Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes
APA
Liu, Y. (2019). Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes. Perimeter Institute. https://pirsa.org/19070031
MLA
Liu, Yehua. Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes. Perimeter Institute, Jul. 11, 2019, https://pirsa.org/19070031
BibTex
@misc{ pirsa_PIRSA:19070031, doi = {10.48660/19070031}, url = {https://pirsa.org/19070031}, author = {Liu, Yehua}, keywords = {Condensed Matter}, language = {en}, title = {Neural Belief-Propagation Decoders for Quantum Error-Correcting Codes}, publisher = {Perimeter Institute}, year = {2019}, month = {jul}, note = {PIRSA:19070031 see, \url{https://pirsa.org}} }
University of Sherbrooke
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Abstract
Belief-propagation (BP) decoders are responsible for the success of many modern coding schemes. While many classical coding schemes have been generalized to the quantum setting, the corresponding BP decoders are flawed by design in this setting. Inspired by an exact mapping between BP and deep neural networks, we train neural BP decoders for quantum low-density parity-check codes, with a loss function tailored for the quantum setting. Training substantially improves the performance of the original BP decoders. The flexibility and adaptability of the neural BP decoders make them suitable for low-overhead error correction in near-term quantum devices.
Reference: arXiv:1811.07835 (to appear in PRL)