160 citations · 356 across the 10 of their papers we have counts for
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Characterizing Trainability of Instantaneous Quantum Polynomial Circuit Born Machines
Kevin Shen, Susanne Pielawa, Vedran Dunjko +1
Instantaneous quantum polynomial quantum circuit Born machines (IQP-QCBMs) have been proposed as quantum generative models with a classically tractable training objective based on…
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…
Sampling diverse near-optimal solutions via algorithmic quantum annealing
Masoud Mohseni, Marek M. Rams, Sergei V. Isakov +5
Sampling a diverse set of high-quality solutions for hard optimization problems is of great practical relevance in many scientific disciplines and applications, such as artificial…
Engineering Atomic Quantum Reservoirs for Photons
Susanne Pielawa, Luiz Davidovich, David Vitali +1
We present protocols for creating entangled states of two modes of the electromagnetic field, by using a beam of atoms crossing microwave resonators. The atoms are driven by a tran…
Generation of EPR-entangled radiation through an atomic reservoir
Susanne Pielawa, Giovanna Morigi, David Vitali +1
We propose a scheme for generating two-mode squeezing in high-Q resonators using a beam of atoms with random arrival times, which acts as a reservoir for the field. The scheme is b…