about the process of writing a referee report. Help the reviewer (and later, the reader) as much as you can. Referees who get papers that require effort to read will put off the task, delaying a decision on your paper. (Such referees may also be less inclined to agree to review other papers we send them, on the assumption that handling our papers is a hassle. So you help everyone else, too, by submitting as sharp a paper as you can.)
3. Know your audience.
In particular, for TQE, papers that begin by explaining X, Y, Z and CNOT gates waste space and opportunity -- what a collaborator of mine calls "momentum" -- and you will lose readers. For the TQE audience, it's not necessary, and I don't want it 100+ times per year in our journal. This is also strongly correlated with newcomers to the field, whose work is often too basic to represent a publishable advance, so once again you start off on the wrong foot with reviewers. If there is too much of it, I will desk reject the paper and ask you to fix and resubmit.
Conversely, it is fair to assume that TQE readers are unfamiliar with the basics of e.g. machine learning or your problem domain and to include some background material. But if you are spending a lot of space on purely classical ML, have you submitted to the right journal?
The scope of TQE is, broadly, quantum computing, communications and sensing. I desk reject papers on quantum-inspired (read: classical) algorithms and on post-quantum cryptography (PQC), which deserves to be reviewed, read and used by classical cryptographers and systems engineers. I also desk reject papers that are pure physics, without a clear connection to the use of superposition, entanglement and interference (discrete or continuous) to surpass classical systems. True supporting tech such as classical cryogenic processors or cooling systems for quantum computers is very welcome, though!
In short, to repeat, know your audience -- the readers, reviewers and editors.
Let me reiterate, this is informal, friendly, non-binding advice to help writers create papers that are ready for the TQE review process.
Good luck to all authors, I love reading your work. You are working in the most exciting field right now, IMO, and we are all on the same side -- building, deploying and using the best systems we can. Stop me and say hi when you see me at a conference!
