551 citations · 696 across the 10 of their papers we have counts for
8 papers · 1 filter
Evaluating analytic gradients on quantum hardware
Maria Schuld, Ville Bergholm, Christian Gogolin +2
An important application for near-term quantum computing lies in optimization tasks, with applications ranging from quantum chemistry and drug discovery to machine learning. In man…
Graph isomorphism and Gaussian boson sampling
Kamil Bradler, Shmuel Friedland, Josh Izaac +2
We introduce a connection between a near-term quantum computing device, specifically a Gaussian boson sampler, and the graph isomorphism problem. We propose a scheme where graphs a…
Machine learning method for state preparation and gate synthesis on photonic quantum computers
Juan Miguel Arrazola, Thomas R. Bromley, Josh Izaac +3
We show how techniques from machine learning and optimization can be used to find circuits of photonic quantum computers that perform a desired transformation between input and out…
Gaussian Boson Sampling using threshold detectors
Nicolás Quesada, Juan Miguel Arrazola, Nathan Killoran
We study what is arguably the most experimentally appealing Boson Sampling architecture: Gaussian states sampled with threshold detectors. We show that in this setting, the probabi…
Continuous-variable quantum neural networks
Nathan Killoran, Thomas R. Bromley, Juan Miguel Arrazola +3
We introduce a general method for building neural networks on quantum computers. The quantum neural network is a variational quantum circuit built in the continuous-variable (CV) a…
Quantum generative adversarial networks
Pierre-Luc Dallaire-Demers, Nathan Killoran
Quantum machine learning is expected to be one of the first potential general-purpose applications of near-term quantum devices. A major recent breakthrough in classical machine le…