Transversal STAR architecture for megaquop-scale quantum simulation with neutral atoms Part 1.

ORAL

Abstract



Recent progress in quantum error correction anticipates an early era of fault-tolerant quantum computers, with millions of reliable quantum operations, but the cost of preparing low-noise magic states remains challenging. The proposed partially-fault-tolerant STAR architecture attempted to address this challenge by using post-selection to prepare low-noise, small-angle magic. Its envisioned physical implementation, however, assumes fixed qubit connectivity, resulting in implementation costs closer to fully-fault-tolerant approaches. Here, we propose the transversal STAR architecture and co-design it with neutral-atom quantum hardware, deriving significant savings in logical layout, time, and space. Through circuit-level simulations, we derive the logical noise model for surface-code-based transversal gadgets and verify their composability. At its limit, the transversal STAR can efficiently simulate local Hamiltonians with a total simulation volume >600. Achieving this limit requires 10,000 physical qubits at a physical error rate of 10-3. This is equivalent to a fully-fault-tolerant computation requiring 106-107 T gates. Finally, we extend the transversal STAR architecture to high-rate quantum codes, demonstrating how a limited set of highly parallel transversal Clifford gates and generalized small-angle magic injection can be utilized for local Hamiltonian simulation, thus substantially reducing the physical resources necessary for megaquop-scale quantum simulation.

*This work was supported by the NNSA ASC Beyond Moore's Law project and the Edwin Thompson Jaynes Postdoctoral Fellowship of the Washington University Physics Department. Numerical studies were performed on the HPC system Perlmutter, a NERSC resource, using NERSC award DDR-ERCAP0030190.

Publication: https://arxiv.org/abs/2509.18294

Presenters

  • I Chi Chen

    • Ames National Laboratory, Iowa State University
    • LANL
    • Los Alamos National Lab

Authors

  • I Chi Chen

    • Ames National Laboratory, Iowa State University
    • LANL
    • Los Alamos National Lab
  • Refaat Ismail

    • Quera Computing Inc
    • QuEra Computing Inc.
  • Chen Zhao

    • QuEra Computing Inc.
  • Ronen Weiss

    • Los Alamos National Laboratory (LANL)
    • Washington University in St. Louis
  • Fangli Liu

    • QuEra Computing Inc.
  • Hengyun Zhou

    • QuEra Computing Inc.
    • QuEra Computing Inc., Massachusetts Institute of Technology
    • QuEra Computing and MIT
  • Shengtao Wang

    • QuEra Computing Inc.
  • Andrew T Sornborger

    • Los Alamos National Laboratory (LANL)
  • Milan Kornjaca

    • QuEra Computing Inc.