Disentangling Hype from Practicality: On Realistically Achieving Quantum Advantage
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Abstract (arXiv)
Quantum computers offer a new paradigm of computing with the potential to vastly outperform any imagineable classical computer. This has caused a gold rush towards new quantum algorithms and hardware. In light of the growing expectations and hype surrounding quantum computing we ask the question which are the promising applications to realize quantum advantage. We argue that small data problems and quantum algorithms with super-quadratic speedups are essential to make quantum computers useful in practice. With these guidelines one can separate promising applications for quantum computing from those where classical solutions should be pursued. While most of the proposed quantum algorithms and applications do not achieve the necessary speedups to be considered practical, we already see a huge potential in material science and chemistry. We expect further applications to be developed based on our guidelines.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jul 2023.
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Citing papers per year: 2024: 2; 2025: 3; 2026: 3.
8 papers.
- 2025Benchmarking Quantum Reinforcement Learningcited by 9
- 2024On Optimizing Hyperparameters for Quantum Neural Networkscited by 1
- 2024Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisationcited by 1
- 2025Data-driven quantum Koopman method for simulating nonlinear dynamicscited by 1
- 2025On Quantum Perceptron Learning via Quantum Searchcited by 0
- 2026Quantum simulation of real-world nonlinear dynamics via Koopman methodcited by 0
- 2026Practical advantage beyond the quadratic speedup limit with fully-quantum walkscited by 0
- 2026AutoQuREO: A Framework for Automated Quantum Resource Estimation and Optimizationcited by 0
- 2026AutoQuREO: A Framework for Automated Quantum Resource Estimation and Optimization13 Aug 2026
- 2026Practical advantage beyond the quadratic speedup limit with fully-quantum walks24 Jul 2026
- 2026Quantum simulation of real-world nonlinear dynamics via Koopman method8 Jul 2026
- 2025Data-driven quantum Koopman method for simulating nonlinear dynamics29 Jul 2025
- 2025On Quantum Perceptron Learning via Quantum Search21 Mar 2025
- 2025Benchmarking Quantum Reinforcement Learning27 Jan 2025
- 2024Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation13 May 2024
- 2024On Optimizing Hyperparameters for Quantum Neural Networks27 Mar 2024