Progressive-Proximity Bit-Flipping for Decoding Surface Codes
CoRR(2024)
摘要
Topological quantum codes, such as toric and surface codes, are excellent
candidates for hardware implementation due to their robustness against errors
and their local interactions between qubits. However, decoding these codes
efficiently remains a challenge: existing decoders often fall short of meeting
requirements such as having low computational complexity (ideally linear in the
code's blocklength), low decoding latency, and low power consumption. In this
paper we propose a novel bit-flipping (BF) decoder tailored for toric and
surface codes. We introduce the proximity vector as a heuristic metric for
flipping bits, and we develop a new subroutine for correcting a particular
class of harmful degenerate errors. Our algorithm achieves linear complexity
growth and it can be efficiently implemented as it only involves simple
operations such as bit-wise additions, quasi-cyclic permutations and
vector-matrix multiplications. The proposed decoder shows a decoding threshold
of 7.5
binary symmetric channel.
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