The space complexity of recognizing well-parenthesized expressions in the streaming model: the Index function revisited
Rahul Jain, Ashwin Nayak

TL;DR
This paper establishes a space lower bound for unidirectional streaming algorithms recognizing well-parenthesized expressions, proving bidirectional streams are exponentially more space-efficient, and explores quantum protocols for related problems.
Contribution
It proves a conjecture on space complexity lower bounds for streaming algorithms and introduces a novel quantum information cost framework for analyzing quantum protocols.
Findings
Unidirectional streaming algorithms require at least Omega(sqrt{n}/T) space.
Bidirectional streams are exponentially more efficient than unidirectional ones.
Quantum information cost analysis reveals limitations for quantum streaming algorithms.
Abstract
We show an Omega(sqrt{n}/T) lower bound for the space required by any unidirectional constant-error randomized T-pass streaming algorithm that recognizes whether an expression over two types of parenthesis is well-parenthesized. This proves a conjecture due to Magniez, Mathieu, and Nayak (2009) and rigorously establishes that bidirectional streams are exponentially more efficient in space usage as compared with unidirectional ones. We obtain the lower bound by establishing the minimum amount of information that is necessarily revealed by the players about their respective inputs in a two-party communication protocol for a variant of the Index function, namely Augmented Index. The information cost trade-off is obtained by a novel application of the conceptually simple and familiar ideas such as average encoding and the cut-and-paste property of randomized protocols. Motivated by recent…
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