论文标题
Ab-initio树刺量网络网络数字双胞胎用于量子计算机基准测试2D
Ab-initio tree-tensor-network digital twin for quantum computer benchmarking in 2D
论文作者
论文摘要
嘈杂的中级量表量子（NISQ）计算机的大规模数值模拟 - 数字双胞胎 - 在开发有效且可扩展的策略中可以为特定硬件调整量子算法而发挥重要作用。通过Rydberg Atom Quantum计算机的二维张量网络数字双胞胎，我们证明了此类程序的可行性。特别是，我们量化了由Rydberg原子之间的范德华诱导的栅极串扰的效果：根据8 $ \ times $ 8 $ 8的数字双胞胎模拟，基于当前的最新实验设置，可以用高屈服的五号重复代码的初始状态来制备五号重复的代码，以高于first fors for a First量指标，以量身定量计算，以计算有效的量计算。以约700个大门为单位的64 Qubit Greenberger-Horne-Horne-Horne-Zeilinger（GHz）状态在封闭系统中产生了$ 99.9 \％的$ fidelity，同时通过并行化获得了$ 35 \％$的加速。
Large-scale numerical simulations of the Hamiltonian dynamics of a Noisy Intermediate Scale Quantum (NISQ) computer - a digital twin - could play a major role in developing efficient and scalable strategies for tuning quantum algorithms for specific hardware. Via a two-dimensional tensor network digital twin of a Rydberg atom quantum computer, we demonstrate the feasibility of such a program. In particular, we quantify the effects of gate crosstalks induced by the van der Waals interaction between Rydberg atoms: according to an 8$\times$8 digital twin simulation based on the current state-of-the-art experimental setups, the initial state of a five-qubit repetition code can be prepared with a high fidelity, a first indicator for a compatibility with fault-tolerant quantum computing. The preparation of a 64-qubit Greenberger-Horne-Zeilinger (GHZ) state with about 700 gates yields a $99.9\%$ fidelity in a closed system while achieving a speedup of $35\%$ via parallelization.
