玻色量子联手阿里云，开启量子算力新时代

维科网云计算观察01-13

维科网云计算观察玻色量子携手阿里云，将1000计算量子比特的实用化量子算力面向全球开放，开启中国专用量子计算普惠新时代。北京玻色量子科技有限公司的 1000 计算量子比特云服务正式登陆阿里云市场，成为中国量子计算发展史上的一个关键节点。图源：AI 云咨询这意味着全球开发者和企业现在可以通过中国最大的公有云平台，直接调用达到实用化门槛的量子算力。中国专用量子计算正式迈入千比特规模化实用新阶段，从“...

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云咨询这意味着全球开发者和企业现在可以通过中国最大的公有云平台，直接调用达到实用化门槛的量子算力。中国专用量子计算正式迈入千比特规模化实用新阶段，从“实验室设备”转变为数字经济基础设施。量子比特数量是衡量量子算力的关键指标。目前大多数量子计算机硬件的物理量子比特数量处于 200 到 500 之间，经过纠错获得的能用于计算的逻辑量子比特仅有数十个。当可用于计算的量子比特数低于 500 时，量子算法无法有效处理高复杂度的AI模型；达到 1000 这个数量门槛后，量子计算机才有可能求解大范围梯度优化、AI模型训练等实用化问题。玻色量子的突破不仅体现在量子比特数量上。其相干光量子计算机的耦合精度达到 int8，首次超越全球首家量子计算机商业供应商 D-Wave（耦合精度为int5）。玻色量子创始人兼 CEO 文凯表示，这种端到端的服务模式降低了量子计算的使用门槛，1000 计算量子比特云服务最快端到端时间低于 60 秒。量智融合量子计算与人工智能的融合正在创造新的可能性。2025 年 8 月，玻色量子发布了自研的量子玻尔兹曼机及开源编程套件 KPP，这是“量智融合”的重要里程碑。图源：AI 云咨询这一成果与 2024 年诺贝尔物理学奖密切相关，该奖项授予了神经网络先驱、玻尔兹曼机的提出者杰弗里·辛顿。玻尔兹曼机作为一种基于统计物理的能量模型，能够学习数据概率分布并生成新样本，奠定了深度学习的基础。基于传统 GPU 硬件框架训练玻尔兹曼机时，其核心采样过程的 NP-Hard 特性导致模型训练难以实现。而玻色量子的相干光量子计算机利用光量子搭建物理 Ising 模型，凭借量子并行特性可高效处理玻尔兹曼分布采样，在训练速度上实现指数级加速。在生物制药领域，量子计算与 AI 的融合已展现出实际价值。玻色量子研究团队借助相干光量子计算机的玻尔兹曼采样能力，快速学习蛋白序列的进化学信息，捕捉精确的氨基酸互作关系。基于量子玻尔兹曼机，玻色量子联合相关单位开发了蛋白质结构预测量子算法，高效求解 Potts 模型的同时精确预测蛋白氨基酸残基接触图，在 100 结点的数据集上实现收敛。云服务降低量子计算使用门槛量子计算云服务的推出，从根本上改变了量子计算的获取方式。通过阿里云平台，量子计算资源变得像传统云计算资源一样易于获取，大大降低了使用门槛。玻色量子 1000 计算量子比特云服务支持多设备互联、集群计算，能够处理大量的高复杂性且大规模的计算任务，为未来量子计算集群的应用奠定了坚实基础。图源：新华网该服务还可提供 CPQC-X 服务，支持深度战略合作用户提交大于 1000 量子比特的计算任务，开启了定制化量子计算服务的新模式。随着政企、科研工作者、量子算法开发者等用户的不断增加，玻色量子平台调用求解次数累计超过6800万次，覆盖院校超过 900 所，参与研发的开发者人数超过 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