3 citations · 6 across the 28 of their papers we have counts for
29 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…
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…
Detrimental Agnostic Entanglement: The Case Against Hardware-Efficient Ansätze for Combinatorial Optimization
Tobias Rohe, Markus Baumann, Federico Harjes Ruiloba +3
Variational quantum algorithms (VQAs) for combinatorial optimization routinely employ entangling gates as a default design choice, yet the role of entanglement, in its amount and s…
Parity Supervision as a Driver of Generalization in Quantum Generative Modeling
Markus Baumann, Daniel Hein, Steffen Udluft +3
Generative models learn probability distributions in order to produce new samples beyond a finite training set. Their usefulness therefore depends on assigning probability to valid…
Illustration of Barren Plateaus in Quantum Computing
Gerhard Stenzel, Tobias Rohe, Michael Kölle +3
Variational Quantum Circuits (VQCs) have emerged as a promising paradigm for quantum machine learning in the NISQ era. While parameter sharing in VQCs can reduce the parameter spac…
Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study
Gerhard Stenzel, Isabella Debelic, Michael Kölle +4
We extend directed quantum circuit synthesis (DQCS) with reinforcement learning from purely discrete gate selection to parameterized quantum state preparation with continuous singl…
An Evaluation of the Remote CX Protocol under Noise in Distributed Quantum Computing
Leo Sünkel, Michael Kölle, Tobias Rohe +1
Quantum computers connected through classical and quantum communication channels can be combined to function as a single unit to run large quantum circuits that each device is unab…
Quantum King-Ring Domination in Chess: A QAOA Approach
Gerhard Stenzel, Michael Kölle, Tobias Rohe +4
The Quantum Approximate Optimization Algorithm (QAOA) is extensively benchmarked on synthetic random instances such as MaxCut, TSP, and SAT problems, but these lack semantic struct…
Topology-Guided Quantum GANs for Constrained Graph Generation
Tobias Rohe, Markus Baumann, Michael Poppel +3
Quantum computing (QC) promises theoretical advantages, benefiting computational problems that would not be efficiently classically simulatable. However, much of this theoretical s…
Evaluating Variational Quantum Circuit Architectures for Distributed Quantum Computing
Leo Sünkel, Jonas Stein, Jonas Nüßlein +2
Scaling quantum computers, i.e., quantum processing units (QPUs) to enable the execution of large quantum circuits is a major challenge, especially for applications that should pro…
Quantum Architecture Search for Solving Quantum Machine Learning Tasks
Michael Kölle, Simon Salfer, Tobias Rohe +2
Quantum computing leverages quantum mechanics to address computational problems in ways that differ fundamentally from classical approaches. While current quantum hardware remains…
Investigating the Lottery Ticket Hypothesis for Variational Quantum Circuits
Michael Kölle, Leonhard Klingert, Julian Schönberger +3
Quantum computing is an emerging field in computer science that has seen considerable progress in recent years, especially in machine learning. By harnessing the principles of quan…
Quantum Computer Benchmarking: An Explorative Systematic Literature Review
Tobias Rohe, Federico Harjes Ruiloba, Sabrina Egger +3
As quantum computing (QC) continues to evolve in hardware and software, measuring progress in this complex and diverse field remains a challenge. To track progress, uncover bottlen…
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…
Clique detection using symmetry-restricted quantum circuits
Maximilian Balthasar Mansky, Tobias Rohe, Dmytro Bondarenko +2
We show the application of permutation-invariant quantum circuits to the clique problem. The experiment asks to label a clique through identification of the nodes in a larger subgr…
Analysis of quantum neural network performance via edge cases
Maximilian Balthasar Mansky, Tobias Rohe, Linus Menzel +2
We evaluate the particular performance of different quantum machine learning networks on a graph classification task. Quantum circuits with varying internal symmetry that completel…
Solving graph problems using permutation-invariant quantum machine learning
Maximilian Balthasar Mansky, Tobias Rohe, Gerhard Stenzel +7
Many computational problems are unchanged under some symmetry operation. In classical machine learning, this can be reflected with the layer structure of the neural network. In qua…
Accelerated VQE: Parameter Recycling for Similar Recurring Problem Instances
Tobias Rohe, Maximilian Balthasar Mansky, Michael Kölle +3
Training the Variational Quantum Eigensolver (VQE) is a task that requires substantial compute. We propose the use of concepts from transfer learning to considerably reduce the tra…
Investigating Parameter-Efficiency of Hybrid QuGANs Based on Geometric Properties of Generated Sea Route Graphs
Tobias Rohe, Florian Burger, Michael Kölle +3
The demand for artificially generated data for the development, training and testing of new algorithms is omnipresent. Quantum computing (QC), does offer the hope that its inherent…
Optimization of Link Configuration for Satellite Communication Using Reinforcement Learning
Tobias Rohe, Michael Kölle, Jan Matheis +3
Satellite communication is a key technology in our modern connected world. With increasingly complex hardware, one challenge is to efficiently configure links (connections) on a sa…
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…
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…
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…
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…