6 papers · 1 filter
Pulsed learning for quantum data re-uploading models
Ignacio B. Acedo, Pablo Rodriguez-Grasa, Pablo Garcia-Azorin +1
While Quantum Machine Learning (QML) holds great potential, its practical realization on Noisy Intermediate-Scale Quantum (NISQ) hardware has been hindered by the limitations of va…
Quantum Algorithm for Local-Volatility Option Pricing via the Kolmogorov Equation
Nikita Guseynov, Mikel Sanz, Ãngel RodrÃguez-Rozas +2
The solution of option-pricing problems may turn out to be computationally demanding due to non-linear and path-dependent payoffs, the high dimensionality arising from multiple und…
Cost of Emulating a Small Quantum Annealing Problem in the Circuit-Model
Javier Gonzalez-Conde, Zachary Morrell, Marc Vuffray +2
Demonstrations of quantum advantage for certain sampling problems have generated considerable excitement for quantum computing and have further spurred the development of circuit-m…
Quantum approximated cloning-assisted density matrix exponentiation
Pablo Rodriguez-Grasa, Ruben Ibarrondo, Javier Gonzalez-Conde +3
Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the e…
Quantum Carleman linearisation efficiency in nonlinear fluid dynamics
Javier Gonzalez-Conde, Dylan Lewis, Sachin S. Bharadwaj +1
Computational fluid dynamics (CFD) is a specialised branch of fluid mechanics that utilises numerical methods and algorithms to solve and analyze fluid-flow problems. One promising…
Efficient quantum amplitude encoding of polynomial functions
Javier Gonzalez-Conde, Thomas W. Watts, Pablo Rodriguez-Grasa +1
Loading functions into quantum computers represents an essential step in several quantum algorithms, such as quantum partial differential equation solvers. Therefore, the inefficie…