魔法态培育的实际代价
The practical cost of magic state cultivation
- Harvard University（哈佛大学）
- Massachusetts Institute of Technology（麻省理工学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究提出开放边界后选择方法Caliper，仅用非破坏性中途综合征信息，在无噪声横向测量不可用时显著提升魔法态培育效率，并揭示实际约束下的资源权衡。
AI中文摘要：
魔法态培育是一种很有前景的方法，用于制备高保真度的非克利福德资源态——这是容错量子计算的核心组成部分——且具有较低的空间时间开销。在基准测试培育过程时，现有的资源估算假设能够对输出的魔法态进行无噪声的横向测量，以便在培育过程的最终逃逸阶段进行后选择。然而，这样的测量会破坏魔法态，因此在计算过程中不可用。我们开发了一种开放边界后选择方法，称为Caliper，它仅使用非破坏性的中途综合征信息，并且在这些约束条件下显著优于现有方法。在某些情况下，我们的后选择方法独特地恢复了先前估算的资源效率。然而，在其他情况下，我们观察到了权衡。在先前工作中报告的空间时间成本下，可实现的逻辑错误率可能高出几个数量级，而恢复所报告的逻辑错误率则需要明显更大的码和更长的逃逸阶段。我们的结果强调了涉及中途后选择的实际考虑如何影响魔法态培育协议的设计和性能。
英文摘要：
Magic state cultivation is a promising method for preparing high-fidelity non-Clifford resource states - a central component of fault-tolerant quantum computing - with low spacetime overhead. In benchmarking cultivation, existing resource estimates assume access to noiseless transversal measurement of the output magic state to allow for postselection during the final escape stage of the cultivation process. However, such measurements would destroy the magic state and are therefore unavailable during computation. We develop an open-boundary postselection method, Caliper, that uses only nondestructive mid-circuit syndrome information and substantially outperforms existing methods operating under these constraints. In some regimes, our postselection method uniquely recovers the resource efficiency of prior estimates. However, in other cases, we observe a tradeoff. At spacetime costs reported in previous works, the achievable logical error rates can be orders of magnitude higher, and recovering the reported logical error rate requires substantially larger codes and longer escape stages. Our results highlight how practical considerations involving mid-circuit postselection can impact the design and performance of magic state cultivation protocols.
