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quant-ph2025

From Classical Data to Quantum Advantage -- Quantum Policy Evaluation on Quantum Hardware

Daniel Hein, Simon Wiedemann, Markus Baumann +7

Quantum policy evaluation (QPE) is a reinforcement learning (RL) algorithm which is quadratically more efficient than an analogous classical Monte Carlo estimation. It makes use of…

quant-ph2025

The Questionable Influence of Entanglement in Quantum Optimisation Algorithms

Tobias Rohe, Daniëlle Schuman, Jonas Nüßlein +3

The performance of the Variational Quantum Eigensolver (VQE) is promising compared to other quantum algorithms, but also depends significantly on the appropriate design of the unde…

quant-ph2025

Quantum Boltzmann Machines using Parallel Annealing for Medical Image Classification

Daniëlle Schuman, Mark V. Seebode, Tobias Rohe +5

Exploiting the fact that samples drawn from a quantum annealer inherently follow a Boltzmann-like distribution, annealing-based Quantum Boltzmann Machines (QBMs) have gained increa…

quant-ph2024

Reducing QUBO Density by Factoring Out Semi-Symmetries

Jonas Nüßlein, Leo Sünkel, Jonas Stein +6

Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are prominent approaches for solving combinatorial optimization problems, such as those formulated as Quadra…

quant-ph2024

Reducing QAOA Circuit Depth by Factoring out Semi-Symmetries

Jonas Nüßlein, Leo Sünkel, Jonas Stein +4

QAOA is a quantum algorithm for solving combinatorial optimization problems. It is capable of searching for the minimizing solution vector of a QUBO problem . The number…