Recent comments from SciRate

Māris Ozols Nov 16 2020 08:56 UTC

Maybe tone down the "epidemiology" bit in the abstract or substantiate it somewhere in the paper? You don't want some popular science journalist to draw the wrong conclusions.

Junyu Liu Nov 15 2020 06:47 UTC

It is my first time to see that a paper in quantum finance is using the JHEP style latex preprint.

Noon van der Silk Nov 13 2020 06:23 UTC

Thanks for Angelo for reporting this on github - https://github.com/scirate/scirate/issues/396 - it's the font! Great discovery.

Ruslan Shaydulin Nov 12 2020 14:36 UTC

Wow what an awesome random bug tantan
(confirmed in Safari 14.0 on macOS 10.15.7)

Anthony Polloreno Nov 11 2020 20:59 UTC

Scirate question - why does `tantan` render as tantan (a smiley face in my browser)?

Ryan Babbush Nov 10 2020 19:48 UTC

Thanks for the comment! Indeed, part of our motivation for writing this perspective was to provoke the community into describing ways of implementing quadratic speedup algorithms that might defy this analysis. But if I understand your suggestion correctly I do not think it would work. Usually the "c

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Ruslan Shaydulin Nov 10 2020 14:53 UTC

Great perspective. One wonders if some kind of hybridization is possible, where at each step the classical logic primitive is computed on a classical computer based on information obtained via partial measurement and the result fed into the quantum algorithm. E.g. for optimization, the value of the

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Jiayu Zhang Nov 10 2020 06:04 UTC

Dear all who are interested in this paper:
This paper has gone through significant rewrites in this half a year and recently and hopefully is more understandable than previous versions. The most suggested talk so far can be found in https://www.youtube.com/watch?v=PqGwYDeBvQU&feature=youtu.be which

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Hsin-Yuan Huang Nov 06 2020 17:40 UTC

A tutorial on Tensorflow Quantum [https://www.tensorflow.org/quantum/tutorials/quantum_data][1] provides an implementation of the numerical experiments.

It shows how classical and quantum ML models can both easily achieve near-zero training error but the quantum model can generalize better on eng

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Angelo Lucia Nov 03 2020 18:56 UTC

The referenced paper is https://scirate.com/arxiv/2004.01469

Mark M. Wilde Oct 22 2020 17:51 UTC

This is a strong and interesting result for the resource theory of thermodynamics and the resource theory of asymmetric distinguishability. I send my congrats to the authors.

Blake Stacey Oct 02 2020 00:44 UTC

Yes, it certainly *seems* like the operational argument (at the end of section IV.A) would apply to Bohmian mechanics.

Jerry Finkelstein Oct 01 2020 19:24 UTC

In this paper, there is an operational argument in support of the assumption which is labeled P3 (that the two-time probability is a linear function of the quantum state). One might have supposed that this argument would apply equally-well to Bohmian mechanics; however, (as noted in the paper), a

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Simon Apers Sep 29 2020 19:36 UTC

A nice perspective by one of the authors: [https://mycqstate.wordpress.com/2020/09/29/it-happens-to-everyonebut-its-not-fun/](https://mycqstate.wordpress.com/2020/09/29/it-happens-to-everyonebut-its-not-fun/)

Johannes Bausch Sep 23 2020 11:56 UTC

Or, shamelessly advertising myself here, "Recurrent Quantum Neural Networks", http://arxiv.org/abs/2006.14619 (2020)

quantum_hn Sep 18 2020 13:18 UTC

At the bottom of p. 2 the authors comment "However, the problem of learning sequential data, to our best knowledge, has not been investigated in the quantum domain."

However, with the ubiquity of modern search engines, it would not have taken too much effort to find that in fact there have been s

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C. Jess Riedel Sep 15 2020 19:25 UTC

Thanks!

Weilei Zeng Sep 15 2020 17:40 UTC

They actually work by copying and pasting, but the embedded URLs leads to the wrong places.

