Inside IQM: 3 Questions for... Dr Ulrich Meier

As part of our “3 Questions” series, we spoke with Dr Ulrich Meier of IQM Quantum Computers. Dr Meier studied quantum chemistry before a dedicated quantum computing industry even existed. His work has covered performance benchmarking, system architecture, and market development. At IQM, he brings these two worlds together, helping supercomputing centres and enterprises integrate quantum systems into their existing HPC environments. 

In this interview, he explains the milestones on the path towards fault-tolerant quantum computing, the architectural and economic hurdles that still need to be overcome, and the use cases most likely to demonstrate meaningful quantum advantage.

1. What do you see as the most decisive milestones on the path toward scalable, fault-tolerant quantum computing systems?

One of the most decisive milestones is the development of more efficient quantum error-correction methods. Fault-tolerant quantum computing depends on the ability to create logical qubits that can perform reliable computations despite errors occurring at the level of physical qubits. The efficiency of the underlying error-correcting code therefore has a direct impact on the number of physical qubits required to build useful quantum systems.

IQM’s engineers and scientists recently achieved a breakthrough in error-correction efficiency by applying Barbell Codes, a particularly effective variant of quantum low-density parity-check (qLDPC) codes. Combined with IQM’s Constellation Architecture, Barbell Codes have the potential to significantly reduce the physical-qubit overhead required for fault-tolerant quantum computing compared with conventional Surface Codes.

Building on this direction, IQM and its academic collaborators have also begun exploring directional tile codes, a new family of error-correcting codes designed to further improve logical performance on near-term quantum hardware. Early results indicate that these approaches could reduce logical error rates by up to three orders of magnitude under suitable conditions.

These developments illustrate IQM’s broader strategy: error-correcting codes and quantum processor architectures should be designed together. Rather than treating code selection and processor development as separate challenges, IQM is pursuing a co-design approach that aligns hardware architecture, connectivity, and error-correction requirements from the beginning.

This direction supports IQM’s published technology roadmap and its goal of reaching fault-tolerant quantum computing by the beginning of the next decade.

2. What are the key technological and architectural hurdles that still need to be overcome to make fault-tolerant quantum computing viable at scale?

Scaling quantum processors to substantially higher qubit counts requires moving beyond conventional single-chip QPU designs. A key architectural step is therefore the transition towards a chiplet-based approach, in which multiple smaller quantum chips are integrated into a larger processor system.

IQM’s in-house test devices have demonstrated that logical gate fidelity between chiplets can match the performance of operations performed on a single chip. This means that chiplet integration does not introduce additional noise while providing a path towards greater scalability.

The chiplet approach also improves manufacturing yield. Instead of producing and testing an entire large-scale QPU as a single unit, individual chiplets can be characterised before final assembly. This makes it possible to identify components that do not meet specifications at an earlier stage and improves the overall efficiency of the manufacturing process.

However, scalability is not only a question of fidelity and yield. Reducing the bill-of-materials (BOM) cost per qubit remains a central engineering challenge for utility-scale quantum computing. Today, major cost drivers include cryogenic wiring, control electronics, and advanced packaging. Without architectural changes, these factors scale unfavourably as quantum processors grow.

The chiplet approach contributes to a more sustainable cost trajectory by enabling modular fabrication and testing at the chiplet level, improving yield economics and allowing mature fabrication processes to be leveraged as systems scale. Addressing these cost drivers remains a key engineering priority for future quantum systems.

As a full-stack quantum computing company with in-house capabilities covering chip design, chip testing, chip fabrication, and complete system engineering, IQM is working to address both major dimensions of the challenge: maintaining high fidelity as processors scale and reducing the cost of each additional qubit.

3. Which types of use cases are currently the most realistic candidates for demonstrating meaningful quantum advantage in the next phase of development?

The most realistic near-term candidates for demonstrating meaningful quantum advantage share a common architectural pattern: hybrid workflows in which a quantum algorithm operates as a specialised kernel within a broader, predominantly classical computational process.

This approach is more realistic than expecting a quantum computer to solve a complex industrial problem entirely on its own. In a hybrid workflow, the quantum component only needs to outperform a specific classical subroutine rather than replace the complete end-to-end application. This lowers the requirements in terms of qubit count, circuit depth, and hardware fidelity, making early demonstrations of quantum advantage more achievable.

Quantum chemistry and materials science are among the most mature application areas for this model. IQM’s acquisition of the assets of Berlin-based Quantistry GmbH shortly after its public listing on Nasdaq and the Nordic Stock Exchange reflects IQM’s assessment that quantum chemistry is particularly well positioned to become one of the first areas to demonstrate meaningful quantum advantage.

Within this domain, materials science and the life sciences – particularly drug development – are expected to be among the first industrially relevant application areas. The combination of quantum computing and artificial intelligence could further accelerate progress by connecting quantum simulations with AI-supported prediction, optimisation, and analysis.

Optimisation is another important near-term candidate. IQM has already demonstrated the hybrid-kernel approach in practice. In one research project, the Quantum Approximate Optimisation Algorithm (QAOA) is not used as a standalone solver. Instead, it provides expectation values that guide a classical greedy algorithm for solving combinatorial problems such as the Maximum Independent Set problem.

This approach was demonstrated experimentally on IQM’s superconducting quantum hardware. Even at shallow circuit depths, the hybrid method outperformed purely classical baselines, showing how a quantum processor can contribute targeted computational value without having to perform the complete computational workload.

A second research project applies QAOA to rolling stock planning, a real-world scheduling problem in the transport sector. This demonstrates how the same hybrid-kernel principle can extend beyond theoretical optimisation problems to industrially relevant logistics and planning applications.

Together, these results indicate a scalable path towards quantum-enhanced solutions on early fault-tolerant hardware. In this model, the quantum processor performs carefully selected tasks where it can provide computational value, while classical systems continue to manage the surrounding workflow, data processing, and decision-making.

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