English

Ab-initio tree-tensor-network digital twin for quantum computer benchmarking in 2D

Quantum Physics 2024-07-01 v3

Abstract

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×\times8 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%99.9\% fidelity in a closed system while achieving a speedup of 35%35\% via parallelization.

Keywords

Cite

@article{arxiv.2210.03763,
  title  = {Ab-initio tree-tensor-network digital twin for quantum computer benchmarking in 2D},
  author = {Daniel Jaschke and Alice Pagano and Sebastian Weber and Simone Montangero},
  journal= {arXiv preprint arXiv:2210.03763},
  year   = {2024}
}

Comments

17 pages, 8 figures, 2 tables; minor updates in the conclusion for clarification and fix of some typos

R2 v1 2026-06-28T03:01:57.741Z