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We also propose Compressed LUTs (CLUTs) to reduce the memory needed by LILLIPUT.
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LILLIPUT incurs a latency of few nanoseconds and enables real-time decoding. 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 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.
Experimental quantum error correction software#
Second, it programs the LUTs with error assignments for all possible error events by running a software decoder offline. 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. To enable real-time decoding in near-term QEC, we propose LILLIPUT- a Lightweight Low Latency Look-Up Table decoder. Thus, almost all QEC studies so far have relied on offline decoding. Unfortunately, software decoders are slow and hardware decoders are fast but less accurate. A decoder uses these syndromes to identify and correct errors in real time, which is required to use feedback implemented in quantum algorithms. By periodically executing a syndrome extraction circuit on the logical qubits, information about errors (called syndrome) is extracted while running programs. To close this gap, Quantum Error Correction (QEC) encodes logical qubits and distributes information using several physical qubits. The error rates of quantum devices are orders of magnitude higher than what is needed to run most quantum applications.