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The error rates of quantum devices are orders of magnitude higher than what is needed to run most quantum applications. To close this gap, Quantum Error Correction (QEC) encodes logical qubits and distributes information using several physical qubits. By periodically executing a syndrome extraction circuit on the logical qubits, information about errors (called syndrome) is extracted while running programs. A decoder uses these syndromes to identify and correct errors in real time, which is required to use feedback implemented in quantum algorithms. Unfortunately, software decoders are slow and hardware decoders are fast but less accurate. Thus, almost all QEC studies so far have relied on offline decoding. To enable real-time decoding in near-term QEC, we propose LILLIPUT-- a Lightweight Low Latency Look-Up Table decoder. LILLIPUT consists of two parts-- First, it translates syndromes into error detection events that index into a Look-Up Table (LUT) whose entry provides the error information in real-time. Second, it programs the LUTs with error assignments for all possible error events by running a software decoder offline. LILLIPUT tolerates an error on any operation in the quantum hardware, including gates and measurement, and the number of tolerated errors grows with the size of the code. It needs <7% logic on off-the-shelf FPGAs that allows it to be easily integrated alongside the control and readout circuits in existing systems. LILLIPUT incurs a latency of few nanoseconds and enables real-time decoding. We also propose Compressed LUTs (CLUTs) to reduce the memory needed by LILLIPUT. By exploiting the fact that not all error events are equally likely and only storing data for the most probable error events, CLUTs reduce the memory needed by up-to 107x (from 148 MB to 1.38 MB) without degrading accuracy.

Scalable quantum computing can become a reality with error correction, provided coherent qubits can be constructed in large arrays. The key premise is that physical errors can remain both small and sufficiently uncorrelated as devices scale, so that logical error rates can be exponentially suppressed. However, energetic impacts from cosmic rays and latent radioactivity violate both of these assumptions. An impinging particle ionizes the substrate, radiating high energy phonons that induce a burst of quasiparticles, destroying qubit coherence throughout the device. High-energy radiation has been identified as a source of error in pilot superconducting quantum devices, but lacking a measurement technique able to resolve a single event in detail, the effect on large scale algorithms and error correction in particular remains an open question. Elucidating the physics involved requires operating large numbers of qubits at the same rapid timescales as in error correction, exposing the event's evolution in time and spread in space. Here, we directly observe high-energy rays impacting a large-scale quantum processor. We introduce a rapid space and time-multiplexed measurement method and identify large bursts of quasiparticles that simultaneously and severely limit the energy coherence of all qubits, causing chip-wide failure. We track the events from their initial localised impact to high error rates across the chip. Our results provide direct insights into the scale and dynamics of these damaging error bursts in large-scale devices, and highlight the necessity of mitigation to enable quantum computing to scale.