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Universality and kernel-adaptive training for classically trained, quantum-deployed generative models
Andrii Kurkin, Kevin Shen, Susanne Pielawa +2
The instantaneous quantum polynomial (IQP) quantum circuit Born machine (QCBM) has been proposed as a promising quantum generative model over bitstrings. Recent works have shown th…
Note on the Universality of Parameterized IQP Circuits with Hidden Units for Generating Probability Distributions
Andrii Kurkin, Kevin Shen, Susanne Pielawa +2
In a series of recent works, an interesting quantum generative model based on parameterized instantaneous polynomial quantum (IQP) circuits has emerged as they can be trained effic…
Weighted Approximate Quantum Natural Gradient for Variational Quantum Eigensolver
Chenyu Shi, Vedran Dunjko, Hao Wang
The variational quantum eigensolver (VQE) is one of the most prominent algorithms using near-term quantum devices, designed to find the ground state of a Hamiltonian. In VQE, a cla…