Quantum cloud platforms remain fundamentally non-virtualised: despite rapid hardware scaling, each user program still monopolises an entire quantum processor, preventing resource sharing, economic scalability, and quality-of-service differentiation. Existing Quantum Virtual Machine (QVM) designs attempt spatial multiplexing through topology-specific or template-based partitioning, but these approaches are brittle under hardware heterogeneity, calibration drift, and transient defects, which dominate real quantum devices. We present DynQ, the first dynamic, topology-agnostic Quantum Virtual Machine that virtualises quantum hardware using quality-weighted community detection. Instead of imposing fixed geometric regions, DynQ models a quantum processor as a weighted graph derived from live calibration data and automatically discovers execution regions that maximise internal gate quality while minimising inter-region coupling. This operationalises the classical virtualisation principle of high cohesion and low coupling in a quantum-native setting, producing execution regions that are connectivity-efficient, noise-aware, and resilient to crosstalk and defects. We evaluate DynQ across five IBM Quantum backends using calibration-derived noise simulation and on two production devices, comparing against state-of-the-art QVM and standard compilation baselines. On hardware with pronounced spatial quality variation, DynQ achieves up to 19.1 percent higher fidelity and 45.1 percent lower output error. When transient hardware defects cause baseline executions to fail completely, DynQ adapts dynamically and achieves over 86 percent fidelity. By transforming calibrated device graphs into adaptive virtual hardware abstractions, DynQ decouples quantum programs from fragile physical layouts and enables reliable, high-utilisation quantum cloud services.

翻译：量子云平台本质上仍缺乏虚拟化能力：尽管硬件规模迅速扩大，但每个用户程序仍独占整个量子处理器，阻碍了资源共享、经济可扩展性和服务质量差异化。现有的量子虚拟机设计试图通过拓扑特定或基于模板的分区实现空间复用，但这些方法在硬件异构性、校准漂移和瞬时缺陷（这些是真实量子设备的主要特征）面前显得脆弱。我们提出了DynQ，首个动态、拓扑无关的量子虚拟机，它利用质量加权社区检测技术实现量子硬件虚拟化。DynQ不强制划分固定几何区域，而是将量子处理器建模为基于实时校准数据生成的加权图，并自动发现能最大化内部门质量同时最小化区域间耦合的执行区域。这将在量子原生环境中实现了经典虚拟化的高内聚、低耦合原则，所产生的执行区域具有连接高效性、噪声感知能力，并能抵抗串扰和缺陷。我们在五个IBM Quantum后端上使用基于校准的噪声仿真进行评估，并在两台生产设备上进行了测试，与最先进的量子虚拟机及标准编译基线进行了比较。在空间质量差异显著的硬件上，DynQ实现了高达19.1%的保真度提升和45.1%的输出误差降低。当瞬时硬件缺陷导致基线执行完全失败时，DynQ能动态适应并实现超过86%的保真度。通过将校准后的设备图转化为自适应的虚拟硬件抽象，DynQ使量子程序与脆弱的物理布局解耦，为实现可靠、高利用率的量子云服务提供了可能。