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A Exact Quantum Learning Algorithm for the 2-Junta Problem in Constant Time

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Abstract

This study proposes an exact quantum learning algorithm for finding two dependent variables to solve the 2-junta problem. A 2-junta is a Boolean function \(f:{\left\{\text{0,1}\right\}}^{n}\to \left\{0, 1\right\}\) that depends on only 2 out of \(n\) variables. In 2021, Chen proposed an exact quantum learning algorithm for solving the 2-junta problem by performing the function operation \(O\left({log}_{2}n\right)\) times in the worst case. However, our proposed quantum algorithm only requires three function operations in the worst case using the modified black-box function of El-Wazan et al.

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  1. Department of Computer Science and Information Engineering, National University of Kaohsiung, No.700, Kaohsiung University Rd, Kaohsiung, Taiwan

    Chien-Yuan Chen

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  1. Chien-Yuan Chen
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Correspondence to Chien-Yuan Chen.

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Chen, CY. A Exact Quantum Learning Algorithm for the 2-Junta Problem in Constant Time. Int J Theor Phys 61, 212 (2022). https://doi.org/10.1007/s10773-022-05198-4

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  • DOI: https://doi.org/10.1007/s10773-022-05198-4

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