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20232026
most citedEvaluating Variational Quantum Circuit Architectures for Distributed Quantum Computing

3 citations · 6 across the 28 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

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…

cs.CV2024

Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data

Tobias Rohe, Barbara Böhm, Michael Kölle +3

Drones have revolutionized various domains, including agriculture. Recent advances in deep learning have propelled among other things object detection in computer vision. This stud…

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…

quant-ph2024★ 1 cited

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-ph2024

From Problem to Solution: A general Pipeline to Solve Optimisation Problems on Quantum Hardware

Tobias Rohe, Simon Grätz, Michael Kölle +3

With constant improvements of quantum hardware and quantum algorithms, quantum advantage comes within reach. Parallel to the development of the computer at the end of the twentieth…

quant-ph2024

A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning

Michael Kölle, Timo Witter, Tobias Rohe +3

Quantum Computing aims to streamline machine learning, making it more effective with fewer trainable parameters. This reduction of parameters can speed up the learning process and…

quant-ph2024

Towards Federated Learning on the Quantum Internet

Leo Sünkel, Michael Kölle, Tobias Rohe +1

While the majority of focus in quantum computing has so far been on monolithic quantum systems, quantum communication networks and the quantum internet in particular are increasing…