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.

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University of Texas Austin
United States
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