Equivalence of Systematic Linear Data Structures and Matrix Rigidity

Authors Sivaramakrishnan Natarajan Ramamoorthy, Cyrus Rashtchian

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Sivaramakrishnan Natarajan Ramamoorthy
  • University of Washington, Seattle, USA
Cyrus Rashtchian
  • University of California, San Diego, USA


We thank Paul Beame, Sajin Koroth, Pavel Hrubeš, Pavel Pudlák, Anup Rao, Makrand Sinha, Amir Yehudayoff and Sergey Yekhanin for useful discussions. Special thanks to Paul, Anup, Makrand and Amir for the encouragement to write up these results.

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Sivaramakrishnan Natarajan Ramamoorthy and Cyrus Rashtchian. Equivalence of Systematic Linear Data Structures and Matrix Rigidity. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 35:1-35:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


Recently, Dvir, Golovnev, and Weinstein have shown that sufficiently strong lower bounds for linear data structures would imply new bounds for rigid matrices. However, their result utilizes an algorithm that requires an NP oracle, and hence, the rigid matrices are not explicit. In this work, we derive an equivalence between rigidity and the systematic linear model of data structures. For the n-dimensional inner product problem with m queries, we prove that lower bounds on the query time imply rigidity lower bounds for the query set itself. In particular, an explicit lower bound of ω(n/r log m) for r redundant storage bits would yield better rigidity parameters than the best bounds due to Alon, Panigrahy, and Yekhanin. We also prove a converse result, showing that rigid matrices directly correspond to hard query sets for the systematic linear model. As an application, we prove that the set of vectors obtained from rank one binary matrices is rigid with parameters matching the known results for explicit sets. This implies that the vector-matrix-vector problem requires query time Ω(n^(3/2)/r) for redundancy r ≥ √n in the systematic linear model, improving a result of Chakraborty, Kamma, and Larsen. Finally, we prove a cell probe lower bound for the vector-matrix-vector problem in the high error regime, improving a result of Chattopadhyay, Koucký, Loff, and Mukhopadhyay.

Subject Classification

ACM Subject Classification
  • Theory of computation → Cell probe models and lower bounds
  • Theory of computation → Circuit complexity
  • matrix rigidity
  • systematic linear data structures
  • cell probe model
  • communication complexity


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