A Generalized Quantum Branching Program

Authors Debajyoti Bera, Tharrmashastha SAPV



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Author Details

Debajyoti Bera
  • Department of Computer Science, IIIT-D, New Delhi, India
Tharrmashastha SAPV
  • Department of Computer Science, IIIT-D, New Delhi, India

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Debajyoti Bera and Tharrmashastha SAPV. A Generalized Quantum Branching Program. In 43rd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 284, pp. 31:1-31:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.FSTTCS.2023.31

Abstract

Classical branching programs are studied to understand the space complexity of computational problems. Prior to this work, Nakanishi and Ablayev had separately defined two different quantum versions of branching programs that we refer to as NQBP and AQBP. However, none of them, to our satisfaction, captures the intuitive idea of being able to query different variables in superposition in one step of a branching program traversal. Here, we propose a quantum branching program model, referred to as GQBP, with that ability. To motivate our definition, we explicitly give examples of GQBP for n-bit Deutsch-Jozsa, n-bit Parity, and 3-bit Majority with optimal lengths. We then show several equivalences, namely, between GQBP and AQBP, GQBP and NQBP, and GQBP and query complexities (using either oracle gates or a QRAM to query input bits). In a way, this unifies the different results that we have for the two earlier branching programs and also connects them to query complexity. We hope that GQBP can be used to prove space and space-time lower bounds for quantum solutions to combinatorial problems.

Subject Classification

ACM Subject Classification
  • Theory of computation → Quantum computation theory
  • Theory of computation → Quantum query complexity
  • Theory of computation → Quantum complexity theory
Keywords
  • Quantum computing
  • quantum branching programs
  • quantum algorithms
  • query complexity

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References

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