Kathrin Spendier is the technical prize director for XPRIZE Quantum Applications, a competition focused on developing quantum algorithms to solve society’s most pressing challenges.
What is XPRIZE Quantum Applications?
XPRIZE is a 30-year-old nonprofit foundation focused on creating a world that’s equitable and abundant for everyone. We’ve launched around 30 competitions addressing the world’s biggest challenges across domains like deep tech, health, and society. Our mission is identifying barriers that prevent progress and designing audacious but achievable competitions to break through them.
The XPRIZE Quantum Applications competition is a three-year, $5 million prize focused on unlocking the future impact of quantum computing.. While it’s smaller than other XPRIZE competitions such as the $101 million XPRIZE Healthspan with human trials, it addresses a critical gap in quantum computing. We’re developing algorithms for hardware that doesn’t exist yet. It’s purely theoretical work to prepare for quantum computers that can solve major societal challenges.
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The big audacious challenge is bridging the gap between quantum computing’s promise and its practical implementation. The quantum computing community often claims that quantum computers will solve climate problems, develop new batteries, or optimize complex systems. However, it’s unclear how near-term these solutions actually are or what resources they’ll require.
The competition asks teams to develop a quantum computing algorithm to solve a real-world problem and specify exactly what resources they’ll need. This could cover things like how many qubits are needed, how deep the quantum circuits must be, and what type of quantum computer they’d use. We want hard numbers backing up these claims, not just high-level assertions. Right now, only a few carefully constructed problems have shown quantum advantage over classical methods, and even for those, it’s unclear what resources you’d need to apply them to real problems. If someone says they need a million error-corrected qubits, that level of scale remains well beyond current hardware capabilities.
There are several interconnected challenges. First, current quantum computers only have 100 to 1,000 noisy qubits. As computations proceed, errors accumulate quickly, so we can simulate most current quantum computations on classical computers. While there have been some niche demonstrations where quantum processors provided novel insights, nothing has yet addressed major societal challenges.
The algorithmic challenge is equally significant. To write a quantum algorithm, you need to understand quantum mechanics—superposition, entanglement, and interference—and figure out how to leverage these properties mathematically. This is relatively straightforward for quantum-native systems like molecular chemistry, which already use the Schrödinger equation. But for problems involving linear equations, fluid mechanics, or matrix operations, you have to translate them into a quantum framework. This translation introduces overhead in that you need more qubits, deeper circuits, and more runs, all of which add noise and complexity.
There’s also a moving target problem. Classical computing continues to improve, so the goalposts for quantum advantage keep shifting. A quantum speedup shown today might be reduced or even closed by better classical algorithms. Even when we do find quantum advantage, it often exists only in certain parameter regimes that might not align with the real-world problems we want to solve.
The competition is designed to be very open-ended. We don’t prescribe how many qubits teams should use or which quantum computing modality they should target. It could be gate-based, annealing, photonics, or another architecture. We have three submission tracks: developing new algorithms with quantum advantage that demonstrate advantage for societally important problems, applying existing algorithms to new applications, or finding clever ways to reduce the resources required to achieve advantage using known approaches.
The key is bringing together quantum algorithm developers and domain experts who understand real-world problems. Right now, these communities don’t talk enough. Quantum experts might develop algorithms with theoretical advantages that don’t map to practical problems, while domain experts might not realize where quantum computing could help overcome computational barriers. The competition aims to foster these crucial conversations and collaborations.
We currently have 224 teams from 39 countries participating. It’s an incredibly diverse group that includes individuals, undergraduate and graduate students, postdocs, university teams, startups, and entrepreneurs with varied backgrounds. The Phase I submission deadline was Aug. 1.
Teams are actively looking for members with domain expertise in areas like chemistry, biology, or imaging. We look for people who understand where real computational bottlenecks exist in their fields. Anyone interested in contributing can still explore opportunities to join existing teams by visiting our website. While joining is at the discretion of each team, the competition is designed to be as inclusive as possible. Solutions can come from anyone, anywhere on the planet.
Success would mean having clear roadmaps for quantum algorithms that can solve important societal challenges with realistic resource requirements. Instead of saying we need millions of qubits decades from now, we’d have algorithms that might work with tens of thousands of logical qubits.
This is still ambitious but achievable in a more reasonable timeframe. Most importantly, we’d have well-supported approaches where the projected quantum advantage aligns with societally important problems, whether that’s drug discovery, materials science, climate modeling, or other critical global challenges.
The competition is really about changing the conversation from “quantum computers will eventually solve everything” to “here’s exactly how quantum computers can solve this specific important problem, and here’s what we need to build to make it happen.”
