I heard some people delete 100+ author papers from their Google scholar to be more in line with their own work.

Huge thanks to @joeytindall.bsky.social. I had a great time working with him during my 4-month stay at the Flatiron Institute in New York. This guy is amazing!

A big thank you also to @mstoud.bsky.social for having me.

@flatironinstitute.org @simonsfoundation.org

Particularly interesting to us was witnessing how slowly loop correlations build up in heavy-hex processors. Loop correlations are what make loopy networks potentially significantly harder to use than loop-free MPS and tree-tensor networks.

We also introduce a bunch of metrics to certify that the samples are of high-quality. This way, we verified that we solved the biggest circuit in IBM's recent quantum chemistry experiment to numerical precision.

We combine some existing ideas with ITensorNetworks.jl and @joeytindall.bsky.social's flexible boundary MPS code to adapt to any planar geometry.

With our open-source (but not completely polished) software, you can start simulating and sampling 2D circuits today: github.com/JoeyT1994/Te...

Big congrats to @carrasqu.bsky.social's group at @ethz.ch, including Yuxuan Zhang and Roeland Wiersema, and particularly Matteo D'Anna for his amazing first-author work early in his PhD.

Oh no, haha. My bad and thanks!

I don't see any reason why not every circuit executed on hardware should be compressed. The approach can also be used to re-compile into a different gate set or topology.

Classical simulation is not just here to compete with quantum devices.

I'm surprised Grover's is on here. Maybe not for database search but as a form of amplitude amplification?

Sorry 🤐

This paper was meant to go live yesterday (still love you arXiv), but who doesn't scroll social media on a holiday 💁

Thanks to my amazing group and co-authors Tyson Jones, Yanting Teng (@yteng.bsky.social), Armando Angrisani (@aangrisani.bsky.social), and Zoë Holmes (@qzoeholmes.bsky.social)!

Pauli propagation is naturally interfaced with both quantum computers and other classical simulation methods - the perfect team player!

I love improving classical algorithms for simulating quantum computations, and I truly believe performant classical methods are good for everyone.

In VERY short:

- PP is a recent path integral method that is orthogonal to e.g. tensor networks.
- PP evolves objects that are sparse Pauli basis, commonly observables in the Heisenberg picture.
- PP is amazing for quick estimates in low-ish Magic quantum systems.
- PP is hard to converge exactly.

This "compact" 30-page main text manuscript summarizes much of what we have learned about Pauli propagation (PP) and where its strengths lie.

From the general framework description, over theoretical guarantees, to the nitty-gritty implementation details that you are happy to not have to deal with.

Here the general link to UnitaryHACK: unitaryhack.dev

Here the link to our project page: unitaryhack.dev/projects/pau...

And keep your eyes peeled for tomorrow 👁️👁️

And precisely at that time with a specific approach.

What do you mean by "spoofing"? When I say that I mean that something was a cheap or fake result that looks real. However, at least the TN results are from actual converging simulations (I can't confidently speak of the other EPFL one (shame on me)).