量子信息科学材料：在量子演进2.0中的作用
Materials for Quantum Information Science: Roles in the Quantum Evolution 2.0
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- Virginia Tech（弗吉尼亚理工大学）
- Virginia Tech National Security Institute（弗吉尼亚理工学院国家安全研究所）
- Northwestern University（西北大学）
- University of Maryland, College Park（马里兰大学帕克分校）
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中文总结 AI 辅助
量子信息科学进入量子演进2.0，材料成为核心挑战。本文综述各平台退相干机制与表征方法，揭示共同结构-相干性问题，并提出机理理解、高通量指标和表征工具三大需求。
中文摘要 AI 辅助
量子信息科学正进入第二阶段，即量子演进2.0，其挑战已从展示对单个量子态的相干控制转向构建可扩展的多量子比特处理器和网络。这一转变使材料科学成为该领域的核心。在超导电路、量子缺陷、量子光子器件以及新兴材料平台（包括二维材料和异质结构）中，性能现在更多地受限于控制不佳的表面、埋藏界面和原子身份尚未完全知晓的缺陷，而非器件设计。本综述调查了这些量子平台的材料挑战以及解决这些挑战所需的表征方法。对于每个平台，我们确定了主要的退相干机制、材料理解的现状以及最紧迫的开放材料问题。跨平台比较随后揭示了一个共同的结构-相干性问题。所涉及的材料化学在各平台间反复出现，涉及无序或埋藏环境中的轻元素，但没有任何平台能够将特定的原子尺度结构与测量的相干性变化定量联系起来。最后，我们指出了三个需求：原子层面退相干的机理理解、可预测器件性能的高通量代理指标，以及为量子材料构建的表征工具，解决这些问题将推动所有平台的相干性、可扩展性和集成性进步。
英文摘要
Quantum information science is entering a second phase, the Quantum Evolution 2.0, in which the challenge has shifted from demonstrating coherent control of individual quantum states to building scalable multi-qubit processors and networks. This transition places materials science at the center of the field. Across superconducting circuits, quantum defects, quantum photonic devices, and emerging materials platforms, including two-dimensional materials and heterostructures, performance is now limited less by device design than by poorly controlled surfaces, buried interfaces, and defects whose atomic identities remain incompletely known. This review surveys the materials challenges of these quantum platforms together with the characterization methods needed to resolve them. For each platform we identify the dominant decoherence mechanisms, the current state of materials understanding, and the most pressing open materials problems. A cross-platform comparison then reveals a shared structure-coherence problem. The implicated material chemistry recurs across platforms, involving light elements in disordered or buried environments, yet no platform can quantitatively connect a specific atomic-scale structure to a measured change in coherence. We close by identifying three needs, mechanistic understanding of decoherence at the atomistic level, high-throughput proxy metrics predictive of device performance, and characterization tools built for quantum materials, whose resolution would advance coherence, scalability, and integration across all platforms.
