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M. Baumann

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Preprint Sep 2026

When Can Quantum Extreme Learning Machines Replace Quantum Reservoirs?

A simple two-qubit reservoir is constructed that performs temporal recall exactly, while every fixed-window predictor faces the same positive worst-case error over unbounded delays, regardless of model capacity.

M. Baumann, Gerhard Stenzel, Jonas Stein et al. · 0 citations
Preprint Aug 2026

The Organization of Environmental Coupling Shapes What Quantum Reservoirs Remember

For an open quantum reservoir, how the system forgets is part of how it computes. Quantum reservoir computing processes input streams with fixed quantum dynamics and trains only a linear readout. Dissipation can make old inputs fade, but prior studies commonly fix the environmental process and tune only its strength. H...

M. Baumann, Itamar Fink, Johannes Wittmann et al. · 0 citations
Preprint Aug 2026

Implicit Differentiation for Measurement-Efficient Bilevel Quantum-Classical Optimization

This work proposes a bilevel optimization model for diagonal cost Hamiltonians where coefficients depend on a tunable outer parameter and develops correlator-reuse implicit differentiation (CR-ID), which obtains outer gradients by reusing quantum measurements already collected during inner energy estimation, requiring...

Tobias Rohe, M. Baumann, Federico Harjes Ruiloba et al. · 0 citations

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