Outlier Detection and other applications of Quantum Matrix Multiplication
Giacomo Antonioli, Alessandro Berti, Alessandro Poggiali, Anna Bernasconi, Gianna M. Del Corso · 2025
This work explores the potential of Quantum Matrix Multiplication (QMM) to accelerate several computational tasks, demonstrating substantial speedups. We present three distinct applications showcasing QMM’s versatility and efficiency. We introduce a novel Hybrid-Quantum Angle Based Outlier Detection (H-QABOD) algorithm, leveraging QMM to efficiently identify outliers in numerical datasets. We evaluate H-QABOD’s performance on both synthetic and real-world datasets, benchmarking it against its classical counterpart. Furthermore, we investigate QMM’s application within quantum linear algebra, specifically for multitrace estimation and Frobenius norm computation.