CryoZip: An Efficient Cryogenic Compressor for Quantum Error Correction Syndromes
For quantum computing systems, CryoZip addresses the bandwidth and power bottleneck at the cryogenic interface, enabling scalable fault-tolerant quantum error correction.
CryoZip is a cryogenic compression framework that reduces syndrome transmission bandwidth from 4 K to room temperature by up to 48x, achieving 1.8x higher compression than state-of-the-art and 4-26x energy savings under realistic noise.
Scaling fault tolerant quantum computing is increasingly constrained by the limited bandwidth and power budget across the 4 K to room temperature (RT) interface. We present CryoZip, a cross stack cryogenic compression framework that cooperates with a lightweight cryogenic quantum error correction (QEC) predecoder to reduce 4 K to RT syndrome transmission under realistic, circuit level noise. CryoZip targets sparse syndrome vectors with a sliding window compression architecture sized under strict decoding latency constraints to maximize energy efficiency. We implement and evaluate the design in 22 nm FDSOI characterized at 4 K, using vector based power, performance, and area analysis to obtain realistic hardware data. CryoZip achieves up to 48x compression, 1.8x higher than state of the art compressors, across various QEC codes while delivering 4 to 26x energy savings. When paired with a QEC predecoder, it yields over 14,238x bandwidth reduction, while energy savings rise to 42x when accounting for realistic QEC interface overheads.