Silva Thais L, Taddei Márcio M, Carrazza Stefano, Aolita Leandro
Quantum Research Centre, Technology Innovation Institute, Abu Dhabi, UAE.
Federal University of Rio de Janeiro, Caixa Postal 68528, Rio de Janeiro, RJ, 21941-972, Brazil.
Sci Rep. 2023 Oct 25;13(1):18258. doi: 10.1038/s41598-023-45540-2.
Simulating quantum imaginary-time evolution (QITE) is a significant promise of quantum computation. However, the known algorithms are either probabilistic (repeat until success) with unpractically small success probabilities or coherent (quantum amplitude amplification) with circuit depths and ancillary-qubit numbers unrealistically large in the mid-term. Our main contribution is a new generation of deterministic, high-precision QITE algorithms that are significantly more amenable experimentally. A surprisingly simple idea is behind them: partitioning the evolution into a sequence of fragments that are run probabilistically. It causes a considerable reduction in wasted circuit depth every time a run fails. Remarkably, the resulting overall runtime is asymptotically better than in coherent approaches, and the hardware requirements are even milder than in probabilistic ones. Our findings are especially relevant for the early fault-tolerance stages of quantum hardware.
模拟量子虚时演化(QITE)是量子计算的一个重大前景。然而,现有的算法要么是概率性的(重复直到成功),成功概率小到不切实际,要么是相干性的(量子幅度放大),在中期电路深度和辅助量子比特数大到不切实际。我们的主要贡献是新一代确定性、高精度的QITE算法,这些算法在实验上更易于实现。其背后是一个惊人的简单想法:将演化划分为一系列以概率方式运行的片段。每次运行失败时,这会导致浪费的电路深度大幅减少。值得注意的是,由此产生的总体运行时间在渐近意义上比相干方法更好,并且硬件要求甚至比概率性方法更宽松。我们的发现对于量子硬件的早期容错阶段尤为重要。