๐คญ aw shucks... (Cheque's in the mail ๐)
@christopherchubb.com
Mathematical physicist and quantum info theorist (big pile of qubits thinking about other qubits). ๐ฆ๐บโก๐ด๓ ฃ๓ ก๓ ฑ๓ ฃ๓ ฟโก๐จ๐ญโก๐ฆ๐บ, he/they, ๐งฆ๐๐ฐ๐ฅ๐ณ๏ธโ๐โ๐ฅ๐
๐คญ aw shucks... (Cheque's in the mail ๐)
Shout out to @joerenes.bsky.social and Christophe Piveteau (who did all the work ๐).
Paper available at: arxiv.org/abs/2310.10722
Code available at: github.com/ChriPiv/tnde... Thanks!
While the circuit-level results are still at the proof-of-principle stage, we hope performance can be significantly improved in future work. To give you a sense of the difficult, here is the eldritch horror that is the TN which corresponds to d=5 circuit-level noise
As well as improvements in the thresholds, we see significant improvements in the logical error rates for all four setups considered.
Going to 3D TNs allow us to decode 3D codes such as the 3D surface code. It also lets us decode noisy 2D codes, such as the toric code under phenomenological noise, or even full-on circuit-level noise. For all but circuit noise, our decoder gives state-of-the-art thresholds.
In this paper we show how to extend the tensor network decoding techniques I developed in my last paper to 3D. The core of this is an extension of the sweep-line contraction scheme to 3D. See this thread for an explanation of the previous 2D approach twitter.com/QuantumChubb...
Do you want to correct a quantum code? Do you like tensor networks? Do you live in 3D? Well I have the paper for you! scirate.com/arxiv/2310.1...
Preparing quantum info lecture notes Broke: Handwritten Woke: LaTeX Bespoke: [picture of Mike and Ike scented crayons]
350,757 Flips, author ordering by how many coins they flipped.
arxiv.org/abs/2310.04153
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