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Quantum snakes on a plane: mobile, low-dimensional logical qubits on a 2D surface

Abstract:

Recent demonstrations indicate that silicon-spin quantum processing unit will be able to shuttle physical qubits rapidly and with high fidelity—a desirable feature for maximizing logical connectivity, supporting new codes, and routing around damage. However it may seem that shuttling at the logical level is unwise: static defects in the device may “scratch” a logical qubit as it passes, causing correlated errors to which the code is highly vulnerable. Here we explore an architecture where logical qubits are 1D strings (“snakes”) which can be moved freely over a planar latticework. Possible scratch events are inferred via monitor qubits and the complementary gap; if deemed a risk, remarkably the shuttle process can be undone in a way that negates any corruption. This leads to high levels of tolerance against shuttling-related imperfections and enables logical operations between snakes by a semitransversal method. We conclude that this approach is suitable for fault-tolerant computing in both near-term and long-term, mature-era silicon devices.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1103/494s-jd8h

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Materials
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Materials
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Materials
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author


More from this funder
Funder identifier:
https://ror.org/001aqnf71
Grant:
MR/Y015843/1
More from this funder
Funder identifier:
https://ror.org/0439y7842
Grant:
EP/Y004655/1


Publisher:
American Physical Society
Journal:
PRX Quantum More from this journal
Volume:
7
Article number:
010339
Publication date:
2026-02-25
Acceptance date:
2025-12-17
DOI:
EISSN:
2691-3399


Language:
English
Pubs id:
2365189
UUID:
uuid_efaa6cb4-1f3b-441b-9d6f-b23b22441094
Local pid:
pubs:2365189
Source identifiers:
W4417439749
Deposit date:
2026-01-30
ARK identifier:

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