BlueQubit and its research partners have received U.S. Department of Energy Genesis Mission grants totaling $1.5 million to advance artificial intelligence-based quantum error correction.
The projects will bring together BlueQubit, Microsoft, Argonne National Laboratory, Sandia National Laboratories, UC San Diego, UC Riverside, the University of Maryland, the University of Southern California and Virginia Tech.
The teams will use AI, machine learning and high-performance quantum simulation to address two major barriers to fault-tolerant quantum computing: the large number of physical qubits needed to create reliable logical qubits and the time required to detect and correct errors.
Quantum computers are highly sensitive to noise, which can disrupt calculations before useful work is completed. Quantum error correction uses additional qubits and software to identify and repair those errors, but current approaches can require substantial hardware resources.
BlueQubit and its partners plan to develop more efficient error-correcting codes and faster decoding systems. Decoders analyze measurements from a quantum processor and determine which corrective actions should be applied.
The initiatives will combine AI-driven code optimization with physics-informed decoder models designed around the limitations of real quantum hardware.
Reducing qubit overhead could allow useful quantum systems to operate with fewer physical components. Lower decoding latency could also help processors correct errors quickly enough to prevent them from accumulating during complex calculations.
BlueQubit believes improvements in reliability and scalability could move quantum computing closer to practical applications in pharmaceutical research, advanced materials, defense and financial risk modeling.
The company develops quantum algorithms and applications using processors from IBM, Quantinuum and QuEra. It also uses classical simulation infrastructure powered by NVIDIA graphics processing units to test quantum workloads.
KEY QUOTE:
“Unlocking practical quantum advantage requires bridging the gap between theoretical error-correcting codes and real-world hardware constraints.”
“These awards highlight the vital role of AI-driven co-design and high-fidelity simulation in solving quantum computing’s toughest engineering challenges. We are thrilled to partner with world-class national labs and universities to build the software foundations for scalable, fault-tolerant quantum hardware.”
Hrant Gharibyan, CEO of BlueQubit
