TILT: Achieving Higher Fidelity on a Trapped-Ion Linear-Tape Quantum Computing Architecture

  title={TILT: Achieving Higher Fidelity on a Trapped-Ion Linear-Tape Quantum Computing Architecture},
  author={Xin-Chuan Wu and Dripto M. Debroy and Yongshan Ding and Jonathan M. Baker and Yuri Alexeev and Kenneth R. Brown and Frederic T. Chong},
  journal={2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)},
  • X. Wu, Dripto M. Debroy, +4 authors F. Chong
  • Published 29 October 2020
  • Computer Science, Physics
  • 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
Trapped-ion qubits are a leading technology for practical quantum computing. In this work, we present an architectural analysis of a linear-tape architecture for trapped ions. In order to realize our study, we develop and evaluate mapping and scheduling algorithms for this architecture. In particular, we introduce TILT, a linear “Turing-machinelike” architecture with a multilaser control “head,” where a linear chain of ions moves back and forth under the laser head. We find that TILT can… Expand

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