首页|Quantum Neural Network for Quantum Neural Computing
Quantum Neural Network for Quantum Neural Computing
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
万方数据
Neural networks have achieved impressive breakthroughs in both industry and academia.How to effectively develop neural networks on quantum computing devices is a challenging open problem.Here,we propose a new quantum neural network model for quantum neural computing using(classically controlled)single-qubit operations and measurements on real-world quantum systems with naturally occurring environment-induced decoherence,which greatly reduces the difficulties of physical implementations.Our model circumvents the problem that the state-space size grows exponentially with the number of neurons,thereby greatly reducing memory requirements and allowing for fast optimization with traditional optimization algorithms.We benchmark our model for handwritten digit recognition and other nonlinear classification tasks.The results show that our model has an amazing nonlinear classification ability and robustness to noise.Furthermore,our model allows quantum computing to be applied in a wider context and inspires the earlier development of a quantum neural computer than standard quantum computers.
National Laboratory of Solid State Microstructures,School of Physics,Collaborative Innovation Center of Advanced Microstructures,Nanjing University,Nanjing 210093,China
MatricTime Digital Technology Co.Ltd.,Nanjing 211899,China
国家自然科学基金江苏省自然科学基金中央高校基本科研业务费专项Key Research and Development Program of Nanjing Jiangbei New AeraProgram for Innovative Talents and Entrepreneurs in Jiangsu
NETL
NSTL
万方数据
