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Time-Efficient Constant-Space-Overhead Fault-Tolerant Quantum Computation

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arxiv 2207.08826 v3 pith:2GTYELNX submitted 2022-07-18 quant-ph

classification quant-ph
keywords quantumoverheadprotocolspacecodesconstant-space-overheadfault-toleranttime
verification ladder T0 review T1 audit T2 compute T3 formal
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Scaling up quantum computers to attain substantial speedups over classical computing requires fault tolerance. Conventionally, protocols for fault-tolerant quantum computation demand excessive space overheads by using many physical qubits for each logical qubit. A more recent protocol using quantum analogues of low-density parity-check codes needs only a constant space overhead that does not grow with the number of logical qubits. However, the overhead in the processing time required to implement this protocol grows polynomially with the number of computational steps. To address these problems, here we introduce an alternative approach to constant-space-overhead fault-tolerant quantum computing using a concatenation of multiple small-size quantum codes rather than a single large-size quantum low-density parity-check code. We develop techniques for concatenating different quantum Hamming codes with growing sizes. As a result, we construct a low-overhead protocol to achieve constant space overhead and only quasi-polylogarithmic time overhead simultaneously. Our protocol is fault tolerant even if a decoder has a non-constant runtime, unlike the existing constant-space-overhead protocol. This code concatenation approach will make possible a large class of quantum speedups within feasibly bounded space overhead yet negligibly short time overhead.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A distillation-teleportation protocol for fault-tolerant QRAM

    quant-ph 2025-05 accept novelty 8.0 of 10

    An adaptive distillation-teleportation protocol implements a fault-tolerant QRAM query with poly(n) quantum resources and 1/poly(n) device fidelity, at the cost of an exponential classical dataset update each round.

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