发表机构
Parity Quantum Computing Germany GmbH; Parity Quantum Computing GmbH; University of Innsbruck（帕里特量子计算德国有限公司; 帕里特量子计算有限公司; 因斯布鲁克大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文为交换型自旋量子比特平台规划了从NISQ到容错时代的量子算法路线图，展示了Parity Twine编译方法及其原生错误检测技术的优势，并通过数字量子模拟提供资源估算，指导硬件设计。
AI 中文摘要
受近期基于交换型（EO）自旋量子比特的自旋量子处理单元开发突破的推动，我们为EO平台上量子算法的实现提供了路线图，涵盖从NISQ时代到容错时代。为了提供算法驱动的量子芯片扩展视角，我们考虑了一系列针对不同硬件成熟阶段的应用，并制定了成功实现的要求。我们表明，编译方法Parity Twine与硬件能力完美互补，可执行量子傅里叶变换或QAOA等任务。此外，我们描述了一种Parity Twine原生的错误检测技术，EO量子比特可以独特且有利的方式利用该技术来提高算法性能。最后，由于近期算法基准和长期视角都可以在数字量子模拟中找到，我们特别讨论了费米子快速傅里叶变换和Fermi-Hubbard模型的模拟。后者在量子纠错和部分容错实现的背景下被明确讨论。通过提供详细的资源估算并识别每个层面的扩展瓶颈，我们的工作为基于EO的量子计算提供了定量视角，并将为未来的硬件设计选择提供信息。
英文摘要
Motivated by recent breakthroughs in the development of spin-based quantum processing units based on exchange-only (EO) spin qubits, we provide a roadmap for the implementation of quantum algorithms on the EO platform, ranging from the NISQ to the fault-tolerant era. To provide an algorithm-driven perspective on the scaling of quantum chips, we consider a range of applications targeting different stages of hardware maturity and formulate requirements for a successful realization. We show that the compilation method Parity Twine perfectly complements the hardware's capabilities to perform tasks such as the quantum Fourier transform or QAOA. Furthermore, we describe an error detection technique native to Parity Twine, which EO qubits can leverage in a unique and advantageous way to improve algorithm performance. Finally, since both near-term algorithmic benchmarks and a long-term perspective can be found in digital quantum simulation, we specifically discuss the fermionic fast Fourier transform and the simulation of Fermi-Hubbard models. The latter is explicitly discussed in the context of quantum error correction and a partially fault-tolerant realization. By providing detailed resource estimates and identifying scaling bottlenecks on each level, our work offers a quantitative perspective on EO-based quantum computing and will inform future hardware design choices.
