Abstract
For quantum machine learning, the exact boundary between classical and quantum advantage is still poorly understood. Direct comparison between quantum neural networks (QNNs) and existing classical models, which encompass fundamentally different function classes, often fails to provide broader insight into the difference between the two. Inspired by the techniques of Neural Quantum States and Random Fourier Features, this work introduces Neural Fourier Surrogates (NFS), a stochastic classical neural network architecture for efficiently learning coefficients over the same finite Fourier series support as quantum neural networks. Testing on a selection of tabular benchmark datasets, we find that NFS is an effective classifier architecture broadly competitive with established classical baselines, including a comparable Random Fourier Features model, and possessing comparable performance to data-reuploading QNNs; combined with additional analysis comparing the learned Fourier spectra of QNNs and NFS on synthetic data, these results establish NFS as a natural classical baseline for evaluating QNN performance.
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Publication details
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- Open access
- Green open access
Cite this article
APA 7
Knitter, O., Mei, J., Kim, S. H., Chen, C., Yamada, M., & Roetteler, M. (2026). Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks. https://omanscience.com/en/articles/neural-fourier-surrogates-for-data-reuploading-quantum-neural-networks
MLA 9
Knitter, Oliver, et al. "Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks." https://omanscience.com/en/articles/neural-fourier-surrogates-for-data-reuploading-quantum-neural-networks.
Chicago (author–date)
Knitter, Oliver, Jonathan Mei, Sang Hyub Kim, Chi Chen, Masako Yamada, and Martin Roetteler. 2026. "Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks." https://omanscience.com/en/articles/neural-fourier-surrogates-for-data-reuploading-quantum-neural-networks.
Harvard
Knitter, O., Mei, J., Kim, S. H., Chen, C., Yamada, M. and Roetteler, M. (2026) 'Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks', Available at: https://omanscience.com/en/articles/neural-fourier-surrogates-for-data-reuploading-quantum-neural-networks.
Vancouver
Knitter O, Mei J, Kim SH, Chen C, Yamada M, Roetteler M. Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks. https://omanscience.com/en/articles/neural-fourier-surrogates-for-data-reuploading-quantum-neural-networks
IEEE
O. Knitter, J. Mei, S. H. Kim, C. Chen, M. Yamada, and M. Roetteler, "Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks," https://omanscience.com/en/articles/neural-fourier-surrogates-for-data-reuploading-quantum-neural-networks.