Quantum Hackathon teams match classical solvers on satellite scheduling

A quantum algorithm run on IBM Quantum's Heron processor matched an exact classical solver on a satellite-scheduling problem covering eight satellites — but could not beat the classical solution at the problem size testable in two days. That result, produced at the UK's fifth Quantum Hackathon at the University of Warwick in 2026, is a fair snapshot of where near-term quantum computing stands for R&D teams weighing hybrid approaches: parity on small instances, with scaling arguments doing the heavy lifting.

The National Quantum Computing Centre (NQCC) organized the three-day event, which brought ten teams of graduate students and early-career researchers together with industry mentors and technology providers including IBM and Amazon Web Services Braket. Teams had two days to define a model, implement it on quantum emulators and physical processors, and generate results.

"Our industry mentors join the teams to provide specific domain knowledge and contextualize the use case, while the teams are also supported by our own applications engineers and technology providers such as IBM and Amazon Web Services BraKet," said Daisy Shearer, the NQCC's lead organizer for the event.

Can quantum warm-starts help schedule satellite fleets?

Start-up Nexorion Spacetech, founded in 2025, set the satellite-scheduling challenge. Commercial Earth-observation operators must assign imaging tasks across constellations, weighing urgency — a wildfire's leading edge outranks routine crop monitoring — against each satellite's location and trajectory. Co-founder Utsav Talekar framed the operational constraint plainly: "Exact solvers cannot return answers within the available planning window for large fleets containing dozens of satellites, so operators must rely on approximations that provide a workable solution rather than the best one."

The team built a quantum algorithm to generate a "warm-start" input for a classical optimizer, a standard technique for speeding convergence in combinatorial problems. On Heron hardware, the quantum warm start performed as well as the exact solver at the hackathon's eight-satellite scale. Co-founder Thien Bui highlighted the process over the headline number: "What was really important was the way that they improved the quantum circuit to achieve a better outcome. They really engaged with the larger scale problem, not just what can be achieved in two days."

The team also mapped stakeholder impact: faster imaging could feed emergency responders real-time disaster data, but coordinated satellite imaging raises surveillance concerns, and the team recommended acceptable-use policies and regulation from the outset. "It was clear that they had really thought about the broader implications of their use case," said Natasha Oughton, who leads the NQCC's responsible and ethical quantum computing initiative.

Nexorion reports a longer runway: the European Space Agency has selected the company to validate hybrid quantum computing for landing systems on the Moon or Mars. "These need real-time feedback to guarantee the safety of the spacecraft and the astronauts," Talekar said.

What did quantum machine learning show on EEG data?

Applied Quantum Computing (AQP), which works with healthcare customers on near-term use cases, challenged its team to predict pre-seizure brain states from EEG data. The team received 10-minute streams labelled "normal" or "pre-seizure"; AQP's Ethan Davies had pre-condensed the raw signals into features, with the team then trimming the feature set further to fit available quantum resources.

Results were mixed. Simulations suggested a quantum neural network would trail a classical model, though a last-minute run on real hardware beat predictions. A hybrid quantum-kernel method — mapping features into a richer space for classical machine learning — looked more promising and would avoid repeated calls to a quantum processor. It still failed to outperform the classical baseline, and the team recommended further work with more diverse datasets. Davies sees transfer potential: "Quantum methods like these could help to predict the outcomes of sudden events, such as the immediate effect of taking a patient off a mechanical ventilator."

Which team won, and on what economics?

The overall winners, mentored by Tech Mahindra, targeted switching off mobile transmitters during low demand. Simulating a street zone in Kensington, they found an existing classical solution could cut cell usage by up to 40%, and the classical solver won at that scale. Their case rested on scaling: classical resource requirements grow exponentially as the simulated region extends to metro areas, while the quantum algorithm's footprint scales quadratically or even linearly.

The second-placed team took the event's first music problem, testing whether quantum methods could group related melodies across an archive of more than 200,000 Irish folk records. The method met with some success; the team concluded human musicians still identify tunes better.

Judge Gerard Milburn, NQCC Quantum Fellow and University of Sussex professor, said: "I am particularly thrilled to see a use case for Irish folk music, it's so unexpected and offers a hint of how quantum computing will have an impact beyond science and technology to address wider cultural perspectives." The NQCC will look to next year's edition to test whether scaling arguments that favored quantum approaches at Warwick begin to translate into measured advantages on larger instances.