The Technology Innovation Institute (TII), a global scientific research centre and the applied research pillar of Abu Dhabi’s Advanced Technology Research Council (ATRC), has announced a key advancement in quantum computing with the development of a new quantum optimisation solver. The work makes significant strides toward the practical application of quantum computers by demonstrating how large-scale, combinatorial optimisation problems can be addressed using just a few quantum bits (qubits).
This milestone marks the first-ever, successful demonstration of a quantum solver for an optimisation of over 7000 variables and encoded using only 17 qubits, setting a new standard for the capability of quantum computers to handle large optimisation problems.
The research findings are detailed in a study published in Nature Communications, January.
A framework for practical quantum computing
The quantum solver is a hybrid quantum-classical algorithm based on a novel encoding scheme that leverages qubit correlations to maximise the use of quantum resources. This allows the efficient encoding of thousands of binary variables into a much smaller number of qubits while maintaining a high solution quality. The approach also reduces the computational overhead associated with quantum optimisation by mitigating the effects of barren plateaus during model training.
“Our work tackles several challenges that have historically limited the applicability of quantum solvers,” explains Marco Sciorilli, lead author of the abovementioned study and Associate Researcher at TII. “By introducing a scalable encoding method, we have shown that complex problems can be addressed even with the hardware constraints of today’s quantum devices.”
The method was tested on benchmark graph problems known as Maximum Cut that are provably hard to solve, and which have applications in network design and resource allocation. Results indicated solution qualities comparable to state-of-the-art classical methods, even exceeding them in some examples.
Collaborative research to advance global expertise
While TII stands at the forefront of building a quantum computer in the region, this research builds on collaborative efforts involving TII’s Quantum Research Centre and international partners, including NVIDIA, Los Alamos National Laboratory, and Caltech. The collaboration combined theoretical insights and experimental validation using commercially available quantum devices, leveraging expertise across diverse fields.
‘’This advancement demonstrates the critical importance of international collaboration in quantum science,’’ says Dr. Leandro Aolita, Chief Researcher of Quantum Research Centre. ‘’It reflects our commitment to bridging theoretical research and practical applications, ensuring that Abu Dhabi continues to contribute to cutting-edge, global innovation.’’
Broad applications across key industries
Optimisation problems are foundational in a wide range of industries, including supply chain management, energy grid optimisation, and financial modelling. Traditional approaches to these problems require immense computational resources, making them impractical for large-scale applications. The new quantum solver introduces a potential approach that, with further development, could provide a pathway for addressing these limitations in the future.
By encoding optimisation variables into a small number of qubits, the method reduces the resources required for computation, without compromising on accuracy or scalability. The research also highlighted the solver’s ability to function effectively without requiring extensive quantum error mitigation, enhancing its feasibility for near-term deployment.
A future path for quantum research
TII’s Quantum Research Centre is now exploring the next steps to build on this milestone. Planned areas of focus include expanding the solver’s application to broader classes of optimisation problems, as well as integrating it with classical algorithms for enhanced performance. The team is also investigating how these quantum techniques can inspire the development of improved classical solvers that can provide near-term benefits, while the hardware for quantum computing continues to evolve.
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