Adapt or Die: Polynomial Lower Bounds for Non-Adaptive Dynamic Data Structures
Joshua Brody, Kasper Green Larsen

TL;DR
This paper establishes polynomial lower bounds for non-adaptive dynamic data structures in the cell probe model, revealing fundamental limits and connecting data structure complexity to circuit lower bounds.
Contribution
It proves polynomial lower bounds for non-adaptive data structures and explores properties that could lead to such bounds in more general models.
Findings
Polynomial lower bounds for non-adaptive data structures.
Identification of key properties for proving bounds.
Connection between data structures and depth-2 circuit complexity.
Abstract
In this paper, we study the role non-adaptivity plays in maintaining dynamic data structures. Roughly speaking, a data structure is non-adaptive if the memory locations it reads and/or writes when processing a query or update depend only on the query or update and not on the contents of previously read cells. We study such non-adaptive data structures in the cell probe model. This model is one of the least restrictive lower bound models and in particular, cell probe lower bounds apply to data structures developed in the popular word-RAM model. Unfortunately, this generality comes at a high cost: the highest lower bound proved for any data structure problem is only polylogarithmic. Our main result is to demonstrate that one can in fact obtain polynomial cell probe lower bounds for non-adaptive data structures. To shed more light on the seemingly inherent polylogarithmic lower bound…
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Taxonomy
TopicsAdvanced Data Storage Technologies · Distributed systems and fault tolerance · Cryptography and Data Security
