Hybrid Quantum-Classical Fraud Detection Using Gated Token Mixing Transformers and Graph-Based Evidence Subgraph Discovery for Explainable AML

GODWIN OLUWAFEMI OLAOYE

Published Jun 16, 2026• 0 citations

DOI: 10.5281/zenodo.20718302

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Hybrid Quantum-Classical Fraud Detection Using Gated Token Mixing Transformers and Graph-Based Evidence Subgraph Discovery for Explainable AML

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Published Jun 16, 2026• 0 citations

Publisher

DOI: 10.5281/zenodo.20718302

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This paper addresses the problem of finding the densest $k$ -vertex subgraph in an arbitrary graph. This problem is NP-hard and has important applications in social network analysis, fraud detection, recommendation systems, and bioinformatics. We propose two quantum approaches to solve this problem: reduction to Quadratic Unconstrained Binary Optimization (QUBO) and using Grover's quantum search algorithm. For the latter approach, we present an explicit gate-based oracle circuit utilizing Dicke states and Quantum Fourier Transform for edge counting. Numerical simulations demonstrate a quadratic speedup over classical Brute-force search.This paper addresses the problem of finding the densest $k$-vertex subgraph in an arbitrary graph. This problem is NP-hard and has important applications in social network analysis, fraud detection, recommendation systems, and bioinformatics. We propose two quantum approaches to solve this problem: reduction to Quadratic Unconstrained Binary Optimization (QUBO) and using Grover's quantum search algorithm. For the latter approach, we present an explicit gate-based oracle circuit utilizing Dicke states and Quantum Fourier Transform for edge counting. Numerical simulations demonstrate a quadratic speedup over classical Brute-force search.

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This paper addresses the problem of finding the densest

k

-vertex subgraph in an arbitrary graph. This problem is NP-hard and has important applications in social network analysis, fraud detection, recommendation systems, and bioinformatics. We propose two quantum approaches to solve this problem: reduction to Quadratic Unconstrained Binary Optimization (QUBO) and using Grover's quantum search algorithm. For the latter approach, we present an explicit gate-based oracle circuit utilizing Dicke states and Quantum Fourier Transform for edge counting. Numerical simulations demonstrate a quadratic speedup over classical Brute-force search.