Who We Are
Quantum@C3 (or QC3) is a research initiative affiliated with the Center for Computational Sciences (C3) at the Federal University of Rio Grande (FURG), dedicated to Quantum Computing and Quantum Machine Learning. The initiative emerged from FURG's participation in the development of the international IEEE/ACM/AAAI CS2023 curriculum, which introduced a new knowledge unit entitled Quantum Architectures within the Computer Systems Architecture area. This effort paved the way for research on hybrid classical–quantum computer system architectures. Today, Quantum@C3 brings together researchers and students engaged in research projects and international collaborations. Its activities focus on the Data-Centric Quantum Machine Learning approach and distributed quantum systems.
Research in Quantum Computing Systems
Quantum@C3 investigates methods and applications of quantum computing systems aimed at industrial and scientific problems. The team develops research projects in anomaly detection, cyber-physical system monitoring, point-to-point quantum communication, and intelligent environments. The initiative is still in its incubation stage and is focused on producing preliminary research results. Current projects investigate the limitations of today's quantum devices, including noise, decoherence, and the limited availability of qubits. Based on these research challenges, the group has proposed methods founded on the concept of Data-Centric Quantum Machine Learning (DC-QML), recently developed within Quantum@C3, with an emphasis on the relationship between data, quantum encoding, and algorithm performance.
Research in Data-Centric Quantum Machine Learning
This is one of the main research areas of Quantum@C3. This approach investigates how data quality, representation, and encoding influence the performance of quantum algorithms. The initiative has been studying both the advantages and the limitations of the DC-QML approach. Currently, the focus is on developing methods that expand the practical application of Quantum Machine Learning (QML) on quantum processing units (QPUs).
