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Same Spectrum, Harder First-Order Training: Phase-Locking in Single- versus Multi-Qubit Re-Uploading Circuits
Michael Poppel, David Bucher, Maximilian Zorn +5
Angle-encoded variational quantum circuits implement truncated Fourier series. For one-dimensional inputs, a single-qubit re-uploading (serial) circuit represents every function th…
Exploiting Symmetry in Quantum Reservoir Computing
Markus Baumann, Michael Poppel, Thomas Gabor +3
Quantum reservoir computing (QRC) uses a quantum processor without training it. The input is encoded into a quantum state, a fixed random circuit evolves it, selected observables a…
Architecture Shape Governs QNN Trainability: Jacobian Null Space Growth and Parameter Efficiency
Michael Poppel, David Bucher, Maximilian Zorn +5
Variational quantum circuits with angle encoding implement truncated Fourier series, and architectures arranging qubits with encoding layers each -- sharing encoding budget…
Constrained Quantum Optimization via Iterative Warm-Start XY-Mixers
David Bucher, Maximilian Janetschek, Michael Poppel +3
The Quantum Approximate Optimization Algorithm (QAOA) is a leading hybrid heuristic for combinatorial optimization, but efficiently handling hard constraints remains a significant…
Long Range Frequency Tuning for QML
Michael Poppel, Markus Baumann, Sebastian Wölckert +2
Angle-encoded variational quantum circuits admit a truncated Fourier series representation of their output, but approximating functions with maximum frequency using fixe…