Classical feature map surrogates and metrics for quantum control landscapes

• URL: http://arxiv.org/abs/2509.25930v1
• Date: Tue, 30 Sep 2025 08:24:13 GMT
• Title: Classical feature map surrogates and metrics for quantum control landscapes
• Authors: Martino Calzavara, Tommaso Calarco, Felix Motzoi,
• Abstract summary: We derive and analyze three feature maps of parametrized quantum dynamics, which generalize variational quantum circuits.<n>The Lie-Fourier representation is shown to have a dense spectrum with discrete peaks, that reflects control Hamiltonian properties, but that is compressible in typically found symmetric systems.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We derive and analyze three feature map representations of parametrized quantum dynamics, which generalize variational quantum circuits. These are (i) a Lie-Fourier partial sum, (ii) a Taylor expansion, and (iii) a finite-dimensional sinc kernel regression representation. The Lie-Fourier representation is shown to have a dense spectrum with discrete peaks, that reflects control Hamiltonian properties, but that is also compressible in typically found symmetric systems. We prove boundedness in the spectrum and the cost function derivatives, and discrete symmetries of the coefficients, with implications for learning and simulation. We further show the landscape is Lipschitz continuous, linking global variation bounds to local Taylor approximation error - key for step size selection, convergence estimates, and stopping criteria in optimization. This also provides a new form of polynomial barren plateaux originating from the Lie-Fourier structure of the quantum dynamics. These results may find application in local and general surrogate model learning, which we benchmark numerically, in characterizations of hardness and phase transitions in the problem instances, and for meta-parameter heuristics in quantum optimizers.

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