Tetris: A Compilation Framework for VQA Applications in Quantum Computing
Yuwei Jin, Zirui Li, Fei Hua, Tianyi Hao, Huiyang Zhou, Yipeng Huang,, and Eddy Z. Zhang

TL;DR
Tetris is a novel compilation framework for VQA applications on near-term quantum devices that significantly reduces two-qubit gate counts, circuit depth, and duration, improving efficiency and accuracy.
Contribution
It introduces a new IR and optimization techniques specifically targeting two-qubit gate reduction in VQA circuit compilation.
Findings
Up to 41.3% reduction in CNOT gates
Up to 37.9% reduction in circuit depth
Up to 42.6% reduction in circuit duration
Abstract
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…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Neural Networks and Reservoir Computing · Quantum Information and Cryptography
