通过高效Trotter-Suzuki方案减少门数量
Reducing the Gate Count with Efficient Trotter-Suzuki Schemes
AI总结：
本文提出了一种高效Trotter-Suzuki方案，用于减少量子模拟中的门数量，通过优化框架发现新方法并在Heisenberg模型上验证其效率。
摘要：
格点场论的哈密顿量形式提供了对实时动力学的访问，但其模拟难以高效实现。Trotter-Suzuki分解是时间演化计算的核心，无论是量子硬件还是经典计算，例如通过张量网络。尽管低阶Trotter化仍然是标准选择，因为其简单性，更高阶的方案有潜力提高效率。在本工作中，我们概述了Trotter-Suzuki方案及其一般实现的简要指南。为了帮助此目的，我们突出展示了通过我们的优化框架发现的新高效方案，并在Heisenberg模型上展示了其性能。
英文摘要：
Hamiltonian formulations of lattice field theories provide access to real-time dynamics, but their simulation is difficult to implement efficiently. Trotter-Suzuki decompositions are at the center of time evolution computation, either on quantum hardware or classically, for instance with the use of tensor networks. While low-order Trotterizations remain the standard choice due to their simplicity, higher-order schemes offer the potential for improved efficiency. In this work we outline a short guide to Trotter-Suzuki schemes and their implementations in general. To help with this, we highlight new efficient schemes found by our optimization framework, and demonstrate their performance on the Heisenberg model.
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