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quant-ph2026
A quantum generative model for in silico clinical trials using scarce training datasets
Olatz Sanz Larrarte, Reza Dastbasteh, Roberto Sanchez-Navarro +7
In silico methods have emerged as a strategy to complement clinical trials. These are particularly relevant for rare or heterogeneous diseases for which traditional methods are cos…
quant-ph2026
Noise mitigation of quantum observables via learning from Hamiltonian symmetry decays
Javier Oliva del Moral, Olatz Sanz Larrarte, Joana Fraxanet +2
We present a new quantum error mitigation technique (QEM), called GUiding Extrapolations from Symmetry decayS (GUESS), which exploits Hamiltonian symmetries to improve accuracy of…