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、以团队为基础的多学科努力，以应对国家重要性的挑战，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。通过汇集一个跨部门的团队，该项目将开发材料和化学问题的量子张量网络模拟技术。该项目旨在霍尼韦尔量子解决方案公司正在开发的囚禁离子量子计算系统上部署和演示这些技术。交付成果包括一个综合的软件开发工具包，使多学科和跨部门的用户能够使用它。该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的行业科学家，他们正在开发大规模高性能囚禁离子量子计算系统。这个跨部门的团队将致力于开创一套新的量子算法方法和软件工具，用于“全息”量子算法。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。霍尼韦尔的囚禁离子量子计算机将实现对选定量子比特的电路中测量和重置(MCMR)，以便尽可能有效地将量子比特应用于材料模拟的经典困难方面：表示电子关联和纠缠。这些技术旨在减少处理大规模逼真材料和化学模拟所需的量子比特数量和门的精度。该项目寻求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。这个工具包将吸引广泛的用户和研究人员基础，以帮助量子计算技术和创新的进一步发展。将开发面对面的研讨会和会议，以及在线教育和培训材料，以向工业界和学术界的工程师、化学家、材料科学家和软件开发人员广泛传播这项工作。该奖项反映了NSF的法定使命，并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，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.