Quantum computing holds potential for breakthroughs in medicine, logistics, and finance. Current machines face a significant hurdle. They are often too small and noisy to manage the hundreds of thousands of qubits required for complex calculations. Researchers are now looking at modular quantum computing as the path forward to address these limitations.
Ivana Dimitrova, a professor of physics and electrical engineering at Northeastern University, explains that individual quantum processors struggle with scale. Linking these processors together provides more power but introduces new technical interference. These physical links often suffer from slow speeds and data errors that disrupt operations.
Supported by the U.S. Department of Energy, Dimitrova is collaborating with Hessam Mahdavifar, a professor of electrical and computer engineering, to mitigate these errors. Their two-year project focuses on creating specialized software designed to identify and correct interference within modular systems. By producing tools that catch errors, the team aims to provide the industry with a way to scale quantum hardware for large-scale problem solving.
The research project divides labor between software and hardware. Mahdavifar focuses on writing code and validating reliability through simulations. Dimitrova handles hardware integration, applying these algorithms to physical machines to test their efficacy. The first year centers on designing error-correction codes, while the second year moves into testing those designs against real-world, imperfect qubits.
Success in this area could significantly impact the intersection of quantum computing and artificial intelligence. By stabilizing modular quantum processors, researchers expect to create a more reliable foundation for advanced computation. The team intends to share their findings with the broader scientific community to encourage the adoption of practical, error-free modular systems.