SBIR Phase I: Low-Density Logical Qubit Parity Coding

SBIR 第一阶段：低密度逻辑量子位奇偶校验编码

• 批准号: 2213187
• 负责人: Dennis Lucarelli
• 金额: $ 25.54万
• 依托单位: ERROR CORP.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213187&HistoricalAwards=false
• 关键词: SBIR; Phase; Low; Density; Logical

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to accelerate the adoption of error correction technologies in the quantum computing industry. It is widely held that quantum error correction will be critical to realize the potential of universal quantum computing. An error-corrected quantum computer holds promise for making transformational discoveries in science and engineering that will have broad impact across traditional technology sectors. By developing resource-efficient quantum error correction design and decoding software tools, this Phase I project aims to hasten the era of error-corrected quantum computing.This Small Business Innovation Research (SBIR) Phase I project will advance a new method for error syndrome extraction from a register of data qubits during the execution of an error-corrected quantum algorithm. In contrast to the standard approach to syndrome extraction, where each quantum codeword is treated independently, this new approach extracts error information from the entire quantum computer collectively. The algorithmic and cost advantage of the proposed approach is a reduction in the number of extra qubits required for error syndrome extraction. This project will focus on reducing the density of the quantum circuits used for syndrome extraction according to the new approach. Low-density quantum circuits are critical for robust quantum error correction since syndrome extraction is mediated by two-qubit entangling gates, which often have error rates higher than idling or memory errors occurring in the data qubits. Another objective of this Phase I project is to design low-density error correcting codes that promote locality in syndrome extraction. Local syndrome extraction is important for error correction in quantum processors that support limited connectivity between qubits. A final objective is to benchmark the proposed constructions and algorithms on simulated data and perform proof-of-concept experimental validation on cloud-based quantum computers.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.

小企业创新研究（SBIR）第一阶段项目的更广泛影响将是加速量子计算行业采用纠错技术。 人们普遍认为，量子纠错将是实现通用量子计算潜力的关键。 纠错量子计算机有望在科学和工程领域做出变革性的发现，这将对传统技术领域产生广泛影响。通过开发资源高效的量子纠错设计和解码软件工具，该第一阶段项目旨在加速纠错量子计算时代的到来。该小型企业创新研究（SBIR）第一阶段项目将提出一种新的方法，用于在执行纠错量子算法期间从数据量子位寄存器中提取错误伴随式。与标准的伴随式提取方法不同，在标准方法中，每个量子码字都被独立处理，这种新方法从整个量子计算机中集体提取错误信息。 所提出的方法的算法和成本优势是减少了错误伴随式提取所需的额外量子位的数量。该项目将专注于根据新方法降低用于症状提取的量子电路的密度。低密度量子电路对于稳健的量子纠错至关重要，因为伴随式提取是由两个量子比特纠缠门介导的，其错误率通常高于数据量子比特中发生的空闲或存储器错误。这个第一阶段项目的另一个目标是设计低密度的纠错码，促进本地化的综合征提取。局部伴随式提取对于支持量子比特之间的有限连接的量子处理器中的纠错是重要的。最终目标是在模拟数据上对拟议的结构和算法进行基准测试，并在基于云的量子计算机上进行概念验证实验验证。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。