On the Fine-Grained Query Complexity of Symmetric Functions
Supartha Podder, Penghui Yao, Zekun Ye

TL;DR
This paper investigates the query complexity of symmetric Boolean functions, establishing relationships between quantum and randomized algorithms, and proving polynomial equivalences among various complexity measures.
Contribution
It provides new bounds relating quantum and randomized query complexities for symmetric functions and proves polynomial equivalences among complexity measures.
Findings
Quantum algorithms can be simulated by randomized algorithms with polynomial overhead.
For symmetric functions, success probabilities close to 1/2 can be achieved with limited queries.
Polynomial equivalences among complexity measures are established for partial symmetric functions.
Abstract
This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to . Our contributions include the following: i) An analysis of the optimal success probability of quantum and randomized query algorithms of two fundamental partial symmetric Boolean functions given a fixed number of queries. We prove that for any quantum algorithm computing these two functions using queries, there exist randomized algorithms using queries that achieve the same success probability as the quantum algorithm, even if the success probability is arbitrarily close to 1/2. ii) We establish that for any total symmetric Boolean function , if a quantum algorithm uses queries to compute with success probability , then there exists a randomized algorithm using…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Machine Learning and Algorithms · Complexity and Algorithms in Graphs
