EPB and IonQ Deploy Hybrid Trapped-Ion Algorithms on Forte Enterprise to Optimize Power Grid Topology

Municipal utility EPB, in partnership with IonQ, has released experimental findings demonstrating the efficacy of hybrid quantum-classical algorithms for power grid management. Supported by a $4 million grant from the National Institute of Standards and Technology (NIST), the research project was conducted at the EPB Quantum Center in Chattanooga, Tennessee, using an on-premises IonQ Forte Enterprise trapped-ion quantum system.

The study focused on addressing the complexities of Distribution Network Reconfiguration (DNR), a mixed-integer nonlinear programming challenge. The research teams implemented three distinct computational frameworks: Quantum-Enhanced Deep Reinforcement Learning (Q-DRL), Subspace LR-QAOA with a guided MISOCP solver, and Warm-Start Iterative Quantum Imaginary-Time Evolution (QITE). These methods aimed to minimize resistive dissipation and optimize power grid topology while bypassing the barren plateaus typical of conventional quantum approaches.

Experimental benchmarks on the IonQ Forte Enterprise system demonstrated that quantum-assisted pipelines could effectively guide classical power flow engines toward low-loss configurations. The research highlighted an empirical threshold on a 417-bus network where quantum-derived variable hints began to offset circuit compilation and latency, marking a significant step toward practical utility deployment of quantum algorithms.

Source: quantumcomputingreport.com
Publication date: 29.10.2026