Laser Process Reduces Photonics Production Costs by 50%

More than 50 percent of current photonics production costs result from painstaking manual calibration, a challenge Heriot-Watt University researchers have now addressed with a novel laser process. FreeForm Photonics is commercializing technology that builds alignment directly into optical glass components, fundamentally altering how these critical parts are manufactured. This process achieves sub-micron tolerances, a scale smaller than the width of a human hair, and promises to reduce expenses for sectors reliant on precisely assembled photonics, including quantum computing systems, medical diagnostics, and the optical communications infrastructure that supports the modern internet. “By integrating passive alignment features into the glass components themselves, we are fundamentally changing what it takes to manufacture high-performance optics,” said Dr. Calum Ross, Research Fellow at Heriot-Watt University.

FreeForm Photonics Laser Process Eliminates Manual Calibration

A new laser-based manufacturing process developed at Heriot-Watt University promises to reduce costs and complexity in the production of photonic components, a sector currently burdened by extensive manual calibration. FreeForm Photonics is commercializing technology that embeds alignment features directly into optical glass, circumventing a process that accounts for more than half of all photonics production costs. FreeForm Photonics has secured funding through Scottish Enterprise’s High Growth Spinout Programme, preparing the company for seed investment and commercial scale-up.

Derek Shaw, Director of Entrepreneurship and Investment at Scottish Enterprise, stated that FreeForm Photonics exemplifies how Scotland’s supportive innovation ecosystem can help translate research into global opportunity. With a global photonic components market nearing $1 billion and projected for substantial growth, the company is already engaging with over 100 industry leaders and potential customers, supplying trial samples to sectors including aerospace, telecommunications, and healthcare. Professor Gillian Murray, Deputy Principal for Enterprise and Business at Heriot-Watt University, emphasized the university’s role in fostering innovation, stating, “Through our entrepreneurial programmes and business support, we are working to strengthen Scotland’s innovation ecosystem and support high-growth businesses that can compete globally.”

Sub-Micron Precision Optics Enable Quantum and Beyond

The demand for increasingly sophisticated photonic systems is currently limited by manufacturing processes reliant on extensive manual calibration, which accounts for more than half of all photonics production costs. This reliance on hand-assembly creates a bottleneck for scaling production in critical areas like quantum computing, medical diagnostics, and the optical communications networks that support modern infrastructure. A new laser-based process developed at Heriot-Watt University directly addresses this challenge by embedding alignment features into optical glass components during manufacturing, effectively eliminating the need for post-production calibration. This advancement offers benefits beyond cost reduction, promising to accelerate development cycles and improve the reliability of complex photonic systems. FreeForm Photonics.

FreeForm Photonics is a great example of how Scotland’s supportive innovation ecosystem system can help turn cutting-edge research into global opportunity.

Derek Shaw, Director of Entrepreneurship and Investment at Scottish Enterprise
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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