Quantum Speedup Based on Classical Decision Trees

Abstract

Lin and Lin have recently shown how starting with a classical query algorithm (decision tree) for a function, we may find upper bounds on its quantum query complexity. More precisely, they have shown that given a decision tree for a function $f:\{0,1{\}}^n\to [m]$ whose input can be accessed via queries to its bits, and a guessing algorithm that predicts answers to the queries, there is a quantum query algorithm for $f$ which makes at most $O(\sqrt{GT})$ quantum queries where $T$ is the depth of the decision tree and $G$ is the maximum number of mistakes of the guessing algorithm. In this paper we give a simple proof of and generalize this result for functions $f:[\ell {]}^n\to [m]$ with non-binary input as well as output alphabets. Our main tool for this generalization is non-binary span program which has recently been developed for non-binary functions, and the dual adversary bound. As applications of our main result we present several quantum query upper bounds, some of which are new. In particular, we show that topological sorting of vertices of a directed graph $\mathcal{G}$ can be done with $O(n^{3/2})$ quantum queries in the adjacency matrix model. Also, we show that the quantum query complexity of the maximum bipartite matching is upper bounded by $O(n^{3/4}\sqrt{m}+n)$ in the adjacency list model.

arXiv comment32 pages, 2 figures. Matches published version

References in corpus (10)

• Quantum Counting
• Negative weights make adversaries stronger
• Quantum query complexity of state conversion
• Quantum query complexity of some graph problems
• Quantum lower bounds for the collision and the element distinctness problems
• Span programs and quantum query complexity: The general adversary bound is nearly tight for every boolean function
• Span-program-based quantum algorithm for evaluating formulas
• Span programs and quantum algorithms for st-connectivity and claw detection
• Quantum query complexity of minor-closed graph properties
• Symmetry-assisted adversaries for quantum state generation

Cited by in corpus (6)

• Representation of binary classification trees with binary features by quantum circuits
• Quantum-accelerated constraint programming
• Des-q: a quantum algorithm to provably speedup retraining of decision trees
• A Query-Efficient Quantum Algorithm for Maximum Matching on General Graphs
• Improved Quantum Query Complexity on Easier Inputs
• Improved Quantum Query Upper Bounds Based on Classical Decision Trees