基于量子生成对抗网络的数据重构  

Data Reconstruction Based on Quantum Generative Adversarial Networks

作　　者：江奕达 王明明[1] JIANG Yida;WANG Mingming(School of Computer Science,Xi’an Polytechnic University,Xi’an 710048,China)

机构地区：[1]西安工程大学计算机科学学院,西安710048

出　　处：《计算机工程与应用》2024年第5期156-164,共9页Computer Engineering and Applications

基　　金：陕西省自然科学基础研究计划一般项目(面上)(2019JM-291)。

摘　　要：使用神经网络实现数据重构是人工智能领域一项十分重要的研究课题。生成对抗网络(generative adversarial network,GAN)作为近年来人工智能的热门算法,在完成数据重构任务中有较好的表现。量子计算作为一种能够加速经典计算的新型计算模式,正不断地与经典人工智能算法相融合。其中,量子生成对抗网络(quantum generative adversarial network,QGAN)在图像相关任务中具有良好的表现,但是量子模型的拟合能力还有待提高。故此,提出了一种基于GAN框架的量子-经典混合生成对抗网络(Q-CGAN)用于实现数据重构任务。该框架利用经典网络的非线性提高拟合效果,利用量子特性提供量子加速。使用MNIST手写数据集对比验证了量子模型和混合模型的重构效果,结果显示,Q-CGAN较纯量子生成器在数据重构过程中具有更好的表现。此外,还研究了混合模型中使用不同量子编码方案和不同参数化量子线路对数据重构效果的影响。Data reconstruction using neural networks is a very important research topic in the field of artificial intelli-gence.Generative adversarial network(GAN),as a popular algorithm of artificial intelligence in recent years,has a good performance in completing data reconstruction tasks.As a new computing mode that can accelerate classical computing,quantum computing is constantly merging with classical artificial intelligence algorithms.Among them,pure quantum generative adversarial network(QGAN)has a good performance in image related tasks.However,since the fitting ability in the quantum model still needs to be improved,this paper proposes a hybrid generative confrontation network(Q-CGAN)based on the GAN framework to realize the data reconstruction task.The framework exploits classical nonlineari-ties to improve fitting performance and quantum properties to provide quantum speedups.Using the MNIST handwritten data set to compare and verify the reconstruction effect of the hybrid model in this network,the results show that Q-CGAN has better performance in the data reconstruction process than pure quantum generators.In addition,the effect of using different quantum encoding schemes and different parameterized quantum circuits in the hybrid model on the data reconstruction effect is also studied.

关 键 词：量子计算 混合生成对抗网络 数据重构 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]