4 papers
Practical Noise Mitigation for Quantum Annealing via Dynamical Decoupling: Toward Industry-Relevant Optimization using Trapped Ions
Sebastian Nagies, Chiara Capecci, Marcel Seelbach Benkner +6
Quantum annealing is a framework for solving combinatorial optimization problems. While it offers a promising path towards a practical application of quantum hardware, its performa…
Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms
Natacha Kuete Meli, Shuteng Wang, Marcel Seelbach Benkner +5
Quantum-enhanced Computer Vision (QeCV) is a new research field at the intersection of computer vision, optimisation theory, machine learning and quantum computing. It has high pot…
Compensating connectivity restrictions in quantum annealers via splitting and linearization techniques
Marcel Seelbach Benkner, Zorah Lähner, Vladislav Golyanik +2
Current quantum annealing experiments often suffer from restrictions in connectivity in the sense that only certain qubits can be coupled to each other. The most common strategy to…
QuCOOP: A Versatile Framework for Solving Composite and Binary-Parametrised Problems on Quantum Annealers
Natacha Kuete Meli, Vladislav Golyanik, Marcel Seelbach Benkner +1
There is growing interest in solving computer vision problems such as mesh or point set alignment using Adiabatic Quantum Computing (AQC). Unfortunately, modern experimental AQC de…