论文标题
Tetris-Adapt-VQE：一种自适应算法，可产生较浅的，较差的Ansätze
TETRIS-ADAPT-VQE: An adaptive algorithm that yields shallower, denser circuit ansätze
论文作者
论文摘要
自适应量子变量算法对于在近期量子硬件上模拟强相关的系统尤其有希望，但在很大程度上，由于当前设备的严重相干时间限制，它们尚不可行。在这项工作中，我们介绍了一种称为Tetris-Adapt-VQE的算法，该算法迭代地构建了一个差异ansätze，一次是少数运算符，以模拟的问题决定。该算法是Autapt-VQE算法的修改版本，其中抬高单个操作器 - 允许在每次迭代中添加具有不相交的支持的多个操作员。俄罗斯俄罗斯 - 适应-VQE导致更密集，但电路显着，而没有增加CNOT门或变化参数的数量。就电路深度而言，它比原始算法的优势随系统尺寸而增加。此外，与Adapt-VQE相比，在每次迭代时在每次迭代中相对于每个迭代中的每个候选统一的能量梯度的昂贵步骤。这些改进使我们更接近证明在量子硬件上具有实用量子优势的目标。
Adaptive quantum variational algorithms are particularly promising for simulating strongly correlated systems on near-term quantum hardware, but they are not yet viable due, in large part, to the severe coherence time limitations on current devices. In this work, we introduce an algorithm called TETRIS-ADAPT-VQE, which iteratively builds up variational ansätze a few operators at a time in a way dictated by the problem being simulated. This algorithm is a modified version of the ADAPT-VQE algorithm in which the one-operator-at-a-time rule is lifted to allow for the addition of multiple operators with disjoint supports in each iteration. TETRIS-ADAPT-VQE results in denser but significantly shallower circuits, without increasing the number of CNOT gates or variational parameters. Its advantage over the original algorithm in terms of circuit depths increases with the system size. Moreover, the expensive step of measuring the energy gradient with respect to each candidate unitary at each iteration is performed only a fraction of the time compared to ADAPT-VQE. These improvements bring us closer to the goal of demonstrating a practical quantum advantage on quantum hardware.
