5 citations · 6 across the 6 of their papers we have counts for
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JAQSI: Just Another Quantum Simulator
Melvin Strobl, Maja Franz, Lukas Scheller +3
Classical simulation supports the development and validation of quantum algorithms through full-state inspection, controlled noise models and backpropagation, albeit for small quan…
Unflattening by Flattening -- How Input Distributions Shape Output Variance in Angle-Encoded Circuits
Melvin Strobl, Gabriel Mejia, Eileen Kuehn +1
Barren plateaus hinder training of parameterized quantum circuits by making loss gradients exponentially small in the number of qubits. For angle-encoded product states, we show ho…
Software Between Quantum and Machine Learning -- And Down to Pulses
Maja Franz, Melvin Strobl, Jonathan Hunz +5
Contemporary quantum computing platforms remain, in essence, programmable physical systems whose control is typically mediated through unitary gate abstractions. While such abstrac…
Trainable Quantum Spectral Models for Partial Differential Equations
Gabriel Mejia, Eileen Kuehn, Melvin Strobl +1
This work studies trainable quantum spectral models (QSMs) for solving linear partial differential equations (PDEs). Instead of learning solutions directly in physical space, QSMs…
Beyond Gates: Pulse Level Quantum Fourier Models
Melvin Strobl, Maja Franz, Lukas Scheller +3
In the domain of variational quantum algorithms, quantum Fourier models (QFMs) provide a mathematically well defined structure for quantum machine learning (QML). There has been a…