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arXiv 2210.02403quant-ph
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第二量子化中周期固体的量子计算

Quantum Computation for Periodic Solids in Second Quantization

Aleksei V. Ivanov, Christoph Sünderhauf, Nicole Holzmann, Tom Ellaby, Rachel N. Kerber, Glenn Jones, Joan Camps

AI总结:

提出基于第二量子化稀疏量子化的量子算法,用于周期固体基态能量计算,利用Wannier函数降低资源需求,估算NiO和PdO需约10^10-10^12个T门及3×10^8物理量子比特。

摘要:

在这项工作中,我们提出了一种用于在纠错量子计算机上计算周期固体基态能量的量子算法。该算法基于第二量子化中的稀疏量子化方法,并针对Bloch和Wannier基组开发。我们表明,Wannier函数相对于Bloch函数所需的计算资源更少,因为:(i)哈密顿量的L$_1$范数显著更低,(ii)可以利用Wannier函数的平移对称性来减少必须加载到量子计算机中的经典数据量。我们估算了该量子算法对于NiO和PdO等周期固体的资源需求。这些过渡金属氧化物因其催化性质而在工业上具有相关性。我们发现,使用200--900个自旋轨道近似的哈密顿量的基态能量估计需要约$10{}^{10}$--$10^{12}$个T门,并且在物理错误率为$0.1\\%$时,需要多达$3\cdot10^8$个物理量子比特。

英文摘要:

In this work, we present a quantum algorithm for ground-state energy calculations of periodic solids on error-corrected quantum computers. The algorithm is based on the sparse qubitization approach in second quantization and developed for Bloch and Wannier basis sets. We show that Wannier functions require less computational resources with respect to Bloch functions because: (i) the L$_1$ norm of the Hamiltonian is considerably lower and (ii) the translational symmetry of Wannier functions can be exploited in order to reduce the amount of classical data that must be loaded into the quantum computer. The resource requirements of the quantum algorithm are estimated for periodic solids such as NiO and PdO. These transition metal oxides are industrially relevant for their catalytic properties. We find that ground-state energy estimation of Hamiltonians approximated using 200--900 spin orbitals requires {\it ca.}~$10{}^{10}$--$10^{12}$ T gates and up to $3\cdot10^8$ physical qubits for a physical error rate of $0.1\%$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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