From the 1 of 20 linked papers with an AI index.
20 papers
Implicit Differentiation for Measurement-Efficient Bilevel Quantum-Classical Optimization
Tobias Rohe, Markus Baumann, Federico Harjes Ruiloba +3
Quantum optimization has shown promising results for quadratic unconstrained binary optimization (QUBO) problems. Real-world applications, however, often involve polynomial coeffic…
From Quantum Shots to Training Data: Reorganizing Measurement Records in Quantum Machine Learning
Markus Baumann, Maximilian Zorn, Thomas Gabor +2
The paper introduces a shot‑grouping technique that partitions quantum measurement records into disjoint groups and averages within each group, providing a tunable trade‑off betwee…
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…
Mitigating Exponential Mixed Frequency Growth through Frequency Selection
Michael Poppel, David Bucher, Maximilian Zorn +4
Angle encoding has emerged as a popular feature map for embedding classical data into quantum models, naturally generating truncated Fourier series with universal function approxim…
Quantum Optimization Methods for the Generalized Traveling Salesman Problem
Maximilian Zorn, Melinda Braun, Michael Ertl +4
This paper studies quantum optimization baselines for the Generalized Traveling Salesman Problem (GTSP), a clustered routing problem that naturally models variant selection and seq…