From the 1 of 11 linked papers with an AI index.
11 papers
Emergent Problem-Graph Alignment in RL-Discovered Entanglement Topologies for QAOA
Tobias Rohe, Federico Harjes Ruiloba, Markus Baumann +4
In the Quantum Approximate Optimization Algorithm (QAOA), the entanglement topology, where qubit pairs are connected by two-qubit gates, is conventionally set equal to the edge set…
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…
Quantum Optimization Algorithms
Jonas Stein, Maximilian Zorn, Leo Sünkel +1
Quantum optimization allows for up to exponential quantum speedups for specific, possibly industrially relevant problems. As the key algorithm in this field, we motivate and discus…
Evolutionary-Based Circuit Optimization for Distributed Quantum Computing
Leo Sünkel, Jonas Stein, Gerhard Stenzel +3
In this work, we evaluate an evolutionary algorithm (EA) to optimize a given circuit in such a way that it reduces the required communication when executed in the Distributed Quant…
Towards Scalable Lottery Ticket Networks using Genetic Algorithms
Julian Schönberger, Maximilian Zorn, Jonas NüÃlein +2
Building modern deep learning systems that are not just effective but also efficient requires rethinking established paradigms for model training and neural architecture design. In…