Partial Minimum Branching Program Size Problem Is ETH-Hard

Authors Ludmila Glinskih , Artur Riazanov



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Ludmila Glinskih
  • Google, Mountain View, CA, USA
Artur Riazanov
  • EPFL, Lausanne, Switzerland

Acknowledgements

The authors are grateful to Rahul Santhanam for suggesting working on connections between meta-complexity and branching programs, and to Mark Bun and anonymous reviewers for very helpful feedback on the preliminary versions of this paper.

Cite As Get BibTex

Ludmila Glinskih and Artur Riazanov. Partial Minimum Branching Program Size Problem Is ETH-Hard. In 16th Innovations in Theoretical Computer Science Conference (ITCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 325, pp. 54:1-54:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ITCS.2025.54

Abstract

We show that assuming the Exponential Time Hypothesis, the Partial Minimum Branching Program Size Problem ({MBPSP}^{*}) requires superpolynomial time. This result also applies to the partial minimization problems for many interesting subclasses of branching programs, such as read-k branching programs and OBDDs.
Combining these results with the recent unconditional lower bounds for {MCSP} [Ludmila Glinskih and Artur Riazanov, 2022], we obtain an unconditional superpolynomial lower bound on the size of Read-Once Nondeterministic Branching Programs (1- NBP) computing the total versions of the minimum BP, read-k-BP, and OBDD size problems. 
Additionally we show that it is NP-hard to check whether a given BP computing a partial Boolean function can be compressed to a BP of a given size.

Subject Classification

ACM Subject Classification
  • Theory of computation → Circuit complexity
Keywords
  • MCSP
  • branching programs
  • meta-complexity
  • lower bounds

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