Quantum Query as a State Decomposition

TL;DR

This paper introduces a new Block Set formulation of the Quantum Query Model, providing an explicit interpretation of quantum algorithms through vector decomposition and phase inversion, with applications to analyzing quantum exact algorithms.

Contribution

It presents the Block Set formulation as an alternative to the Quantum Query Model, offering clearer insights into quantum algorithm structure and complexity analysis.

Findings

Block Set vectors must satisfy specific properties.

Both formulations produce the same output state Gram matrix.

The approach simplifies the analysis of quantum exact algorithms.

Abstract

The Quantum Query Model is a framework that allows us to express most known quantum algorithms. Algorithms represented by this model consist on a set of unitary operators acting over a finite Hilbert space, and a final measurement step consisting on a set of projectors. In this work, we prove that the application of these unitary operators before the measurement step is equivalent to decomposing a unit vector into a sum of vectors and then inverting some of their relative phases. We also prove that the vectors of that sum must fulfill a list of properties and we call such vectors a Block Set. If we define the measurement step for the Block Set Formulation similarly to the Quantum Query Model, then we prove that both formulations give the same Gram matrix of output states, although the Block Set Formulation allows a much more explicit form. Therefore, the Block Set reformulation of the Quantum Query Model gives us an alternative interpretation on how quantum algorithms works. Finally, we apply our approach to the analysis and complexity of quantum exact algorithms.