Rigetti and Algorithmiq announced today, February 20, 2026, that they are partnering to fight financial fraud using quantum machine learning. The partnership focuses on anomaly detection, a key technology for preventing fraudulent transactions, and aims to improve the performance of hybrid quantum-classical methods for digital payment systems. A key component of this project includes implementing a new adaptation of Algorithmiq’s Tensor network error mitigation on Rigetti’s 36-qubit quantum computer hosted at the UK’s National Quantum Computing Center (NQCC). “We look forward to pushing the boundaries of what is possible with current quantum hardware, while deepening our understanding of the integration of advanced error mitigation solutions with quantum computers,” Righetti said. This research is supported by a newly awarded proof of concept project in the 2025 STFC Cross-Cluster Proof of Concept: SparQ Quantum Computing Call.
Advances in hybrid quantum anomaly detection with Rigetti and Algorithmiq
Quantum machine learning is now being applied directly to financial data by Righetti, with a particular focus on enhancing anti-fraud techniques. The company is collaborating with Algorithmiq to refine its hybrid quantum-classical anomaly detection method, with the aim of enhancing digital payment systems and accelerating adoption within the broader digital economy. This partnership is an important step toward realizing the practical application of quantum computing in the financial sector.
Mitigating Tensor Network Errors on 36-qubit NQCC Computers
Righetti is currently focusing his research efforts on applying quantum machine learning techniques to analyze real financial datasets. A key element of this research includes collaboration with Algorithmiq to improve hybrid quantum-classical methods for anomaly detection, a key tool for preventing financial fraud. The companies specifically aim to improve fraud detection systems and leverage Algorithmiq’s new implementation of Tensor network error mitigation to accelerate the adoption of quantum-enhanced digital payment solutions. This integration of advanced error mitigation capabilities aims to take full advantage of the capabilities of existing quantum hardware and will provide a deeper understanding of how these solutions can be combined with Righetti computers.
At Rigetti, we focus on applying quantum machine learning to real-world financial data.
Righetti
