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APS -APS March Meeting 2017 - Event - A Hybrid Classical/Quantum Approach for Large-Scale Studies of Quantum Systems with Density Matrix Embedding Theory

机译:APS -APS 2017年3月会议-活动-使用密度矩阵嵌入理论对量子系统进行大规模研究的经典/量子混合方法

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Determining ground state energies of quantum systems by hybrid classical/quantum methods has emerged as a promising candidate application for near-term quantum computational resources. Short of large-scale fault-tolerant quantum computers, small-scale devices can be leveraged with current computational techniques to identify important subspaces of relatively large Hamiltonians. Inspired by the work that described the merging of dynamical mean-field theory (DMFT) with a small-scale quantum computational resource as an impurity solver~[Bauer et al., arXiv:1510.03859v2], we describe an alternative embedding scheme, density matrix embedding theory (DMET), that naturally fits with the output from the variational quantum eigensolver and other hybrid approaches. This approach is validated using a quantum abstract machine simulator~[Smith~et al., arXiv:1608.03355] that reproduces the ground state energy of the Hubbard model converged to the infinite limit. We comment on the implementation of this algorithm in near-term superconducting processors.
机译:通过混合经典/量子方法确定量子系统的基态能量已经成为近期量子计算资源的有希望的候选应用。缺少大型容错量子计算机,小型设备可以利用当前的计算技术来识别相对较大的哈密顿量的重要子空间。受描述动态均场理论(DMFT)与小规模量子计算资源作为杂质求解器的合并的工作的启发,[Bauer等人,arXiv:1510.03859v2],我们描述了另一种嵌入方案,密度矩阵嵌入理论(DMET),自然适合变分量子本征求解器和其他混合方法的输出。使用量子抽象机器模拟器[Smithet al。,arXiv:1608.03355]验证了该方法,该模拟器再现了收敛至无限极限的哈伯德模型的基态能量。我们评论了该算法在近期超导处理器中的实现。

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