most citedPhysics-Informed Neural Networks for an optimal counterdiabatic quantum computation

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph2025

Sequential Quantum Computing

Sebastián V. Romero, Alejandro Gomez Cadavid, Enrique Solano +1

We propose and experimentally demonstrate sequential quantum computing (SQC), a paradigm that utilizes multiple homogeneous or heterogeneous quantum processors in hybrid classical-…

quant-ph20251 cited

Protein folding with an all-to-all trapped-ion quantum computer

Sebastián V. Romero, Alejandro Gomez Cadavid, Pavle Nikačević +8

We experimentally demonstrate that the bias-field digitized counterdiabatic quantum optimization (BF-DCQO) algorithm, implemented on IonQ's fully connected trapped-ion quantum proc…

quant-ph2025

Branch-and-bound digitized counterdiabatic quantum optimization

Anton Simen, Sebastián V. Romero, Alejandro Gomez Cadavid +2

Branch-and-bound algorithms effectively solve combinatorial optimization problems, relying on the relaxation of the objective function to obtain tight lower bounds. While this is s…

quant-ph20232 cited

Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation

Antonio Ferrer-Sánchez, Carlos Flores-Garrigos, Carlos Hernani-Morales +7

We introduce a novel methodology that leverages the strength of Physics-Informed Neural Networks (PINNs) to address the counterdiabatic (CD) protocol in the optimization of quantum…

quant-ph2023

A hybrid quantum-classical algorithm for multichannel quantum scattering of atoms and molecules

Xiaodong Xing, Alejandro Gomez Cadavid, Artur F. Izmaylov +1

We propose a hybrid quantum-classical algorithm for solving the time-independent Schrödinger equation for atomic and molecular collisions. The algorithm is based on the -matrix…