Collaborative Research: FET: Medium: Design and Implementation of Quantum Databases

合作研究：FET：媒介：量子数据库的设计和实现

• 批准号: 2312754
• 负责人: Yongshan Ding
• 金额: $ 60万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2312754&HistoricalAwards=false
• 关键词: Collaborative; Research; FET; Medium; Design

Quantum systems can in principle store and process data faster than conventional digital systems. Achieving such speedup in practice, however, is often hindered by the difficulties in: (i) quickly accessing data in quantum superposition, and (ii) reliably manipulating quantum data in the presence of high error rates inherent in quantum devices. Current technologies designed for quantum processing units (QPUs) lack this interface to access data at scale, also known as the quantum I/O bottleneck. This effort develops the systems architecture for quantum databases (QDBs) that provide crucial data input for QPUs to process efficiently and reliably. Building on recent significant progress in quantum random access memory (QRAM) technologies, the program identifies the key software and hardware advances needed to translate proof-of-principle demonstrations into viable, scalable platforms.At the core of the envisioned quantum database (QDB) systems is the development of QRAM architectures that allow low-latency and high-fidelity queries. The investigators of this program study the hardware and software requirements for functional, fault-tolerant QRAM architectures, develop simulation and benchmarking tools, and present new algorithms enabled by QDBs. An extensive set of education and outreach activities is included in the program to foster the growth of future quantum computing workforce and promote a deeper understanding of the potential and limitations of quantum memory and databases.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

原则上，量子系统可以比传统数字系统更快地存储和处理数据。然而，在实践中实现这种加速通常会受到以下困难的阻碍：（i）快速访问量子叠加中的数据，以及（ii）在量子设备固有的高错误率存在的情况下可靠地操纵量子数据。当前为量子处理单元 (QPU) 设计的技术缺乏大规模访问数据的接口，也称为量子 I/O 瓶颈。这项工作开发了量子数据库 (QDB) 的系统架构，为 QPU 提供关键的数据输入，以实现高效、可靠的处理。该计划以量子随机存取存储器（QRAM）技术最近取得的重大进展为基础，确定了将原理验证演示转化为可行的可扩展平台所需的关键软件和硬件进步。作为设想的量子数据库（QDB）的核心Systems 是 QRAM 架构的开发，允许低延迟和高保真查询。该项目的研究人员研究功能性、容错 QRAM 架构的硬件和软件要求，开发模拟和基准测试工具，并提出由 QDB 支持的新算法。该计划包括一系列广泛的教育和推广活动，以促进未来量子计算劳动力的增长，并促进对量子存储器和数据库的潜力和局限性的更深入了解。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来提供支持。