Weilei Zeng Sep 15 2020 17:37 UTC

Interesting result. Just as a feedback, the two google links on Page 4 are not available.

Anthony Leverrier Sep 10 2020 13:23 UTC

Ah yes! Thanks for the explanation.

Matt Hastings Sep 10 2020 12:58 UTC

Glad you like it! I must admit, we also thought it was N^{5/8} for a while. But, I think N^{3/5} is indeed what follows from balancing. Though, if we miss something, please let us know so we can get that extra 0.025 power in the exponent.

Ignoring polylogs, one has distances N^{1/2} and N^{3/4

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Anthony Leverrier Sep 10 2020 11:55 UTC

Amazing! Unless I'm missing something, the distance should even be $N^{5/8}$ instead of $N^{3/5}$, unless the balancing trick (or the final weight reduction) causes the expected distance to decrease.

Namit Anand Sep 10 2020 05:30 UTC

Yes, please do post it here if you find something interesting -- you're also welcome to just send me an email! Also, thanks for pointing to its role as a biodiversity measure -- I never would have found that (in fact, they use the entire family of Rényi entropies).

Blake Stacey Sep 10 2020 03:09 UTC

Thanks for the reply!

The first time I encountered a quantity of the form $\sum_i p(i)^2$ was in the context of Rényi entropy, and then as a [biodiversity measure](https://www.maths.ed.ac.uk/~tl/mdiss.pdf), so it defintely does appear under many names! I'll look around for earlier references conn

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Namit Anand Sep 08 2020 18:05 UTC

Hi Blake, thanks for the comment. In fact, the connection between $l_2$-norm of coherence and participation ratio was already used in a previous paper by a subset of the authors: https://arxiv.org/abs/1906.09242; see Appendix C (where it is implicitly used). But for some reason, we had forgotten to

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Blake Stacey Sep 08 2020 17:28 UTC

In Eq. (5), the authors state that given a pure state and a basis, the second moment of the probabilities for that state measured in that basis is equal to 1 minus the [$l_2$-norm of coherence](https://arxiv.org/abs/1311.0275), and they say that "To the best of our knowledge", they make that connect

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Gil Kalai Aug 28 2020 06:13 UTC

Victory asked if my theory does not contradict the (excellent) paper "Quantum advantage with noisy shallow circuits in 3D" by Sergey Bravyi, David Gosset, Robert Koenig, and Marco Tomamichel (BGKT).

This is a good question.

The crucial point is that my theory excludes the ability of NISQ s

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Junyu Liu Aug 26 2020 12:35 UTC

I like the title of this paper! It is very cyberpunkian!

Giacomo Nannicini Aug 24 2020 19:55 UTC

Thanks for the very detailed comments, this was extremely helpful.

I posted a revision based on your suggestions. Let me remark that this introduction is meant for non-physicists that may not be comfortable with the more traditional approach.

Victory Omole Aug 13 2020 06:30 UTC

> The computational complexity class describing NISQ circuits is LDP (low-degree polynomial) and
this class is contained in the familiar class of distributions that can be approximated by bounded-depth
(classical) computation.
) Distributions that can be (approximately) described by bounded-degre

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Matt Mercer Aug 12 2020 02:17 UTC

Belief Propagation was invented by Judea Pearl for Bayesian Networks, not Tensor Networks.
Guiffre Vidal's first paper (2005) where he uses the term “Tensor Networks” https://arxiv.org/abs/quant-ph/0511070

First paper (1997) to use Quantum Bayesian Networks in quantum computing
https://arxiv.or

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Blake Stacey Aug 11 2020 23:06 UTC

I've had some notes about a mild generalization of Proposition III.4 sitting around since about the time this appeared. Since I don't seem to be doing anything else with them, I figured I might as well post them here.

