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arXiv · 2410.04008

Design the Quantum Instruction Set with the Cartan Coordinate Analysis Framework

Abstract

Most quantum compiling efforts rely on standard two-qubit basis gates, such as CX and iSWAP, to implement general quantum operations. However, with the advancement of quantum architecture design, more nonstandard two-qubit gates can now be implemented and calibrated on devices. Using these nonstandard gates may improve the performance of quantum computation. Despite this potential, it remains unclear how to efficiently incorporate these nonstandard gates into the quantum instruction set to enhance quantum advantage. To address this, we propose an analytical framework that facilitates the design of quantum instruction sets based on nonstandard gates. Our approach is grounded in the KAK decomposition and an analysis of the Cartan coordinate of two-qubit operations, enabling analytical conversion between any two two-qubit operations. This framework also demonstrates the lower and upper bounds of the conversion cost, revealing the relationship between the entangling power of two-qubit instructions and their Cartan coordinates. We further develop a compiler based on the analytical framework, which reduces the unitary decomposition cost with nonstandard two-qubit instructions. Using the proposed compiler, we evaluate various options for designing a quantum instruction set based on nonstandard gates. Our experiments demonstrate the efficiency of the proposed framework in the quantum instruction set design. Compared to the state-of-the-art method that is based on the numerical search, our framework reduces the time/resource overhead of exploring the instruction set design space by thousands of times. Moreover, with the established framework, we propose feasible designs for the quantum instruction set by modeling real-world quantum processors, further promoting the quantum advantage.

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BibTeXRIS

Anbang Wu, Jingwen Leng, Minyi Guo. 2025-03-04. Design the Quantum Instruction Set with the Cartan Coordinate Analysis Framework. https://arxiv.org/abs/2410.04008

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