Recent comments from SciRate

Hi Chignons and Kristel,

I’d like to share a recent work of mine that’s closely related to yours: [Near-Optimal Parameter Tuning of Level-1 QAOA for Ising Models][1]. We show how to efficiently obtain provably optimal parameters for QAOA at $p = 1$ in linear time, without making any assumptions a

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Love the title! :D

Dear all,

Let me add a few points here.
Firstly, nice work Tim and I really appreciate the retraction of the evidence claim upon re-doing the comparison with proper HCI.

Despite the upset our work (arXiv:2501.07231) of pointing out flaws in QSCI might have caused some, to date no real solu

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Dear Michal Krompiec,

Thank you for your comment.

We actually released a revision to the preprint on 10th September, in which we addressed all of the points you raise here. For example, we included HCI results generated with PyCI and found that while, yes, HCI produces the most compact wavef

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We've made a significant update for this paper. The new discovery is the transversal CCZ gates on the 5D non-Abelian self-correcting memory using a more general type of cohomology operation (classified in https://arxiv.org/abs/2411.15848) involving the higher cup product, which is able to break th

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It is surprising to see that QSCI (aka SQD) is compared (just like in the Robledo-Moreno paper) to SCI in PySCF, rather than only to the implementation of HCI in PyCI, or to HCI as implemented in the reference codes Arrow and Dice. In other words, beating PySCF's SCI does not invalidate Reinholdt's

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Thanks for the comments! LCHS addresses non-unitary dynamics, and our work focuses on unitary dynamics.

It seems that your approach relies on post-selecting the (+1) measurement outcomes. How would you simulate the post-selection or measurement process within the ZX-calculus framework? Presumably, you'd need to introduce errors into the ZX graph, then contract the graph up to the measurement nodes and

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Thank you, Joseph and Konstantinos, for sharing your really nice works! We will include them in our next paper update.

I also want to mention that our previous theory work https://arxiv.org/abs/2401.10095 has proven that all shallow quantum ML models are efficiently learnable, and are known in co

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Thanks for reading. Replying on behalf of Zhenghao.

This error model was picked over the circuit-level one, like Boldizsár Poór mentioned: "something like a ZX diagram, where there is no fixed direction of time, this noise model seems like a natural choice". We agree with this.

Operationally, it's

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Awesome work! Really nice.

I would like to bring to your attention our QNLP paper from our Oxford team [ https://arxiv.org/abs/2409.08777 ]. Of course, the learning tasks, the motivations, and the methods are different. But I claim that the Strategy for bypassing trainability issues is the same: tr

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Hi guys, nice work!

In case you missed it, we also developed a method to classically train a class of quantum generative models with hardness guarantees (IQP circuits), and managed to train circuits with up to 1000 qubits.

https://arxiv.org/abs/2503.02934

I think the $|W\rangle$ and $|CCZ\rangle$ are in different SLOCC classes, no local operations + CC can convert one to another. It would have to some non-local operations, maybe you can play with H-boxes ($|CCZ\rangle$) and the $|W\rangle$ written as a ZX-diagram, equation 7 from https://arxiv.org/ab

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Just jumping in to say that in https://arxiv.org/pdf/2506.17181 we studied this exact error model. For something like a ZX diagram, where there is no fixed direction of time, this noise model seems like a natural choice.

Regarding its relation to circuit-level noise, if you use the standard mappi

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Congrats on the results! Do you know how your noise model in Section 5 compares to standard circuit-level noise?

It seems to omit some $O(p)$ errors after two-qubit gates. On the flip side, as you explain, it has more error locations, which increases some error probabilities.

Why pick this mo

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Hi! I have a question regarding the noise model considered here. You state that "we performed numerical simulations under a circuit-level noise model", but then, when the model is described, you consider biased noise in the physical qubits and "each stabilizer measurement may independently fail with

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This is great work! Looking forward to reading it carefully. Can you comment on how the algorithm complexity compares with the recent advances using Linear Combination of Hamiltonian Simulation (LCHS), such as 2508.19238?

Ah, yes, that is quite relevant! Looking back, the $RP^2$ cultivation authors cite this work, but I missed its importance. Thanks for bringing it to my attention, I'll think about how I'd want to mention it in an updated version of the paper.

I think that is something I am looking for! Obviously to be competitive with $|T\rangle$ states we'd want a protocol that didn't use too many $|C_{XYZ}\rangle$ states, but any concrete protocol would be a great place to start. Optimizations can come later.

Although after twenty minutes of fiddlin

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Congrats on the nice cultivation results, Jahan! I also wanna bring your attention to the work that first realized logical Hadamard on $RP^2$ surface code: https://journals.aps.org/prxquantum/abstract/10.1103/PRXQuantum.5.020360, which is the type of gate that can be measured for your cultivatio

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Hi Jahan, using three pi/3 phase states we can produce a |W> state. So it looks like with the pi/6 states that protocol produces you could construct a |W> state using 6 of them (though there might be a smarter way than just combining two pi/6 together to get a pi/3).
Though I don't have the details

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I, the author, have found out some bugs regarding figures that should be fixed in the next version soon.

Good to know 😌. Thanks!

I think it's wrong.

