Telecom networks power modern digital infrastructure—from everyday calls to massive data transfers. Even under normal conditions they’re difficult to maintain, and crises like equipment failures or natural disasters demand swift, effective responses.

MassOrange, a major Spanish telecommunications operator, manages a patchwork of regional and national backbones, each with multiple interconnections and redundancies. While these redundancies support service continuity, they also make the network extremely complex to optimize. Traditional tools for network optimization and resilience planning can reach their computational limits, especially for time-critical responses.

In pursuit of a more powerful approach, Cinfo, Kipu Quantum, and QuEra Computing joined forces to exploit the advantages of neutral-atom quantum computers to pre-calculate crisis scenarios. Their goal was to generate a library of optimal network reconfiguration “recipes,” enabling MassOrange to minimize outages and restore service more quickly during emergencies.

The Challenge: Increasing Network Resilience

Telecommunications operators face two major hurdles in resilience planning:

Complexity of the Network: The MassOrange network comprises multiple regional segments, each linked via extensive fiber backbones, along with several national-scale meshes. Redundancies exist between these regions but are rarely uniform or symmetric, meaning network traffic can be rerouted in countless ways. Any attempt to model the entire system grows exponentially more difficult as nodes and links increase.
Need for Rapid Crisis Responses: When a segment of the network goes down—due to a fiber cut, flood, or broader crisis—engineers must identify an optimal reconfiguration as quickly as possible. Conventional optimization methods can be slow or intractable for large, interconnected systems. Moreover, the best classical algorithms often require simplifying the problem, thereby losing valuable details about local constraints and how to reroute traffic effectively.

Historically, telecom operators have relied on pre-defined failover policies. These rules might work for smaller local disruptions, but they cannot efficiently address more complex, large-scale failures. As networks grow in size and connectivity, the classical approach becomes less scalable, risking substantial service outages and higher operational costs.

The Quantum Approach

QuEra Computing specializes in neutral-atom quantum computers, a modality where individual atoms serve as qubits. One of QuEra’s flagship machines, Aquila, is currently accessible via Amazon Braket. With up to 256 qubits in analog mode, Aquila allows users to explore emerging optimization, simulation, and machine learning algorithms at scale.

Instead of running discrete quantum gates, QuEra’s system evolves in continuous time under carefully programmed laser pulses that manipulate the qubits’ energy states. This evolution can reveal optimal or near-optimal configurations for certain problems—especially those related to combinatorial optimization.

A classic example is the Maximum Independent Set (MIS) problem:

An independent set of a graph is a subset of vertices, none of which are adjacent.
Finding the largest such subset is computationally expensive for large graphs.
Neutral-atom devices naturally solve MIS by exploiting “Rydberg blockade”—an interaction that prevents neighboring atoms from simultaneously occupying high-energy states.

Because the MIS paradigm maps well onto backbone resiliency (where each node’s adjacency represents overlapping paths), it was a natural fit for the telecom network scenario.

Building the “Toy Model”

Despite its name, the “toy model” that Cinfo, Kipu Quantum, and QuEra constructed was far from trivial. It encompassed:

46 Network Nodes to represent a portion of the regional backbone.
Multiple types of connections reflecting link capacity and redundancy levels.
Logical “gadgets,” or extra qubits introduced to replicate more complex connectivity.

Antonio Del Corral (CEO Cinfo) described the iterative process of abstracting real-world constraints into a form solvable by Aquila’s quantum hardware. Cinfo’s role was to translate the telecom engineers’ domain knowledge into a quantum-ready format, while Kipu Quantum, a member of the QuEra Quantum Alliance, handled the algorithmic mapping onto maximum independent set computations. QuEra provided the hardware infrastructure and guidance on using analog quantum advantage, working closely with the software team at Kipu Quantum.

Jan Trautmann (Head of Development at Kipu Quantum) explained that the full network could not be inserted into the quantum system at once. Instead, they partitioned the network into sub-networks, each with local connectivity patterns. For each sub-network, the MIS was found using QuEra’s device. Then, in a post-processing step, the results were merged and validated to ensure no constraints had been inadvertently violated.

These step-by-step solutions were consolidated into a final measure of network resilience. The essential metric was the size of the independent set relative to the total number of nodes (a smaller MIS fraction indicates higher redundancy).

Results & Key Insights

Validation of key concepts was a big part of the overall exercise – basically can the approach work? This encompassed several aspects as bulleted below:

Expert Verification: MassOrange’s network engineers qualitatively checked each quantum-generated solution. Although they did not maintain a classical digital twin of the entire network, they had rules of thumb and local heuristics that aligned well with the quantum output.
Performance vs. Complexity: The project validated that, even for a moderately sized sub-network (around 46 nodes), neutral-atom quantum computers can yield insight into feasible reconfiguration strategies.
Scalability: For larger networks, the problem can still be divided into smaller sub-networks. As quantum devices reach higher qubit counts, the scope of these solutions is expected to expand significantly.

The results are promising. Being able to quickly reconfigure a major telecom backbone in response to crises is a strategic advantage. The work demonstrated Quantum computing provides a potential leap in speed for evaluating thousands of “What if?” scenario. Many present-day solutions rely on partial or approximate heuristics. Quantum computing can improve these heuristics or provide new, more powerful methods—particularly when integrated in hybrid quantum–classical workflows.

It’s thought the same approach taken to backbone resiliency can apply to energy grids, transportation networks, and other critical infrastructure that require high reliability.

Next Steps — Scaling the Model

Cinfo and MassOrange plan to progressively expand the quantum-based model beyond the original 46 nodes to include more of their backbone and sub-networks, eventually reaching a production-ready solution. They believe that combining classical algorithms with quantum routines can further boost efficiency. By leveraging partial solutions or good initial guesses from classical methods, the quantum step may converge on improved or more stable solutions.

Longer-term Cinfo and MassOrange expect capitalize on advancing quantum technology. While Aquila is an analog device, QuEra’s roadmap includes digital and error-corrected quantum computers. As more qubits become available, tackling the entire network—rather than sub-problems—becomes feasible. In the meantime, Kipu Quantum’s specialized “counterdiabatic” techniques hold promise in accelerating convergence and increasing solution quality without waiting for full error correction.

Cinfo envisions employing these quantum optimization methods for other industries, such as supply-chain planning and real-time logistics. MassOrange aims to incorporate quantum-based insights into their standard operating procedures, possibly running large-scale simulations on a rolling basis to keep solution libraries up to date.

Conclusion

This pilot project between Cinfo, Kipu Quantum, and QuEra Computing demonstrates how quantum computing can offer valuable insights into telecom network resiliency. By encoding a 46-node sub-network into a form solvable by QuEra’s neutral-atom hardware, the team successfully modeled a range of failure scenarios and extracted reliable configurations for mitigating disruptions.

Although today’s quantum devices remain limited in qubit count, the near future promises expansion to thousands of qubits, likely boosting both the size and complexity of solvable network models. This project speaks to the imminent practical impact of quantum computing in sectors where speed, scalability, and precise optimization can significantly reduce downtime and operational costs.

As quantum hardware matures, both telecom and other critical infrastructure providers stand to benefit by incorporating precomputed, quantum-informed contingency plans into their standard resilience protocols.