Quantum researchers from CSIRO, Australia’s national science agency, have demonstrated the potential for quantum computing to significantly improve how we solve complex problems involving large datasets, highlighting the potential of using quantum in areas such as real-time traffic management, agricultural monitoring, health care, and energy optimization.
By leveraging the unique properties of quantum computing, like superposition and entanglement, researchers compressed and analyzed a large dataset with speed, accuracy, and efficiency that traditional computers cannot match.
The work is published in the journal Advanced Science.
Unlike regular binary computer bits that are either “on” or “off,” quantum bits (qubits) can exist in multiple states at once, allowing quantum computers to process many possibilities simultaneously.
Dr. Muhammad Usman, a CSIRO quantum scientist and the senior author of the study, said the research team was able to demonstrate quantum machine learning can simplify large sets of data without losing important details.
“With the global volume of data doubling every few years, quantum computing’s ability to handle this complexity will become increasingly valuable,” Dr. Usman said. “Our work focused on groundwater monitoring as a case study, but quantum machine learning has broad applications in any field requiring fast, detailed analysis of large datasets.
“As practical applications for machine learning rapidly increase, we expect that integrating the tremendous computational power of quantum in machine learning will offer transformative impact in solving many industrial and real-world problems. For example, this could transform how we optimize traffic routes to minimize congestion on roads and reduce harmful emissions or process medical imaging with unprecedented accuracy to enable fast and reliable diagnosis.”
The United Nations Educational, Scientific and Cultural Organization (UNESCO) has declared 2025 the International Year of Quantum Science and Technology.
As the global race to build the first fully functional quantum computer continues, much of this focus is on developing quantum hardware platforms.
Dr. Liming Zhu, Research Director at CSIRO’s Data61, lauded the work of the quantum research team and spoke to the importance of progressing practical applications for quantum technologies.
“CSIRO’s breakthrough not only builds confidence in the benefits of quantum machine learning but also serves as a guidepost. By identifying key application performance metrics and challenges, our work helps shape the trajectory of hardware and software innovation, bringing us closer to real-world demonstrations using quantum,” Dr. Zhu said.
“UNESCO’s International Year of Quantum Science and Technology provides us with a great opportunity to promote the valuable work our scientists do as well as help others to better understand this complex field.
“Australia has been a world leader in quantum technology research and development for almost 30 years and this work adds to the pool of significant local innovations.”
More information:
Zeheng Wang et al, Self‐Adaptive Quantum Kernel Principal Component Analysis for Compact Readout of Chemiresistive Sensor Arrays, Advanced Science (2025). DOI: 10.1002/advs.202411573
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