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Quantum Optimization
Quantum Machine Learning
Quantum Speedup and Limitations on Matroid Property Problems
arXiv
Authors: Xiaowei Huang, Jingquan Luo, Lvzhou Li
Year
2021
Paper ID
41297
Status
Preprint
Abstract Read
~2 min
Abstract Words
157
Citations
N/A
Abstract
This paper initiates the study of quantum algorithms for matroid property problems. It is shown that quadratic quantum speedup is possible for the calculation problem of finding the girth or the number of circuits (bases, flats, hyperplanes) of a matroid, and for the decision problem of deciding whether a matroid is uniform or Eulerian, by giving a uniform lower bound Ω\(sqrt{binom{n}{lfloor n/2rfloor}}\) on the query complexity for all these problems. On the other hand, for the uniform matroid decision problem, an asymptotically optimal quantum algorithm is proposed which achieves the lower bound, and for the girth problem, an almost optimal quantum algorithm is given with query complexity O\(log nsqrt{binom{n}{lfloor n/2rfloor}}\). In addition, for the paving matroid decision problem, a lower bound Ω\(sqrt{binom{n}{lfloor n/2rfloor}/n}\) on the query complexity is obtained, and an O\(sqrt{binom{n}{lfloor n/2rfloor}}\) quantum algorithm is presented.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2021 reference point for readers tracking recent quantum research.
- This paper initiates the study of quantum algorithms for matroid property problems.
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