TORONTO, Canada, Oct 9, 2026 – Xanadu Quantum Technologies (Xanadu) has partnered with GlobalFoundries (GF) to develop and manufacture photonic quantum computing components through GF’s 300 mm production line. The initial work will focus on industrializing Xanadu’s superconducting nanowire single-photon detectors and ultra-low-loss silicon nitride (SiN) photonics platform.
The collaboration combines Xanadu’s photonic design and process development expertise with GF’s manufacturing capabilities. Xanadu expects the work to provide a manufacturing foundation for its upcoming fault-tolerant demonstrators, supporting its goal of supplying hardware architectures for quantum data centers.
In photonic quantum computing, photons carry information. Reading calculation outputs requires photon number resolving detectors, which determine how many photons are present in a single light pulse. Xanadu has adopted Superconducting Nanowire Single-Photon Detectors (SNSPDs) for that function in its utility-scale systems.
Xanadu expects SNSPDs to increase computing speed and reduce the chip overhead required by its architecture. The company combines these detectors with SiN photonics used as optical circuit boards. Xanadu describes the detectors as highly efficient and the SiN components as guiding photons across a range of wavelengths with negligible signal loss.
“Transitioning quantum computing technology to a high-volume manufacturing line is fundamental to delivering quantum computing at scale,” said Dr. Christian Weedbrook, founder and chief executive officer of Xanadu. “Partnering with GlobalFoundries allows Xanadu to refine and scale up our existing industry-leading photonics platform and apply GF’s industrial expertise and technology to our photonic chip production. This partnership demonstrates our focus on execution and seeks to provide the reliable, precision-manufactured infrastructure necessary to transition quantum technology from the research environment to commercial-scale data centers.”
“By combining Xanadu’s advanced photonic computing technology with GF’s 300 mm manufacturing expertise, this partnership creates a path to industrialize the critical components needed to accelerate the deployment of fault-tolerant systems and enable future quantum computing architectures,” said Nicholas Sergeant, VP of Quantum Technology Solutions at GF.
The companies are also exploring additional work on quantum modules to increase the capabilities of photonic quantum computing systems.
Source: GlobalFoundries
About GlobalFoundries
GlobalFoundries is a semiconductor foundry that provides advanced manufacturing services for integrated circuits. It offers a range of technologies, including CMOS, RF, embedded memory, silicon photonics, and FinFET, catering to automotive, communications, defense, data center, industrial, and consumer electronics applications. Founded in 2009 after being spun off from AMD, GlobalFoundries has over a decade of experience delivering tailored semiconductor solutions. The company supports fabless chipmakers with design enablement, IP services, and process technologies to accelerate innovation and meet global demand. Headquartered in Malta, New York, it operates manufacturing sites in the U.S., Germany, and Singapore. The company develops technologies for emerging markets, supporting digital applications that demand energy efficiency and reliable performance.
About Xanadu
Xanadu develops photonic quantum computers and software for quantum research. It was founded in 2016 and is headquartered in Toronto, Canada. It’s hardware uses photons, or particles of light, to process quantum information. Named systems include Borealis and Aurora. The company also develops PennyLane, open-source software for quantum programming. Researchers use it for quantum computing, machine learning and chemistry applications. Xanadu offers Catalyst, a compiler for quantum and classical computing workflows. Its collaborations address aerospace, finance, chemistry and materials research. Examples include jet-engine airflow simulations and quantum algorithms for materials and chemistry problems.
