4 citations · 7 across the 5 of their papers we have counts for
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quant-ph2023★ 2 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…
physics.comp-ph2023★ 4 cited
Gradient-Annihilated PINNs for Solving Riemann Problems: Application to Relativistic Hydrodynamics
Antonio Ferrer-Sánchez, José D. Martín-Guerrero, Roberto Ruiz de Austri +2
We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method…