Abstract
Ion trap quantum hardware promises to provide a computational advantage over classical computing for specific problem spaces while also providing an alternative hardware implementation path to cryogenic quantum systems as typified by IBM's quantum hardware. However, programming ion trap systems currently requires both strategies to mitigate high levels of noise and also tools to ease the challenge of programming these systems with pulse- or gate-level operations. This work focuses on improving the state-of-the-art for quantum programming of ion trap testbeds through the use of a quantum language specification, QCOR, and by demonstrating multi-level optimizations at the language, intermediate representation, and hardware backend levels. We implement a new QCOR/XACC backend to target a general ion trap testbed and then demonstrate the usage of multi-level optimizations to improve circuit fidelity and to reduce gate count. These techniques include the usage of a backend-specific numerical optimizer and physical gate optimizations to minimize the number of native instructions sent to the hardware. We evaluate our compiler backend using several QCOR benchmark programs, finding that on present testbed hardware, our compiler backend maintains the number of two-qubit native operations but decreases the number of single-qubit native operations by 1.54 times compared to the previous compiler regime. For projected testbed hardware upgrades, our compiler sees a reduction in two-qubit native operations by 2.40 times and one-qubit native operations by 6.13 times.
Original language | English |
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Title of host publication | Proceedings - 2021 International Conference on Rebooting Computing, ICRC 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 14-23 |
Number of pages | 10 |
ISBN (Electronic) | 9781665423328 |
DOIs | |
State | Published - 2021 |
Event | 2021 International Conference on Rebooting Computing, ICRC 2021 - Virtual, Online, United States Duration: Nov 30 2021 → Dec 2 2021 |
Publication series
Name | Proceedings - 2021 International Conference on Rebooting Computing, ICRC 2021 |
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Conference
Conference | 2021 International Conference on Rebooting Computing, ICRC 2021 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 11/30/21 → 12/2/21 |
Funding
The first author is partially supported by the Institute for Electronics and Nanotechnology’s Georgia Tech Quantum Alliance. Additionally, we acknowledge support for this work from NSF planning grant #2016666, “Enabling Quantum Computer Science and Engineering” and through the ORNL STAQCS project. Finally, this research was supported in part through research infrastructure and services provided by the Rogues Gallery testbed [33] hosted by the Center for Research into Novel Computing Hierarchies (CRNCH) at Georgia Tech and funded by NSF Award Number #2016701. We thank the anonymous reviewers for their helpful feedback.
Keywords
- compilation
- ion trap
- multi-level optimization
- quantum computing