Shaping UK quantum innovation with Qiskit Machine Learning

The Hartree Centre is leading the development of Qiskit Machine Learning to support the UK’s growing quantum computing capabilities.

We’re playing a unique role in shaping the UK’s quantum future. One of the most exciting parts of this work is our leadership of the Qiskit Machine Learning library, a rich software library backed by a thriving global community of quantum software developers and users. By developing and maintaining this open-source library, we’re helping to create tools that researchers and businesses around the world use every day. And just as importantly, we’re making sure the UK is not only ready for quantum computing but actively shaping its direction.

What is Qiskit?

Qiskit is IBM’s open-source software development kit for quantum computing. Today, it’s one of the most widely used ways to design, test and run quantum algorithms. Qiskit interfaces with Python and sits above the hardware stack layer, meaning users can focus on building algorithms rather than worrying about the low-level details of controlling qubits (the basic information units of a quantum computer).

As the ecosystem has grown, Qiskit has expanded to include application-focused modules for quantum chemistry, optimisation and quantum machine learning (QML) built on top of the core software development kit (SDK). These libraries make it easier for users to explore specific application areas and build prototypes without needing to design everything from the ground up.

Our role in Qiskit Machine Learning

In January 2024, the Hartree Centre took over the role of developing and maintaining the Qiskit machine learning application library. As expert partners, we are in an excellent position to drive this effort forward.

Today, the Hartree Centre is one of the few organisations globally that own and maintain such a mature, modular, extensible toolkit that integrates a Qiskit library smoothly with popular AI frameworks like PyTorch and scikit-learn. Qiskit Machine Learning includes quantum kernels, quantum neural networks, and other variational algorithms, all designed to help users experiment with workflows that combine quantum and machine learning resources.

The result is that researchers and industry users can test QML ideas quickly, without needing to understand the full depth of quantum information theory. It lowers the barrier to entry, speeds up experimentation, and gives organisations a practical way to explore whether QML might one day boost their existing workflows. At the same time, it exposes advanced features that allow QML experts to customise their workflows with quantum error mitigation and suppression. Additionally, it enables a tight algorithm integration with ongoing hardware improvements that pave the way towards fault-tolerance.

Connecting to the UK’s National Quantum Strategy

Our work with Qiskit Machine Learning also aligns with the UK’s wider ambitions. The Government’s National Quantum Strategy commits £2.5 billion to building sovereign capability in quantum technologies over the next decade. As part of STFC, the Hartree Centre plays a national role in making sure that businesses and researchers can actually use and benefit from emerging quantum tools.

Maintaining open-source software like Qiskit Machine Learning is a tangible way of doing that. It gives the UK a strong voice in the development of key quantum software infrastructure, supports the skills pipeline, and ensures that industry can begin experimenting even before large-scale fault-tolerant quantum computers arrive.

Why this matters for industry

QML is still an emerging field, but organisations exploring AI are already starting to ask what quantum might mean for them. Qiskit Machine Learning provides an accessible tool to start looking into that question.

For businesses, it enables rapid prototyping, experimentation with hybrid workflows, and early assessment of where quantum might help, and where it might not. It also provides a way to build internal understanding and capability, something many organisations are now recognising as essential for long-term competitiveness.

Importantly, it supports evidence-based decision-making. Not every problem will benefit from quantum approaches, and Qiskit Machine Learning lets companies explore this without needing specialist knowledge or expensive tools and resources. Meanwhile, our upskilling opportunities and expertise help teams build the skills they need to navigate the emerging quantum computing landscape.

Collaborations and community leadership

Our work on Qiskit Machine Learning sits within a much wider network of national and international partnerships that help shape how quantum computing evolves and how the UK benefits from it.

At home, we collaborate with a broad mix of universities, research institutes, and industry partners who are exploring practical quantum use cases. These collaborations ensure that the tools we build address real scientific and industrial challenges, not just theoretical models, and that UK organisations can influence how quantum software matures.

Internationally, we work closely with leading quantum technology providers. Through our role as an IBM Quantum Innovation Centre, UK researchers and businesses gain priority access to cutting-edge quantum hardware and software. Our work with other hardware partners, such as Quantinuum and PsiQuantum, helps us understand the needs of different quantum platforms and prepare UK users for the technologies that are coming next, from today’s noisy devices to tomorrow’s fault-tolerant systems.

We also remain deeply embedded in the global Qiskit community. Our team contributes code, shapes roadmaps, supports users on GitHub, and shares expertise through tutorials, workshops, and conferences. This open-source engagement is a big part of what makes the library stronger: Community feedback drives improvements, and our involvement helps ensure the UK has a visible, influential voice in the future of quantum software.

Looking ahead

We see a long-term future for this library. Qiskit Machine Learning has been cited well over 200 times since we took over the role of development and maintenance, and the community is growing fast. By guiding its roadmap, engaging directly with users, and contributing new capabilities, we’re helping shape how QML evolves globally.

QML represents one of the most exciting frontiers in quantum computing. By leading the development of Qiskit Machine Learning, the Hartree Centre is helping ensure that the UK doesn’t just adopt quantum technologies, it helps build them.

Whether you’re a researcher exploring new quantum models or an organisation starting to think about future AI workflows, Qiskit Machine Learning provides a powerful, accessible way to begin the journey. And we’re here to help every step of the way.