Classically optimized variational quantum eigensolver with applications to topological phases

KN Okada, K Osaki, K Mitarai, K Fujii - Physical Review Research, 2023 - APS
The variational quantum eigensolver (VQE) is regarded as a promising candidate of hybrid
quantum-classical algorithms for near-term quantum computers. Meanwhile, VQE is …

OnionVQE optimization strategy for ground state preparation on NISQ devices

K Gratsea, J Selisko, M Amsler, C Wever… - Quantum Science …, 2024 - iopscience.iop.org
The variational quantum eigensolver (VQE) is one of the most promising and widely used
algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum …

[PDF][PDF] Quantum parallelized variational quantum eigensolvers for excited states

CL Hong, L Colmenarez, L Ding… - ar** and its applications
Y Dong, S Wu - Physica Scripta, 2024 - iopscience.iop.org
In order to explore the possibility of cross-fertilization between quantum computing and
neural networks, and to analyse the effects of multiple weight remap** functions on the …

Evaluating the efficiency of ground-state-preparation algorithms

K Gratsea, C Sun, PD Johnson - Physical Review A, 2024 - APS
In recent years, substantial research effort has been devoted to quantum algorithms for
ground-state-energy estimation (GSEE) in chemistry and materials. Given the many heuristic …

Quantum Neural Networks: Issues, Training, and Applications

CM Ortiz Marrero, N Wiebe, JC Furches, MJ Ragone - 2023 - osti.gov
Our work in the field aims at explaining the limitations and expressive power of Quantum
Machine Learning models, as well as finding feasible training algorithms that could be …

Introducing tools to quantify the performance of quantum computing algorithms and their applications

K Gratsea - 2024 - upcommons.upc.edu
(English) In this thesis, I focused on introducing tools to quantify the performance of quantum
computing algorithms and their applications. The main focus is on two of the most popular …