【摘 要】
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Quantum error-correction codes are immeasurable resources for quantum computing and quantum communication.However,the existing decoders are generally incapable of checking node duplication of belief propagation (BP) on quantum low-density parity check (QL
【机 构】
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School of Sciences,Qingdao University of Technology,Qingdao 266033,China
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Quantum error-correction codes are immeasurable resources for quantum computing and quantum communication.However,the existing decoders are generally incapable of checking node duplication of belief propagation (BP) on quantum low-density parity check (QLDPC) codes.Based on the probability theory in the machine learning,mathematical statistics and topological structure,a GF(4) (the Galois field is abbreviated as GF) augmented model BP decoder with Tanner graph is designed.The problem of repeated check nodes can be solved by this decoder.In simulation,when the random perturbation strength p =0.0115-0.0116 and number of attempts N =60-70,the highest decoding efficiency of the augmented model BP decoder is obtained,and the low-loss frame error rate (FER) decreases to 7.1975 × 10-5.Hence,we design a novel augmented model decoder to compare the relationship between GF(2) and GF(4) for quantum code[[450,200]]on the depolarization channel.It can be verified that the proposed decoder provides the widely application range,and the decoding performance is better in QLDPC codes.
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