Qpurpose is part of a large and growing community involved with quantum computing which includes partners from both industry, governments and research centres. We highlight two of our major industry partners:

Novo Nordisk

- Preparing for future quantum computing advancements in pharma. Novo Nordisk works together with Qpurpose and the Centre for Quantum Mathematics at SDU to explore the use of quantum mathematics and, as the technology matures, quantum computing. Quantum computing has the potential to tackle problems that classical computers cannot, significantly improving the lives of individuals with chronic diseases.

”We are excited to enter this collaboration with Novo Nordisk and look forward to advancing the application of quantum technology in healthcare. With our expertise in quantum mathematics and algorithms, we have already made strides in sectors such as energy and finance, and we are eager to explore their potential in the pharmaceutical industry alongside Novo Nordisk" says Jørgen Ellegaard Andersen, Centre Director and CEO of Qpurpose.

Jyske Bank

- Quantum-Optimised Real-Time Trading in finance. Qpurpose delivers quantum and quantum-inspired solutions that enhance real-time trading and risk management together with Jyske Bank. Our solution, Qpurpose Price Predator, is fully integrated into the bank’s IT systems and used by traders across approximately 300 equity classes, providing near-term price predictions and decision support for trade execution.

Developed through a close, multi-year collaboration with Jyske Bank, the solution combines deep industry insight with advanced quantum methodologies to address real-world trading challenges and deliver measurable value in live market conditions.

Proven results:

• 5x improvement in accuracy: ~2 basis points deviation vs. ~10 for conventional approaches
• Validated at scale: Deployed across 300 equities in real trading environments
• Operational robustness: Stable performance over several months with zero downtime

By leveraging techniques such as Gaussian Boson Sampling as an alternative to Monte Carlo methods, the platform enables faster, more precise financial modeling.

Read more in the at page 44:

https://dqc.dk/wp-content/uploads/2024/12/16-Danish-Quantum-Use-Cases-December-2024.pdf

Further industry partners include:

Ørsted, ATP, Amazon, COWI, DMI, Kamstrup, KPMG, Mærsk, NVIDIA & Trifork.

Quantum computing hardware partners

Quantinuum

Quantinuum and Qpurpose are jointly exploring the application of Quantinuum’s advanced quantum computing capabilities to demonstrate quantum advantage in low-dimensional topology, specifically by performing Topological Quantum Field Theory (TQFT) computations beyond the reach of classical systems, while also investigating the error-correction properties of various TQFT-based codes.

Pasqal

Qpurpose and Pasqal are collaborating to reformulate permutation-based optimization problems as Maximum Weight Independent Set (MWIS) instances tailored to Pasqal’s neutral-atom quantum platform, with the aim of developing quantum-native solutions to real-world industrial optimization challenges.

Atom Computing

In collaboration with Atom Computing, QM and Qpurpose are working to implement important quantum algorithms in topological quantum computing on the powerful neutral-atom platform provided by Atom Computing. The relevant algorithms are BQP-complete, and their implementation will enable researchers to probe longstanding conjectures in mathematics. The project has deep connections to schemes for universal fault-tolerant quantum computing based on TQFT gates. In particular, it is closely related to topological error-correcting codes and the mathematical aspects of topological phases of matter. Part of the project involves rewriting the quantum algorithms in terms of the native gate set of neutral-atom processors, where the controlled-Z gate is the essential two-qubit building block.

IBM

In collaboration with IBM, we are developing quantum algorithms for solving partial differential equations (PDEs). In earlier work, we focused on the advection–diffusion equation, aiming to construct quantum circuits that are implementable on near-term hardware, particularly IBM’s superconducting quantum devices. Our approach is based on the quantum singular value transformation in combination with efficient block-encodings of high-order finite-difference approximations of spatial derivatives. A key objective is to assess the extent to which higher-order methods outperform their lower-order counterparts in a quantum computing setting.

Further quantum hardware partners include:

Microsoft, Orca Quantum & Quandela