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Large-scale quantum computers have the potential to hold computationalcapabilities beyond conventional computers for certain problems. However, thephysical qubits within a quantum computer are prone to noise and decoherence,which must be corrected in order to perform reliable, fault-tolerant quantumcomputations. Quantum Error Correction (QEC) provides the path for realizingsuch computations. QEC continuously generates a continuous stream of data thatdecoders must process at the rate it is received, which can be as fast as 1 MHzin superconducting quantum computers. A little known fact of QEC is that if thedecoder infrastructure cannot keep up, a data backlog problem is encounteredand the quantum computer runs exponentially slower. Today's leading approachesto quantum error correction are not scalable as existing decoders typically runslower as the problem size is increased, inevitably hitting the backlogproblem. That is: the current leading proposal for fault-tolerant quantumcomputation is not scalable. Here, we show how to parallelize decoding toachieve almost arbitrary speed, removing this roadblock to scalability. Ourparallelization requires some classical feed forward decisions to be delayed,leading to a slow-down of the logical clock speed. However, the slow-down isnow only polynomial in code size, averting the exponential slowdown. Wenumerically demonstrate our parallel decoder for the surface code, showing nonoticeable reduction in logical fidelity compared to previous decoders anddemonstrating the parallelization speedup.

Parallel window decoding enables scalable fault tolerant quantum computation