论文标题
为NISQ设备及其他
Making Trotterization adaptive and energy-self-correcting for NISQ devices and beyond
论文作者
论文摘要
连续时间演变的模拟需要在经典计算机和量子计算机上分配时间。较好的时间步骤提高了模拟精度,但不可避免地会导致计算工作的增加。对于当今嘈杂的中间量表量子计算机而言,这尤其昂贵,其中值得注意的门不完美限制了可以以给定精度执行的电路深度。经典的自适应求解器已发达以节省数值计算时间。但是,通过自适应时间步骤最佳使用可用的量子资源仍然是一个重要的挑战。在这里,我们介绍了一种量子算法来解决此问题,从而提供了局部可观察物的量子多体动力学的控制解决方案。我们算法的关键概念元素是一个反馈循环,通过调整时间步骤来自我校正模拟错误,从而在基本级别上显着超过常规的猪trot虫方案并降低电路深度。它甚至允许受控的渐近长期错误,通常情况下的动态面临困难。我们的量子算法的另一个主要优点是,任何所需的保护定律都可以包括在自我校正的反馈回路中,该反馈循环可能具有广泛的适用性。我们通过执行仪表不变性来证明其功能,这对于忠实且长期以来对晶格量规理论的量子模拟至关重要。每当涉及时间离散化的数值方法中,我们的算法在更一般的级别上可能会在更一般的级别上有用。
Simulation of continuous time evolution requires time discretization on both classical and quantum computers. A finer time step improves simulation precision, but it inevitably leads to increased computational efforts. This is particularly costly for today's noisy intermediate scale quantum computers, where notable gate imperfections limit the circuit depth that can be executed at a given accuracy. Classical adaptive solvers are well-developed to save numerical computation times. However, it remains an outstanding challenge to make optimal usage of the available quantum resources by means of adaptive time steps. Here, we introduce a quantum algorithm to solve this problem, providing a controlled solution of the quantum many-body dynamics of local observables. The key conceptual element of our algorithm is a feedback loop which self-corrects the simulation errors by adapting time steps, thereby significantly outperforming conventional Trotter schemes on a fundamental level and reducing the circuit depth. It even allows for a controlled asymptotic long-time error, where usual Trotterized dynamics is facing difficulties. Another key advantage of our quantum algorithm is that any desired conservation law can be included in the self-correcting feedback loop, which has potentially a wide range of applicability. We demonstrate the capabilities by enforcing gauge invariance which is crucial for a faithful and long-sought quantum simulation of lattice gauge theories. Our algorithm can be potentially useful on a more general level whenever time discretization is involved concerning, for instance, also numerical approaches based on time-evolving block decimation methods.