EUV Laser Maker Trumpf Experiments With Quantum Computing to Design Next-Gen Lasers

A German project funded with ~€1.8M will test whether quantum algorithms can outperform supercomputers in modeling CO₂ lasers for chipmaking.

German laser specialist Trumpf, whose CO₂ laser systems are critical components in ASML’s EUV and advanced DUV lithography tools, has launched a project to explore quantum computing as a design tool for high-end industrial lasers. 

Who’s involved and why it matters

According to reporting from Tom’s Hardware, Trumpf is partnering with:

• the Fraunhofer Institute for Laser Technology (ILT),

• and the Dahlem Center at Freie Universität Berlin,

with funding of roughly €1.8 million from Germany’s Federal Ministry of Education and Research. 

The goal is to check whether modern quantum computers can simulate CO₂-laser physics more efficiently than classical supercomputers – a big deal for:

• EUV and DUV lithography,

• industrial materials processing,

• and silicon photonics for high-speed connectivity. 

Why simulate lasers on a quantum computer?

CO₂ lasers involve a lot of intrinsically quantum-mechanical processes:

• vibrational and rotational energy levels in molecules,

• complex collision dynamics,

• and population inversion in multi-level systems. 

Classical supercomputers can only handle these by heavy approximations, because fully representing a many-body quantum system requires storing an exponentially large state space. Quantum computers, in principle, can encode these quantum states natively using qubits, potentially enabling: 

• more accurate simulations of energy transfer and gain in the laser medium,

• faster optimization of cavity design and operating parameters,

• and ultimately more efficient, stable, and powerful CO₂ lasers.

First steps of the project

The initial phase focuses on: 

• translating existing laser-physics models into forms suitable for quantum algorithms,

• benchmarking early quantum implementations against current classical simulations,

• and identifying sub-problems where quantum hardware offers a realistic advantage.

Because today’s quantum computers are still noisy and small-scale, the short-term goal is know-how and algorithm development rather than immediate industrial deployment. But if the approach works, it could become a blueprint for using quantum computing as a meta-tool to design critical hardware for the semiconductor industry itself.