20 citations · 21 across the 5 of their papers we have counts for
5 papers
Closest Accessible Symmetry reduction: a tool for Hamiltonian interpolation analysis
Ana Palacios, Artur Garcia-Saez, Arnau Riera +1
We introduce a framework for analysing the spectrum of Hamiltonian interpolations without heavily relying on discretising the interpolation parameter. The method is based on the co…
Entanglement and Classical Simulability in Quantum Extreme Learning Machines
A. De Lorenzis, M. P. Casado, N. Lo Gullo +3
Quantum Machine Learning (QML) has emerged as a promising framework for exploring how quantum dynamics may enhance data processing tasks. Here we investigate Quantum Extreme Learni…
Quantum annealing eigensolver as a NISQ era tool for probing strong correlation effects in quantum chemistry
Aashna Anil Zade, Kenji Sugisaki, Matthias Werner +6
The quantum-classical hybrid variational quantum eigensolver (VQE) algorithm is arguably the most popular noisy intermediate-scale quantum (NISQ) era approach to quantum chemistry.…
A coherent approach to quantum-classical optimization
Andrés N. Cáliz, Jordi Riu, Josep Bosch +3
Hybrid quantum-classical optimization techniques, which incorporate the pre-optimization of Variational Quantum Algorithms (VQAs) using Tensor Networks (TNs), have been shown to al…
Harnessing Quantum Extreme Learning Machines for image classification
A. De Lorenzis, M. P. Casado, M. P. Estarellas +5
Interest in quantum machine learning is increasingly growing due to its potential to offer more efficient solutions for problems that are difficult to tackle with classical methods…