Cerasoli Frank T, Sherbert Kyle, Sławińska Jagoda, Buongiorno Nardelli Marco
Department of Physics, University of North Texas, Denton, TX 76203, USA.
Phys Chem Chem Phys. 2020 Oct 7;22(38):21816-21822. doi: 10.1039/d0cp04008h.
Development of quantum architectures during the last decade has inspired hybrid classical-quantum algorithms in physics and quantum chemistry that promise simulations of fermionic systems beyond the capability of modern classical computers, even before the era of quantum computing fully arrives. Strong research efforts have been recently made to obtain minimal depth quantum circuits which could accurately represent chemical systems. Here, we show that unprecedented methods used in quantum chemistry, designed to simulate molecules on quantum processors, can be extended to calculate properties of periodic solids. In particular, we present minimal depth circuits implementing the variational quantum eigensolver algorithm and successfully use it to compute the band structure of silicon on a quantum machine for the first time. We are convinced that the presented quantum experiments performed on cloud-based platforms will stimulate more intense studies towards scalable electronic structure computation of advanced quantum materials.
过去十年量子架构的发展激发了物理和量子化学领域的混合经典-量子算法,这些算法有望在量子计算时代完全到来之前,实现对费米子系统的模拟,而这超出了现代经典计算机的能力范围。最近,人们为获得能够精确表示化学系统的最小深度量子电路付出了巨大的研究努力。在此,我们表明,量子化学中用于在量子处理器上模拟分子的前所未有的方法,可以扩展到计算周期性固体的性质。特别是,我们展示了实现变分量子本征求解器算法的最小深度电路,并首次成功地在量子计算机上使用它来计算硅的能带结构。我们相信,在基于云的平台上进行的这些量子实验将激发对先进量子材料可扩展电子结构计算的更深入研究。