戴万阳

教授 (博导、重要学科岗)
单位:南京大学数学学院
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量子计算区块链国际工业革命论坛 理事长
江苏大数据区块链与智能信息专委会 主任
江苏省概率 统计学会    理事长
江苏金融科技研究中心 特邀专家
国际《人工智能与机器学习》杂志  主审
国际《无线电工程与技术》 主审



人工智能区块链为基石的量子计算与量子芯片:建模、容错与容量调度


  • 论文发表信息


  • 英文摘要

      We model the hardware and software architecture for generalized Internet of Things (IoT) by quantum cloud-computing and blockchain. To reduce the measurement error and increase the efficiency of quantum entanglement (i.e., the capability of fault tolerance) in the current quantum computers and communications, we design a quantum-computing chip by modeling it as a multi-input multi-output (MIMO) quantum channel and obtain its channel capacity via our recently derived mutual information formula. To capture the internal qubit data flow dynamics of the channel, we model it via a deep convolutional neural network (DCNN) with generalized stochastic pooling in terms of resource-competition among different quantum eigenmodes or users. The pooling is corresponding to a resource allocation policy with two levels of competitions as in cognitive radio: the first one is on users' selection in a ``win-lose" manner; the second one is on resource-sharing among selected users in a ``win-win" manner. To wit, our scheduling policy is the one by mixing a saddle point to a zero-sum game problem and a Pareto optimal Nash equilibrium point to a non-zero-sum game problem. The effectiveness of our policy is proved by diffusion modeling with theory and numerical examples.

  • 中文摘要

      大数据、人工智能、区块链、物联网等的核心技术是(量子)云计算及将来量子云互联网的计算效率问题, 它们是第四次工业革命向第五次第六次工业革命演化的关键技术。因而,我们通过量子云计算与区块链对广 义物联网的硬件体系与软件结构进行了归一化建模,得到其一般化共性模式。为了降低现行量子计算机与量 子通信中的测量误差及提高它们系统中量子纠缠效率与容错能力,我们通过多进多出(MIMO)量子信道建模 设计出了归一化的量子计算芯片并通过我们近期导出的非高斯互熵公式得到其信道容量。为了捕捉量子信道 内部量子比特数据流的动态演化规律并针对不同量子本征模式或用户之间对系统的资源竞争,我们通过具有 广义随机池深度卷积学习神经网络的人工智能系统对此进行建模。进一步地,我们所涉及的广义随机池与具 有两层竞争的资源配置策略及认知无线电相对应: 第一层是以输赢为目的零和博奕选择层,其决策点是其 鞍点;第二层是赢者之间的非零和博奕利益共享层,其决策点是其全局利益最优Pareto纳什均衡点同时兼顾 了赢者之间利益的公平性。最后,通过扩散逼近论证与数值模拟证明了我们所设计策略的有效性。

  • 关键词

      Quantum-computing modeling, blockchain, fault tolerance, capacity scheduling, queueing network, Internet of Things (IoT), cognitive radio, artificial intelligence (AI), deep convolutional neural network (DCNN)

  • IEEE等国际会议特邀大会嘉宾主旨报告(Keynote Speeches)

    • 该文中的主要学术成就作为特邀大会嘉宾主旨报告在IEEE及其它国际会议上报告。
    • The main results in the paper are presented as invited keynote talks in IEEE and other international conferences.




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