For an arbitrary square-free integer $n \geq 2$, we can find a dimension $d \ge

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Yichen Huang Aug 04 2020 02:48 UTC

After several rounds of negotiations with arXiv moderators, the addendum is accepted by arXiv and appears today:

https://scirate.com/arxiv/2008.00944

I would like to thank arXiv moderators for reviewing my case and understanding the situation.

Yichen Huang Aug 03 2020 07:37 UTC

Thanks for your suggestion, but there is a reason why in this case I prefer a separate submission to an update.

The addendum is related to [arxiv:1912.03645]. Note that most readers only look at the latest updated version while remembering the submission date of the original version. If I update my

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Marco Tomamichel Aug 03 2020 00:32 UTC

The common thing people do is to simply update the arXiv submission. As arXiv keeps old versions stored, this seems a clean way to include an addendum.

Yichen Huang Jul 29 2020 05:32 UTC

I posted an addendum today:

https://vixra.org/abs/2007.0215

It is very unfortunate that the policy of arXiv does not allow an addendum as a separate submission so that I have to post it elsewhere. I am adding this comment here in order to advertise the addendum, for few people keep an eye on viXra

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Yuxuan Du Jul 28 2020 14:26 UTC

Hi William, thanks for your comment. Please refer to Appendix I for the discussion about the more general settings beyond depolarization noise.

William J. Huggins Jul 27 2020 18:01 UTC

What are the conditions for the results regarding noisy learning to break down when you go beyond depolarizing noise?

Ryan Babbush Jul 21 2020 03:51 UTC

This paper points out that it is unlikely that quantum resources will accelerate the convergence of the Hartree-Fock procedure. This timely analysis seems prompted by Google’s recent experimental demonstration of Hartree-Fock on a quantum computer ([arXiv:2004.04174][1]). But in case there is any do

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Sam Jaques Jul 17 2020 13:07 UTC

Do you have a reference/reason for k-local gates to have cost proportional to k?

Alex Wozniakowski Jul 14 2020 13:44 UTC

The [repository][1], which contains the code for this paper, is now available open-source.

[1]: https://github.com/a-wozniakowski/scikit-physlearn

Blake Stacey Jul 14 2020 03:14 UTC

Discussions of this paper have transpired [here](https://golem.ph.utexas.edu/category/2020/06/getting_to_the_bottom_of_noeth.html) and [here](https://johncarlosbaez.wordpress.com/2020/06/29/noethers-theorem-2/).

Mankei Tsang Jul 10 2020 14:36 UTC

The arXiv admin fixed it! The PDF should now work.

Mankei Tsang Jul 10 2020 05:46 UTC

arXiv is somehow unable to produce a PDF, but the postscript version https://arxiv.org/ps/2007.04849 is fine. Will try to fix.

Alexander Jahn Jul 03 2020 13:04 UTC

Beautiful illustrations. A simplified version of this would make for a wonderful undergrad homework problem, I think.

Blake Stacey Jul 02 2020 00:10 UTC

Eq. (1) defines a qubit SIC, for whatever that's worth.

Blake Stacey Jul 01 2020 02:07 UTC

If the initial state is $|\psi\rangle$ and the possible post-transition states are $|\phi_i\rangle$, then unitary transformations will leave invariant the [3-vertex Bargmann invariants](https://arxiv.org/abs/quant-ph/0107006) $\langle \psi | \phi_i \rangle\langle \phi_i | \phi_j \rangle \langle \phi

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Māris Ozols Jun 30 2020 14:47 UTC

This "paper" needs more likes! :D

Thomas Klimpel Jun 28 2020 19:13 UTC

Initially I thought that non-contextuality could be derived from invariance under unitary transformations, but that is wrong. If a set of orthonormal states is given as possible states after the transition, then their scalar products with the initial state remain unchanged under unitary transformati

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Jerry Finkelstein Jun 28 2020 17:45 UTC

The assumptions that the transition probabilities are unchanged by unitary transformations, and that they must vanish for orthogonal states, are rather substantive assumptions. There is also the implicit assumption that they are non-contextual (since the notation which is used requires that transit

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