Codar: A Contextual Duration-Aware Qubit Mapping for Various NISQ Devices
Open accessAbstract
Quantum computing devices in the NISQ era share common features and challenges like limited connectivity between qubits. Since two-qubit gates are allowed on limited qubit pairs, quantum compilers must transform original quantum programs to fit the hardware constraints. Previous works on qubit mapping assume different gates have the same execution duration, which limits them to explore the parallelism from the program. To address this drawback, we propose a Multi-architecture Adaptive Quantum Abstract Machine (maQAM) and a COntext-sensitive and Duration-Aware Remapping algorithm (Codar). The Codar remapper is aware of gate duration difference and program context, enabling it to extract more parallelism from programs and speed up the quantum programs by 1.23 in simulation on average in different architectures and maintain the fidelity of circuits when running on OriginQ quantum noisy simulator.
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We have adopted the concept introduced in [37] to define the notion of 'occupied time' for a qubit.
“We have adopted the concept introduced in [37] to define the notion of 'occupied time' for a qubit.”
From Robust Qubit Mapping Algorithm via Double-Source Optimal Routing on Large Quantum Circuits (2024) · cites this paper as [37]
These algorithms could only handle mapping problems up to 50 qubits.
“Consequently, they could only handle mapping problems up to 50 qubits, which is much smaller than the number of required qubits for achieving quantum advantage.”
From Robust Qubit Mapping Algorithm via Double-Source Optimal Routing on Large Quantum Circuits (2024) · cites this paper as [37]
Deng et al. introduce a model in which single-qubit gates occupy one unit of time and double-qubit gates occupy two units.
“To simplify calculations, Deng et al. introduce a model in which single-qubit gates occupy one unit of time and double-qubit gates occupy two units.”
From Robust Qubit Mapping Algorithm via Double-Source Optimal Routing on Large Quantum Circuits (2024) · cites this paper as [37]
The runtime of algorithms that calculate costs of all potential swapping candidates in each iteration when selecting a SWAP was very long.
“Although the above-mentioned algorithms claimed to achieve optimal mapping solutions, the runtime of these algorithms was very long due to the fact that they needed to calculate the costs of all the potential swapping candidates in each iteration when selecting a SWAP.”
From Robust Qubit Mapping Algorithm via Double-Source Optimal Routing on Large Quantum Circuits (2024) · cites this paper as [37]
CODAR notes that the execution time of single-qubit and double-qubit gates is different.
“CODAR [37] notes that the execution time of single-qubit and double-qubit gates is different.”
From Robust Qubit Mapping Algorithm via Double-Source Optimal Routing on Large Quantum Circuits (2024) · cites this paper as [37]
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- Authors
- Deng, H., Zhang, Y., & Li, Q.
- Affiliations
- University of Science and Technology of China (CN)
- Venue
- 2020 57th ACM/IEEE Design Automation Conference (DAC)
- Publisher
- IEEE
- Published
- 2020-07
- Pages
- 1-6
- ISSN
- 0738-100X (ISSN-L)
- OpenAlex
- W3008133439
- Cited by
- 23
- References
- 29
- Citations by year
- 2026: 1 · 2025: 7 · 2024: 6 · 2023: 3 · 2022: 2 · 2021: 3 · 2019: 1
- FWCI
- 0.76
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- ACM/IEEE Design Automation Conference (DAC) (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Keywords
- qubit mapping, quantum circuit compilation, NISQ devices, parallelism extraction, maqam, CODAR, circuit fidelity, noisy quantum simulation
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