Pinned Repositories
navqt
Noise-assisted Variational Quantum Thermalization (NAVQT) is an algorithm used to learn the parameters in a variational quantum circuit which prepares a thermal state of a Hamiltonian. Different from other approaches it considers the noise itself as a variational parameter which can be learned using approximations on the entropy.
shallow-circuits-noise
unibo
Uncertainties in Bayesian Optimization (unibo) is a repository for calibration analysis of bayesian optimization algorithms for both simulated and real-world data.
jfold's Repositories
jfold/shallow-circuits-noise
jfold/unibo
Uncertainties in Bayesian Optimization (unibo) is a repository for calibration analysis of bayesian optimization algorithms for both simulated and real-world data.
jfold/navqt
Noise-assisted Variational Quantum Thermalization (NAVQT) is an algorithm used to learn the parameters in a variational quantum circuit which prepares a thermal state of a Hamiltonian. Different from other approaches it considers the noise itself as a variational parameter which can be learned using approximations on the entropy.