181 citations · 334 across the 27 of their papers we have counts for
8 papers · 1 filter
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…
Mitigating exponential concentration in covariant quantum kernels for subspace and real-world data
Gabriele Agliardi, Giorgio Cortiana, Anton Dekusar +6
Fidelity quantum kernels have shown promise in classification tasks, particularly when a group structure in the data can be identified and exploited through a covariant feature map…
Quantum multi-output Gaussian Processes based Machine Learning for Line Parameter Estimation in Electrical Grids
Priyanka Arkalgud Ganeshamurthy, Kumar Ghosh, Corey O'Meara +3
Gaussian process (GP) is a powerful modeling method with applications in machine learning for various engineering and non-engineering fields. Despite numerous benefits of modeling…
Towards Less Greedy Quantum Coalition Structure Generation in Induced Subgraph Games
Jonas Nüßlein, Daniëlle Schuman, David Bucher +5
The transition to 100% renewable energy requires new techniques for managing energy networks, such as dividing them into sensible subsets of prosumers called micro-grids. Doing so…
A Machine Learning Approach to Boost the Vehicle-2-Grid Scheduling
Gabriele Agliardi, Giorgio Cortiana, Anton Dekusar +6
Electric Vehicles (EVs) are emerging as battery energy storage systems (BESSs) of increasing importance for different power grid services. However, the unique characteristics of EV…
Bridging the Gap to Next Generation Power System Planning and Operation with Quantum Computation
Priyanka Arkalgud Ganeshamurthy, Kumar Ghosh, Corey O'Meara +2
Innovative solutions and developments are being inspected to tackle rising electrical power demand to be supplied by clean forms of energy. The integration of renewable energy gene…
Evaluating Quantum Optimization for Dynamic Self-Reliant Community Detection
David Bucher, Daniel Porawski, Benedikt Wimmer +5
Power grid partitioning is an important requirement for resilient distribution grids. Since electricity production is progressively shifted to the distribution side, dynamic identi…
Quantum Optimization for the Future Energy Grid: Summary and Quantum Utility Prospects
Jonas Blenninger, David Bucher, Giorgio Cortiana +6
In this project summary paper, we summarize the key results and use-cases explored in the German Federal Ministry of Education and Research (BMBF) funded project "Q-GRID" which aim…