License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.TQC.2022.1
URN: urn:nbn:de:0030-drops-165081
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16508/
Go to the corresponding LIPIcs Volume Portal


Montanaro, Ashley ; Shao, Changpeng

Quantum Algorithms for Learning a Hidden Graph

pdf-format:
LIPIcs-TQC-2022-1.pdf (0.7 MB)


Abstract

We study the problem of learning an unknown graph provided via an oracle using a quantum algorithm. We consider three query models. In the first model ("OR queries"), the oracle returns whether a given subset of the vertices contains any edges. In the second ("parity queries"), the oracle returns the parity of the number of edges in a subset. In the third model, we are given copies of the graph state corresponding to the graph.
We give quantum algorithms that achieve speedups over the best possible classical algorithms in the OR and parity query models, for some families of graphs, and give quantum algorithms in the graph state model whose complexity is similar to the parity query model. For some parameter regimes, the speedups can be exponential in the parity query model. On the other hand, without any promise on the graph, no speedup is possible in the OR query model.
A main technique we use is the quantum algorithm for solving the combinatorial group testing problem, for which a query-efficient quantum algorithm was given by Belovs. Here we additionally give a time-efficient quantum algorithm for this problem, based on the algorithm of Ambainis et al. for a "gapped" version of the group testing problem.

BibTeX - Entry

@InProceedings{montanaro_et_al:LIPIcs.TQC.2022.1,
  author =	{Montanaro, Ashley and Shao, Changpeng},
  title =	{{Quantum Algorithms for Learning a Hidden Graph}},
  booktitle =	{17th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2022)},
  pages =	{1:1--1:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-237-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{232},
  editor =	{Le Gall, Fran\c{c}ois and Morimae, Tomoyuki},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16508},
  URN =		{urn:nbn:de:0030-drops-165081},
  doi =		{10.4230/LIPIcs.TQC.2022.1},
  annote =	{Keywords: Quantum algorithms, query complexity, graphs, combinatorial group testing}
}

Keywords: Quantum algorithms, query complexity, graphs, combinatorial group testing
Collection: 17th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2022)
Issue Date: 2022
Date of publication: 04.07.2022


DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI