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Qottmann
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Had a brief first read, looks very nice overall!
My main feedback is that while the content itself is great, the start after the abstract is a bit steep, and could potentially could be better motivated by providing some big picture context and anticipate what is going to happen in the demo
@Qottmann Added these to the introduction, along with a figure for surface code, to better help readers visualize the function. |
which function are you referring to? I think it could be nice to anticipate these diagrams and what they mean already in the abstract/intro i.e. creating a hand-drawn mock of them and explaining the different regions and what these diagrams say |
drdren
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Hi @obliviateandsurrender , I really enjoyed your demo. I think the readers will love reading it. I had few issues with the flow or the wording. Rather, I think that the definitions of the two thresholds could be made clearer.
The concept is tangible at a high level: If the physical qubits are very erroneous, then encoding qubits with a QEC code using many more qubits will only create noisier results. However, introducing the two different thresholds makes that story more complicated.
Can you clarify the two thresholds? Which should a person eager to implement an algorithm on hardware care about?
| error rates, computing two key metrics: (i) the pseudo-threshold, which is the break-even | ||
| point where a specific error-correcting code becomes better than doing nothing at all, and | ||
| (ii) the fault-tolerant threshold, the fundamental crossing point below which increasing our | ||
| code size provides an exponential suppression of errors. |
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I would say that the two thresholds don't seem very different to each other. Surely, if increasing the code size means that errors go down, then that means that QEC is better than doing nothing at all? The other way around is true too; if applying QEC is better than doing nothing, then that implies that increasing distance d should improve errors?
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Yes, they are not very different (at least in purpose), but rather in being a property of a code family or an individual code. Since generally, you would start with a single code implementation for your hardware, the pseudo-threshold is what you would like to establish, which is also known as the break-even testing. You would proceed to observe the latter only after the former is confirmed (as per my intuitive understanding).
drdren
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I really enjoyed reading this demo, @obliviateandsurrender! I think it is clear and well written. Amazing graphics. How? I am happy to approve this demo.
drdren
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Let's be sure to add the thumbnail when it is ready!
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With the thumbnails and dates changed, I am happy to approve this!
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Title: Understanding Fault-tolerant Threshold Theorem in Practice
Summary: A hands-on guide to understanding the fault-tolerant threshold theorem and simulating surface code pseudo-thresholds.
Relevant references:
Possible Drawbacks:
Related GitHub Issues:
If you are writing a demonstration, please answer these questions to facilitate the marketing process.
GOALS — Why are we working on this now?
Eg. Promote a new PL feature or show a PL implementation of a recent paper.
AUDIENCE — Who is this for?
Eg. Chemistry researchers, PL educators, beginners in quantum computing.
KEYWORDS — What words should be included in the marketing post?
Which of the following types of documentation is most similar to your file?
(more details here)