NSF Convergence Accelerator Track C: A Toolkit for Solving Practical Materials Science Problems on Near-Term

NSF融合加速器支持以使用为灵感，以团队为基础，多学科的努力，解决国家重要性的挑战，并将在不久的将来产生对社会有价值的可交付成果。该项目旨在解决量子模拟的理论优势与现有量子硬件能力之间的差距。通过汇集跨部门团队，该项目将开发用于材料和化学问题的量子张量网络模拟技术。该项目旨在在霍尼韦尔量子解决方案公司正在开发的捕获离子量子计算系统上部署和演示这些技术。可交付成果包括一个全面的软件开发工具包，使其能够被多学科和跨部门的用户群使用。项目团队包括量子信息理论、计算材料和化学技术方面的学术研究人员，以及霍尼韦尔量子解决方案公司正在开发大规模高性能捕获离子量子计算系统的行业科学家。这个跨部门团队的目标是为“全息”量子算法开拓一套新的量子算法方法和软件工具。这些工具将利用张量网络状态表示提供的物理重要状态的有效压缩。霍尼韦尔的捕获离子量子计算机将实现选定量子比特的中路测量和复位（MCMR），以便尽可能有效地将量子比特应用于材料模拟的经典难题：表示电子相关性和纠缠。这些技术旨在减少处理大规模现实材料和化学模拟所需的量子比特数量和门的精度。该项目旨在缩小现实世界问题与近期量子硬件能力之间的差距。交付成果包括一个全面的MCMR算法开发工具包，该工具包与现有的材料科学、化学模拟包和量子编程框架紧密集成。该工具包将吸引广泛的用户和研究人员，以帮助进一步发展量子计算的技术和创新。将开发现场研讨会和会议，以及在线教育和培训材料，将这项工作传播给工业和学术工程师、化学家、材料科学家和软件开发人员的广泛受众。该奖项反映了美国国家科学基金会的法定使命，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。

The NSF Convergence Accelerator supports use-inspired, team-based, multidisciplinary efforts that address challenges of national importance and will produce deliverables of value to society in the near future. This project seeks to address the gap between the theoretical advantages of quantum simulations and the capabilities of existing quantum hardware. By bringing together a cross-sector team, the project will develop quantum tensor network simulation techniques for materials and chemistry problems. The project aims to deploy and demonstrate these techniques on trapped ion quantum computing systems being developed at Honeywell Quantum Solutions. Deliverables include a comprehensive software development toolkit that will enable its use by a multi-disciplinary and cross-sector user base. The project team includes academic researchers in quantum information theory computational materials and chemistry techniques along with industry scientists at Honeywell Quantum Solutions who are developing large-scale high-performance trapped-ion quantum computing systems. The cross-sector team will aim to pioneer a new suite of quantum algorithm methods and software tools for “holographic” quantum-algorithms. These tools will exploit efficient compression of physically important states afforded by tensor-network state representations. Mid-circuit measurement and reset (MCMR) of selected qubits will be enabled by Honeywell’s trapped ion quantum computers in order to apply qubits as efficiently as possible towards the classically hard aspect of materials simulation: representing electronic correlations and entanglement. These techniques aim to reduce the number of qubits and accuracy of gates required to tackle large-scale realistic materials and chemistry simulations. This project seeks to narrow the gap between real-world problems and the capabilities of near-term quantum hardware. Deliverables include a comprehensive MCMR algorithm development toolkit that is tightly integrated with existing material science, chemistry simulation packages, and quantum programming frameworks. This toolkit will engage a broad user- and researcher- base to aid in the further development of techniques and innovations in quantum computing. In-person workshops and conferences, and online education and training materials will be developed to disseminate this work to a broad audience of industry and academic engineers, chemists, materials scientists, and software developers.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.