12 citations · 13 across the 7 of their papers we have counts for
7 papers
Reshaping quantum annealing landscapes with diagonal catalysts
Andrés N. Cáliz, Carlos Ramon-Escandell, Finnley Paolella +4
Quantum annealing is often limited by population trapped in local minima many spin flips from the solution. We introduce a mathematical framework to understand the connection betwe…
Do quantum linear solvers offer advantage for networks-based system of linear equations?
Disha Shetty, Supriyo Dutta, Palak Chawla +5
In this exploratory numerical study, we assess the suitability of Quantum Linear Solvers(QLSs)toward providing a quantum advantage for Networks-based Linear System Problems (NLSPs)…
Trapped ion quantum hardware demonstration of energy calculations using a multireference unitary coupled cluster ansatz: application to the BeH2 insertion problem
Palak Chawla, Disha Shetty, Peniel Bertrand Tsemo +5
In this study, we employ the variational quantum eigensolver algorithm with a multireference unitary coupled cluster ansatz to report the ground state energy of the BeH2 molecule i…
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…
Relativistic VQE calculations of molecular electric dipole moments on trapped ion quantum hardware
Palak Chawla, Shweta, K. R. Swain +9
The quantum-classical hybrid variational quantum eigensolver (VQE) algorithm is among the most actively studied topics in atomic and molecular calculations on quantum computers, ye…
Reinforcement Learning Based Quantum Circuit Optimization via ZX-Calculus
Jordi Riu, Jan Nogué, Gerard Vilaplana +2
We propose a novel Reinforcement Learning (RL) method for optimizing quantum circuits using graph-theoretic simplification rules of ZX-diagrams. The agent, trained using the Proxim…