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Paper 1

High-throughput GPU layered decoder of quasi-cyclic multi-edge type low density parity check codes in continuous-variable quantum key distribution systems

Yang Li, Xiaofang Zhang, Yong Li, Bingjie Xu, Li Ma, Jie Yang, Wei Huang

Year

2020

Journal

Scientific Reports

DOI

10.1038/s41598-020-71534-5

arXiv

-

Abstract The decoding throughput during post-processing is one of the major bottlenecks that occur in a continuous-variable quantum key distribution (CV-QKD) system. In this paper, we propose a layered decoder to decode quasi-cyclic multi-edge type LDPC (QC-MET-LDPC) codes using a graphics processing unit (GPU) in continuous-variable quantum key distribution (CV-QKD) systems. As described herein, we optimize the storage methods related to the parity check matrix, merge the sub-matrices which are unrelated, and decode multiple codewords in parallel on the GPU. Simulation results demonstrate that the average decoding speed of LDPC codes with three typical code rates, i.e., 0.1, 0.05 and 0.02, is up to 64.11 Mbits/s, 48.65 Mbits/s and 39.51 Mbits/s, respectively, when decoding 128 codewords of length $${10}^{{6}}$$ 10 6 simultaneously without early termination.

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Paper 2

Quantum optimization with arbitrary connectivity using Rydberg atom arrays

Minh-Thi Nguyen, Jin-Guo Liu, Jonathan Wurtz, Mikhail D. Lukin, Sheng-Tao Wang, Hannes Pichler

Year

2022

Journal

arXiv preprint

DOI

arXiv:2209.03965

arXiv

2209.03965

Programmable quantum systems based on Rydberg atom arrays have recently been used for hardware-efficient tests of quantum optimization algorithms [Ebadi et al., Science, 376, 1209 (2022)] with hundreds of qubits. In particular, the maximum independent set problem on so-called unit-disk graphs, was shown to be efficiently encodable in such a quantum system. Here, we extend the classes of problems that can be efficiently encoded in Rydberg arrays by constructing explicit mappings from a wide class of problems to maximum weighted independent set problems on unit-disk graphs, with at most a quadratic overhead in the number of qubits. We analyze several examples, including: maximum weighted independent set on graphs with arbitrary connectivity, quadratic unconstrained binary optimization problems with arbitrary or restricted connectivity, and integer factorization. Numerical simulations on small system sizes indicate that the adiabatic time scale for solving the mapped problems is strongly correlated with that of the original problems. Our work provides a blueprint for using Rydberg atom arrays to solve a wide range of combinatorial optimization problems with arbitrary connectivity, beyond the restrictions imposed by the hardware geometry.

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