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HATT: Hamiltonian Aware Ternary Tree for Optimizing Fermion-to-Qubit Mapping

ORAL

Abstract

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.

Publication: https://dl.acm.org/doi/10.1145/3620666.3651371<br>https://arxiv.org/abs/2409.02010v1

Presenters

  • Yuhao Liu

    University of Pennsylvania

Authors

  • Yuhao Liu

    University of Pennsylvania

  • Kevin Yao

    University of Pennsylvania

  • Jonathan Hong

    University of Pennsylvania

  • Julien Froustey

    University of California, Berkeley

  • Yunong Shi

    Amazon.com, Inc.

  • Ermal Rrapaj

    University of California, Berkeley, Lawrence Berkeley National Laboratory

  • Costin C Iancu

    Lawrence Berkeley National Laboratory

  • Gushu Li

    University of Pennsylvania