Ternary Tree Fermion-to-Qubit Mapping with Hamiltonian Aware Optimization
<|reference_start|>Ternary Tree Fermion-to-Qubit Mapping with Hamiltonian Aware Optimization: This paper introduces the Hamiltonian-Aware Ternary Tree (HATT) framework to compile optimized Fermion-to-qubit mapping for specific Fermionic Hamiltonians. In the simulation of Fermionic quantum systems, efficient Fermion-to-qubit mapping plays a critical role in transforming the Fermionic system into a qubit system. HATT utilizes ternary tree mapping and a bottom-up construction procedure to generate Hamiltonian aware Fermion-to-qubit mapping to reduce the Pauli weight of the qubit Hamiltonian, resulting in lower quantum simulation circuit overhead. Additionally, our optimizations retain the important vacuum state preservation property in our Fermion-to-qubit mapping and reduce the complexity of our algorithm from $O(N^4)$ to $O(N^3)$. Evaluations and simulations of various Fermionic systems demonstrate a significant reduction in both Pauli weight and circuit complexity, alongside excellent scalability to larger systems. Experiments on the Ionq quantum computer also show the advantages of our approach in noise resistance in quantum simulations.<|reference_end|>
@article{liu2024ternary,
    title={Ternary Tree Fermion-to-Qubit Mapping with Hamiltonian Aware
  Optimization},
    author={Yuhao Liu, Kevin Yao, Jonathan Hong, Julien Froustey, Yunong Shi,
  Ermal Rrapaj, Costin Iancu, Gushu Li},
    journal={arXiv preprint arXiv:2409.02010},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.02010},
    primaryClass={quant-ph cs.ET}
}