论文标题
与混合张量网络的量子模拟
Quantum simulation with hybrid tensor networks
论文作者
论文摘要
张量网络理论和量子模拟分别是理解量子多体物理学的关键经典和量子计算方法。在这里，我们介绍了混合量张量网络的框架，该框架具有由可测量的量子状态和经典缩写量的构建块，在有效地表示多体波函数方面都继承了它们的独特特征。以混合树张量网络的示例，我们使用量子计算机表现出有效的量子模拟，该量子计算机的大小明显小于目标系统之一。我们从数值上基准了我们的方法，用于查找最高$ 8 $ 8 $和$ 9 \ times 8 $ Qubits的1D和2D旋转系统的基础状态，其操作仅对$ 8+1 $和$ 9+1 $ QUBITS作用。我们的方法阐明了中等规模量子计算机的大量实际问题，并在化学，量子多体物理学，量子场理论和量子重力思维实验中使用了潜在的应用。
Tensor network theory and quantum simulation are respectively the key classical and quantum computing methods in understanding quantum many-body physics. Here, we introduce the framework of hybrid tensor networks with building blocks consisting of measurable quantum states and classically contractable tensors, inheriting both their distinct features in efficient representation of many-body wave functions. With the example of hybrid tree tensor networks, we demonstrate efficient quantum simulation using a quantum computer whose size is significantly smaller than the one of the target system. We numerically benchmark our method for finding the ground state of 1D and 2D spin systems of up to $8\times 8$ and $9\times 8$ qubits with operations only acting on $8+1$ and $9+1$ qubits,~respectively. Our approach sheds light on simulation of large practical problems with intermediate-scale quantum computers, with potential applications in chemistry, quantum many-body physics, quantum field theory, and quantum gravity thought experiments.
