Quantum color code projection decoding method combined with Q neural network

Abstract

The invention relates to the technical field of machine learning, in particular to a quantum color code projection decoding method combined with a Q neural network. Comprising the steps of initializing a color code, training a neural network decoder, decoding the color code by adopting quantum topological coding and the like. The color code decoder designed and trained by machine learning is high in prediction speed, and the problems that a traditional color code decoding algorithm is low in speed and low in accuracy are solved; a color code is mapped to a surface code by using a projection method, and translation invariance of the surface code is fully utilized during decoding, so that state space representation is greatly simplified, the influence of the number of defects is avoided, and the method is better combined with a deep neural network DQN; when facing various noise models, the network structure can be quickly adjusted by means of machine learning to adapt to the various noise models; the decoding scheme is relatively simple in flow, can meet the decoding requirements of various occasions on color codes, and can quickly construct a set of proper decoders.

Description

technical field [0001] The invention relates to the technical field of machine learning, in particular, to a projection decoding method of quantum color code combined with Q neural network. Background technique [0002] In recent years, the research results of machine learning have become more and more mature, and it has a wide range of applications in biology, image recognition, artificial intelligence and other fields. Machine learning involves many disciplines such as probability theory, statistics, approximation theory, convex analysis, algorithmic complexity theory, etc. The results in these disciplines are applied to various problems, enabling automatic learning of the internal structure of data and data analysis. . [0003] The development of quantum computing and quantum information has produced many new algorithms and applications. In order to successfully run quantum algorithms in future quantum computers, it is necessary to ensure the accuracy of qubits, resulti...

AI Technical Summary

Problems solved by technology

However, there is currently no technology that can combine neural networks for projection decoding of quantum color codes. In view of this, we propose a projection decoding method for quantum color codes combined with Q neural networks

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