Tetris: A Compilation Framework for VQA Applications in Quantum Computing

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 a fast bridging approach that mitigates the hardware mapping cost. Overall, Tetris demonstrates a reduction of up to 41.3 percent in CNOT gate counts, 37.9 percent in circuit depth, and 42.6 percent 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.