Hardness Amplification for Dynamic Binary Search Trees
Shunhua Jiang, Victor Lecomte, Omri Weinstein, Sorrachai, Yingchareonthawornchai

TL;DR
This paper establishes new theoretical bounds for binary search trees, demonstrating the optimality of Tango trees under certain conditions and advancing understanding of dynamic optimality in BST models.
Contribution
It proves direct-sum theorems for Wilber's lower bounds and uses them to show Tango trees are optimal among BST algorithms charging costs to the Alternation bound.
Findings
Proves direct-sum theorems for Wilber's bounds.
Amplifies sequences to increase bounds while maintaining separation.
Shows Tango trees are optimal for any value of the Alternation bound.
Abstract
We prove direct-sum theorems for Wilber's two lower bounds [Wilber, FOCS'86] on the cost of access sequences in the binary search tree (BST) model. These bounds are central to the question of dynamic optimality [Sleator and Tarjan, JACM'85]: the Alternation bound is the only bound to have yielded online BST algorithms beating competitive ratio, while the Funnel bound has repeatedly been conjectured to exactly characterize the cost of executing an access sequence using the optimal tree [Wilber, FOCS'86, Kozma'16], and has been explicitly linked to splay trees [Levy and Tarjan, SODA'19]. Previously, the direct-sum theorem for the Alternation bound was known only when approximation was allowed [Chalermsook, Chuzhoy and Saranurak, APPROX'20, ToC'24]. We use these direct-sum theorems to amplify the sequences from [Lecomte and Weinstein, ESA'20] that separate between Wilber's…
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