Tetris: A Compilation Framework for VQA Applications in Quantum Computing

Quantum computing has shown promise in solving complex problems by leveraging the principles of superposition and entanglement. Variational quantum algorithms (VQA) are a class of algorithms suited for near-term quantum computers due to their modest requirements of qubits and depths of computation....

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Vydané v:2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) s. 277 - 292
Hlavní autori: Jin, Yuwei, Li, Zirui, Hua, Fei, Hao, Tianyi, Zhou, Huiyang, Huang, Yipeng, Zhang, Eddy Z.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 29.06.2024
Predmet:
compilation
Computer architecture
Computers
Costs
Logic gates
Quantum algorithm
Quantum computing
Quantum entanglement
Qubit
VQA
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Popis
Shrnutí:Quantum computing has shown promise in solving complex problems by leveraging the principles of superposition and entanglement. Variational quantum algorithms (VQA) are a class of algorithms suited for near-term quantum computers due to their modest requirements of qubits and depths of computation. This paper introduces Tetris - a compilation framework for VQA applications on near-term quantum devices. Tetris focuses on reducing two-qubit gates in the compilation process since a two-qubit gate has an order of magnitude more significant error and execution time than a single-qubit gate. Tetris exploits unique opportunities in the circuit synthesis stage often overlooked by the state-of-the-art VQA compilers for reducing the number of two-qubit gates. Tetris comes with a refined IR of Pauli string to express such a two-qubit gate optimization opportunity. Moreover, Tetris is equipped with a fast bridging approach that mitigates the hardware mapping cost. Overall, Tetris demonstrates a reduction of up to 41.3 \% in CNOT gate counts, 37.9 \% in circuit depth, and \mathbf{4 2. 6 \%} in circuit duration for various molecules of different sizes and structures compared with the state-of-the-art approaches. Tetris is open-sourced at this link.
DOI:10.1109/ISCA59077.2024.00029