IonQ and Partners Demonstrate 14.6 Percent Quantum-Accelerated Performance Gain in Computer-Aided Engineering Workloads Using Trapped-Ion Hardware on September 17

IonQ, Synopsys, and NVIDIA announced on September 17 that they have successfully demonstrated quantum-accelerated performance gains in large-scale Computer-Aided Engineering workloads, achieving a 14.6 percent improvement via trapped-ion hardware. The collaboration leveraged IonQ's trapped-ion quantum computing systems, which deliver gate fidelities above 99.99 percent on single-qubit operations and above 99.9 percent on two-qubit operations, capabilities that superconducting systems have not matched at comparable qubit counts. Separately, Oxford Quantum Circuits released Erado on September 17, an open-source Qiskit simulator for erasure noise and post-selection integrated into their Quantum Computing as a Service SDK. Q-SAFE Solutions unveiled a carrier-grade quantum-safe network platform in the EU-27 on the same day, integrating Quantum Key Distribution and Post-Quantum Cryptography with centralized hybrid key management over existing fiber-optic infrastructure, designed for telecommunications providers, critical infrastructure, and government agencies. IQM Quantum Computers announced it is expanding into South America by selling an on-premises IQM Spark system to Brazil's Eldorado Research Institute, set for deployment in Q1 2027, marking the first quantum computer acquisition by a private research institution in Brazil. Quantum Computing Inc. announced it will demonstrate an integrated quantum security platform combining quantum key distribution with hardware-based Quantum Identity Authentication at the ECOC Exhibition 2026 from September 21-23 at FYCMA in Málaga, Spain, marking the first live demonstration of encryption and authentication integrated on a single platform. This matters because the IonQ-Synopsys-NVIDIA demonstration represents the first publicly disclosed quantum acceleration of a production-scale CAE workflow, moving quantum utility out of academic benchmarks and into engineering tools that enterprises already use. A 14.6 percent performance imp