Quantum computing promises to tackle technological and industrial problems insurmountable for classical computers. However, today's quantum computers still have limited demonstrable functionality, and it is expected that scaling up to millions of qubits is required for them to live up to this touted promise. The feasible route in achieving practical quantum advantage goals is to implement a hybrid operational mode that realizes the cohesion of quantum and classical computers. Here we present a hybrid quantum cloud based on a memory-centric and heterogeneous multiprocessing architecture, integrated into a high-performance computing data center grade environment. We demonstrate that utilizing the quantum cloud, our hybrid quantum algorithms including Quantum Encoding (QuEnc), Hybrid Quantum Neural Networks and Tensor Networks enable advantages in optimization, machine learning, and simulation fields. We show the advantage of hybrid algorithms compared to standard classical algorithms in both the computational speed and quality of the solution. The achieved advance in hybrid quantum hardware and software makes quantum computing useful in practice today.
翻译:量子计算有望解决古典计算机无法克服的技术和工业问题。 然而,今天的量子计算机仍然具有有限的可证明的功能,而且预计需要将量子扩大至数百万平方位,才能实现这一承诺。实现实际量子优势目标的可行途径是实施混合操作模式,实现量子计算机和古典计算机的凝聚力。在这里,我们展示了基于内存中心、多式多处理结构的混合量子云,并融入高性能计算数据中心等级环境。我们证明利用量子云、我们混合量子算法,包括Quantum Encoding(QuEnc)、混合量子网络和Tensor网络,在优化、机器学习和模拟领域带来了优势。我们展示了混合算速和质量与标准经典算法相比的优势。在混合量子硬件和软件的推进使量子计算在今天的实际操作中有用。