Alfonso Dominic, Avramidis Benjamin, Paudel Hari P, Duan Yuhua
National Energy Technology Laboratory, U. S. Department of Energy, Pittsburgh, PA 15236, USA.
NETL Support Contractor, 626 Cochran Mill Road, Pittsburgh, PA 15236, USA.
Nanomaterials (Basel). 2024 Jul 29;14(15):1267. doi: 10.3390/nano14151267.
Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available number of physical qubits with high fidelity limit its application to small chemical systems. This work employed a quantum-classical framework which features a quantum active space-embedding approach to perform simulations of chemical reactions that require up to 14 qubits. This framework was applied to prototypical example metal hydrogenation reactions: the coupling between hydrogen and Li, Li, and Li clusters. Particular attention was paid to the computation of barriers and reaction energies. The predicted reaction profiles compare well with advanced classical quantum chemistry methods, demonstrating the potential of the quantum embedding algorithm to map out reaction profiles of realistic gas-phase chemical reactions to ascertain qualitative energetic trends. Additionally, the predicted potential energy curves provide a benchmark to compare against both current and future quantum embedding approaches.
量子计算以新颖的方式利用量子力学原理来解决传统量子化学方法无法准确处理的复杂化学问题。然而,高计算成本和具有高保真度的物理量子比特的可用数量限制了其在小型化学系统中的应用。这项工作采用了一种量子-经典框架,该框架具有量子活性空间嵌入方法,用于对需要多达14个量子比特的化学反应进行模拟。该框架被应用于典型的金属氢化反应示例:氢与锂、锂和锂簇之间的耦合。特别关注了势垒和反应能量的计算。预测的反应剖面图与先进的经典量子化学方法相比表现良好,证明了量子嵌入算法在绘制实际气相化学反应的反应剖面图以确定定性能量趋势方面的潜力。此外,预测的势能曲线为比较当前和未来的量子嵌入方法提供了一个基准。