As standard data loading processes, quantum state preparation and block-encoding are critical and necessary processes for quantum computing applications, including quantum machine learning, Hamiltonian simulation, and many others. Yet, existing protocols suffer from poor robustness under device imperfection, thus limiting their practicality for real-world applications. Here, this limitation is overcome based on a fanin process designed in a tree-like bucket-brigade architecture. It suppresses the error propagation between different branches, thus exponentially improving the robustness compared to existing depth-optimal methods. Moreover, the approach here simultaneously achieves the state-of-the-art fault-tolerant circuit depth, gate count, and STA. As an example of application, we show that for quantum simulation of geometrically local Hamiltonian, the code distance of each logic qubit can potentially be reduced exponentially using our technique. We believe that our technique can significantly enhance the power of quantum computing in the near-term and fault-tolerant regimes.

翻译：作为标准的数据加载过程，量子态制备与块编码是量子计算应用（包括量子机器学习、哈密顿量模拟等）中关键且必要的步骤。然而，现有协议在器件缺陷下鲁棒性较差，从而限制了其在实际应用中的可行性。本文基于树状桶链架构中设计的扇入过程克服了这一局限。该方法抑制了不同分支间的误差传播，与现有深度最优方法相比，鲁棒性呈指数级提升。此外，本文方法同时实现了最先进的容错电路深度、门数量及STA指标。作为应用示例，我们证明在几何局部哈密顿量的量子模拟中，使用本技术可使每个逻辑量子位的码距实现指数级潜在缩减。我们相信，该技术将显著增强近期及容错体系下量子计算的能力。