An algebraic interpretation of Pauli flow, leading to faster flow-finding algorithms
Piotr Mitosek, Miriam Backens

TL;DR
This paper introduces an algebraic approach to Pauli flow in quantum computation, simplifying its definition and enabling faster algorithms for flow-finding, which enhances the efficiency of one-way quantum computation models.
Contribution
It provides a new algebraic interpretation of Pauli flow using matrices, leading to improved $ ext{O}(n^3)$ algorithms for finding Pauli flow and establishing a lower bound for the problem.
Findings
Algebraic characterization of Pauli flow via matrices $M$ and $N$.
Development of $ ext{O}(n^3)$ algorithms for Pauli flow-finding.
Linking flow-finding complexity to matrix invertibility over $ ext{F}_2$.
Abstract
The one-way model of quantum computation is an alternative to the circuit model. A one-way computation is driven entirely by successive adaptive measurements of a pre-prepared entangled resource state. For each measurement, only one outcome is desired; hence a fundamental question is whether some intended measurement scheme can be performed in a robustly deterministic way. So-called flow structures witness robust determinism by providing instructions for correcting undesired outcomes. Pauli flow is one of the broadest of these structures and has been studied extensively. It is known how to find flow structures in polynomial time when they exist; nevertheless, their lengthy and complex definitions often hinder working with them. We simplify these definitions by providing a new algebraic interpretation of Pauli flow. This involves defining two matrices arising from the adjacency matrix…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Low-power high-performance VLSI design · Coding theory and cryptography
