论文标题
量子 - 最佳控制启发的ANSATZ,用于变异量子算法
Quantum-optimal-control-inspired ansatz for variational quantum algorithms
论文作者
论文摘要
变异量子算法(VQA)的一个中心分量是状态预先准备回路,也称为ANSATZ或变异形式。该电路最常见的是尊重哈密顿量问题的对称性,并以这种方式将变异搜索限制为感兴趣的子空间。在这里,我们表明,通过引入结合对称性的单位者的Ansätze,这种方法并不总是有利的。我们称这类Ansätze被称为量子 - 最佳控制启发的Ansätze(Qoca),灵感来自量子最佳控制理论,并导致VQA的改善对某些重要问题的收敛性。的确,我们在半填充上对流行的Ansätze进行了基准测试,以填充Fermi-Hubbard模型,并表明我们的变异电路可以以更高的精度和较大的系统近似于该模型的基态。我们还展示了如何使用Qoca来找到水分子的基态,并将ANSATZ的性能与用于化学问题的其他常见选择进行比较。这项工作构成了开发更一般的对称性破坏Ansätze的第一步,并应用了物理和化学问题。
A central component of variational quantum algorithms (VQA) is the state-preparation circuit, also known as ansatz or variational form. This circuit is most commonly designed to respect the symmetries of the problem Hamiltonian and, in this way, constrain the variational search to a subspace of interest. Here, we show that this approach is not always advantageous by introducing ansätze that incorporate symmetry-breaking unitaries. This class of ansätze, that we call Quantum-Optimal-Control-inspired Ansätze (QOCA), is inspired by the theory of quantum optimal control and leads to an improved convergence of VQAs for some important problems. Indeed, we benchmark QOCA against popular ansätze applied to the Fermi-Hubbard model at half-filling and show that our variational circuits can approximate the ground state of this model with significantly higher accuracy and for larger systems. We also show how QOCA can be used to find the ground state of the water molecule and compare the performance of our ansatz against other common choices used for chemistry problems. This work constitutes a first step towards the development of a more general class of symmetry-breaking ansätze with applications to physics and chemistry problems.