Shor's algorithm produces states that have exponentially huge numbers of likely outputs. Small subsections of the output will be exponentially close to uniformly random. So sampling small parts of the output is equivalent to sampling a uniformly randomly generated number. The

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I agree! Being able to (even probabilistically) produce a $|CCZ\rangle$ state or similar with $|C_{XYZ}\rangle$ states would basically solve the problem.

I started out restricting to $CX$ gates and $e^{i\pi Z/12}$ rotations (done probabilistically with $|C_{XYZ}\rangle$ states as specified in Br

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The main reason to expect the X+Y+Z magic state to be good is that it reaches further outside of the stabilizer octohedron compared to the X+Y magic state. It is "more magical". But conversions between different forms of magic are often lossy... so it could still be that it ends up more expensive to

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Why not?

Using this space to advertise a question I have: are $|C_{XYZ}\rangle$ magic states (i.e., eigenstates of $(X+Y+Z)$) useful? Because while $|T\rangle$ states are kind of hard to cultivate on the surface code, $|C_{XYZ}\rangle$ states are quite easy, see [my thread here][1].

But just because they

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@craig-gidney Thoughts?

Why?

We have updated the paper
with two new cultivation types.
Hope you'll enjoy.

More interestingly, the first author "Scited" **every single paper** listed here on Scirate but did not "cite" in their paper : P

Hi, Alex

We thank you for pointing out the references. Indeed, we find Theorem 1.2 of https://arxiv.org/pdf/2505.16715 to be identical to our result; however, the proof differs somewhat, particularly in its dependence on the operator norm and accuracy.

Regarding the second paper, the BQP-hard

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To the authors,

Since last year, there has been substantial progress on trace estimation of quantum state powers, and I have been following this ongoing line of research with interest.

I have a few concerns regarding your manuscript. First, your main result, Theorem 1, is **completely identica

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Congrats on your paper! Is your data available? Would you consider making your source code public?

I just wanted to point out a possible typo in the no-distillation proof that would slightly change the exponential scaling required in the number of copies (but of course not its consequence).

If I'm not mistaken, the definition of $m_j $ (D11) implies $\sum_j m_j = d$, leading to $\sum_i \delta_i^

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Nice use (and mention) of ChatGPT in research work :)

Hi Stergios, Mark and Joschka,

Thanks for the response! Empirically Tesseract does have polynomial scaling - here is a log-log plot showing that Tesseract has comparable runtime to belief propagation (without LSD) for SI1000 superdense color code circuits:

![Runtime of BP+LSD, BP, Teseract an

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Where do the default algorithmic scalings for quantum algorithms in your calculator come from? I cannot find any references for most of these in your paper, or in the tool itself. For example, the runtime for exact quantum chemistry calculations is listed simple as "n^5" and for quantum acceleration

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Hi Stergios,

Thanks for your reply! Glad to hear that you are planning to share the code soon.

Cheers,
Seok-Hyung

Hi Oscar. Thanks for your interest in our new decoder. We stand by our claim that VibeLSD is the first *practical* decoder for colour codes that brings performance on par with the surface code. We absolutely agree that there are more accurate decoders. However, these decoders prioritise accuracy at

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Congratulations on this very nice paper! It's very exciting to see BP-based decoding doing so well on color codes, and VibeLSD seems like a very useful and general decoder. I had a few comments/questions:

1) I wanted to point out the neural network decoding of the color code experiment in this pape

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Just to be perfectly clear, in case anyone is still confused: the main text of this article demonstrates that the "brilliant" experiment, in the form originally proposed and analyzed by Wang et al, (i) does not exhibit Bell violation with unentangled photons (contrary to its title); (ii) is perfectl

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Hi Seok-Hyung, thank you for your interest and questions.

1. BP scheduling: Thanks for your feedback on this! We will separate parallel and serial pseudo-code (i.e. two algorithms) in V2 of the paper to make this important point clearer.

2. Runtime Analysis: Our decoder has worst-case cubic

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Congrats on your paper! Really interesting results, and I'm very excited to see colour code performance finally reaching on par with surface codes.

I have a few minor questions.

1. It seems the current serial schedule algorithm in Appendix A appears to behave the same as the parallel schedule

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Hi Craig, I think John and I are describing the same procedure. If you replace the measurement in your circuit by a CNOT onto a fresh qubit, the resulting unitary will map |psi,0,0> to T|psi> \otimes |somefixedstate>. Therefore running the circuit in reverse will map |phi> \otimes |somefixedstate> t

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Congratulations on the new paper! I just wanted to point out earlier work have already defined Gowers norms for quantum states ([arxiv2408.06289][1], [arxiv2305.10277][2]), given properties of the Gowers-3 norm, and several papers have shown testing of stabilizer states via Gowers-3 norm of quantum

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You're missing that the final state of the measured qubits can be complex. For example, try inverting this T gate gadget and see if it still does a T gate: https://algassert.com/quirk#circuit=%7B%22cols%22%3A%5B%5B1%2C%22H%22%5D%2C%5B1%2C%22Z%5E%C2%BC%22%5D%2C%5B%22%E2%80%A2%22%2C%22X%22%5D%2C%5B1%2

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Best title of the year

Thank you for your interest Noah.
We used BP-OSD, which gives better LEPs than MWPM (we didn't include that comparison in the paper, but we obtained data with vanilla MWPM). We haven't compared correlated matching to BP-OSD. Maybe comparing with Tesseract would be a good comparison, that would rea

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