Classiq, INGL, and IonQ Advance Quantum Optimization for Natural Gas Transmission Networks

quantumcomputingreport.com Sep 24, 2026

Classiq, INGL, and IonQ Advance Quantum Optimization for Natural Gas Transmission Networks

Curated by Shubham · TechCapsules · Sep 24, 2026

AI-summarised brief · reviewed before publication

Classiq Technologies and Israel Natural Gas Lines Ltd. (INGL) released joint research showing a hybrid quantum‑classical workflow that optimizes natural‑gas pipeline throughput. The study, posted on arXiv (2609.00825), formulates the pressure‑allocation problem as a Quadratic Unconstrained Binary Optimization model using a second‑degree approximation of the Panhandle‑B flow equation. A Quantum Approximate Optimization Algorithm (QAOA) was synthesized on Classiq’s platform and first validated in simulation on a six‑node, five‑edge network with 30 QAOA layers, reproducing the classical optimum. A reduced 10‑qubit instance was then run on IonQ’s Forte‑1 trapped‑ion processor with two QAOA layers, yielding physically valid pressure settings that bracketed the continuous optimum. The approach is positioned as a global‑search complement to existing hydraulic tools such as SIMONE for engineers.

💡 Why It Matters

· Demonstrating viable QAOA runs on commercial trapped‑ion hardware shows quantum processors can directly assist utility optimization, shortening the search for feasible operating points that classical methods evaluate exhaustively.

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