Classiq and INGL run gas-network optimisation on IonQ Forte-1

Classiq and Israel Natural Gas Lines (INGL) have published results from a collaborative research programme exploring whether quantum optimisation can improve transmission planning for natural gas pipeline networks. A reduced version of the problem was executed on IonQ's Forte-1 trapped-ion quantum processor via the Classiq platform, with full technical results available in a preprint on arXiv.

The research targets a practical engineering challenge: identifying valid pressure and flow configurations across a pipeline network while respecting physical constraints such as supplier pressure, pipe characteristics and minimum customer delivery pressure. As networks scale, the number of possible configurations grows rapidly, making exhaustive classical search computationally expensive. The project examined whether quantum optimisation could narrow the candidate space more systematically, giving engineers a stronger set of starting points for detailed hydraulic validation.

What the research found

In simulator-based testing on a representative gas network, a hybrid quantum-classical workflow developed on the Classiq platform identified the maximum-throughput valid operating point, a result consistent with classical reference solutions. The team then executed a version of the problem on IonQ Forte-1, where the system produced physically valid candidate operating points close to the classical optimum.

The collaboration also examined integration with SIMONE, a hydraulic modelling environment used in the gas industry. In this framing, quantum optimisation surfaces promising planning options that engineers then validate through established hydraulic modelling before any operational conclusion is drawn. Neither Classiq nor INGL described the work as a production deployment; the stated goal is medium-term implementation readiness.

Nir Minerbi, co-founder and chief executive of Classiq, said the work was designed to operate "in a language oil and gas teams recognise: pressure, flow, constraints and validation," rather than as an abstract demonstration. Scott Millard, chief business officer at IonQ, characterised hardware execution on Forte-1 as a practical way to evaluate how quantum computing could contribute to complex planning challenges in the energy sector.

Market and standards context

The energy sector is among the more credible near-term application areas for quantum optimisation, alongside logistics, financial portfolio optimisation and drug discovery. Pipeline network planning shares structural characteristics with other constraint-satisfaction and combinatorial problems that quantum approaches such as the Quantum Approximate Optimisation Algorithm (QAOA) and variational methods are designed to address. However, the field remains at an early stage: demonstrating advantage over best-in-class classical solvers on full-scale industrial instances has not yet been achieved by any vendor.

IonQ's Forte-1 is a commercial trapped-ion system; trapped-ion architectures offer high gate fidelity but relatively low qubit count compared with superconducting alternatives from IBM and Google. The reduced problem scale used in the INGL research reflects that constraint. As hardware roadmaps extend qubit counts and improve error rates, the practical scope of problems amenable to hardware execution is expected to grow.

INGL is a government-owned company responsible for Israel's national natural gas transmission infrastructure, which adds a degree of regulatory and operational rigour to the collaboration. The research reflects a broader pattern in which national energy operators engage with quantum software vendors on pilot programmes ahead of any anticipated commercial deployment, building internal knowledge while hardware matures.

The arXiv preprint provides the full mathematical formulation, quantum optimisation methodology, simulator results and hardware execution details for independent review.