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arxiv: 1206.3348 · v1 · submitted 2012-06-14 · 🪐 quant-ph

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Quantum Compiler Optimizations

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classification 🪐 quant-ph
keywords quantumgatesapplygateoptimizationstheybitscalled
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A quantum computer consists of a set of quantum bits upon which operations called gates are applied to perform computations. In order to perform quantum algorithms, physicists would like to design arbitrary gates to apply to quantum bits. However, the physical limitations of the quantum computing device restrict the set of gates that physicists are able to apply. Thus, they must compose a sequence of gates from the permitted gate set, which approximates the gate they wish to apply - a process called quantum compiling. Austin Fowler proposes a method that finds optimal gate sequences in exponential time, but which is tractable for common problems. In this paper, I present several optimizations to this algorithm. While my optimizations do not improve its overall exponential behavior, they improve its empirical performance by one to two orders of magnitude.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problem

    quant-ph 2026-05 unverdicted novelty 6.0

    Reinforcement learning policy for qubit mapping reduces SWAP overhead by 65-85% versus standard quantum compilers on MQTBench and Queko benchmark circuits.