论文标题
费米 - 哈伯德模型的压缩变分量子质量
Compressed variational quantum eigensolver for the Fermi-Hubbard model
论文作者
论文摘要
Fermi-Hubbard模型是一个合理的目标，可以使用量子本质量算法来通过量子计算机解决。但是，问题大小超出了经典的精确对角线化的范围，这也超出了当前量子计算硬件的范围。在这里，我们使用一种简单的方法，该方法压缩了哈伯德模型的第一个非平凡子案例（带有一个旋转和一个旋转的费米昂），可以使用当前的量子计算硬件来解决较大的实例。我们在$ 2 \ times 1 $ Hubbard模型的情况下，在超导量子硬件平台上实现此方法，包括误差缓解技术，并表明基态的精度相对较高。
The Fermi-Hubbard model is a plausible target to be solved by a quantum computer using the variational quantum eigensolver algorithm. However, problem sizes beyond the reach of classical exact diagonalisation are also beyond the reach of current quantum computing hardware. Here we use a simple method which compresses the first nontrivial subcase of the Hubbard model -- with one spin-up and one spin-down fermion -- enabling larger instances to be addressed using current quantum computing hardware. We implement this method on a superconducting quantum hardware platform for the case of the $2 \times 1$ Hubbard model, including error-mitigation techniques, and show that the ground state is found with relatively high accuracy.
