590 citations · 4.9k across the 34 of their papers we have counts for
10 papers · 1 filter
PennyLane: Automatic differentiation of hybrid quantum-classical computations
Ville Bergholm, Josh Izaac, Maria Schuld +65
PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices,…
Classical benchmarking of Gaussian Boson Sampling on the Titan supercomputer
Brajesh Gupt, Juan Miguel Arrazola, Nicolás Quesada +1
Gaussian Boson Sampling is a model of photonic quantum computing where single-mode squeezed states are sent through linear-optical interferometers and measured using single-photon…
Photonic quantum algorithm for Monte Carlo integration
Patrick Rebentrost, Brajesh Gupt, Thomas R. Bromley
We present a continuous-variable photonic quantum algorithm for the Monte Carlo evaluation of multi-dimensional integrals. Our algorithm encodes n-dimensional integration into n+3…
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…
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 computational finance: Monte Carlo pricing of financial derivatives
Patrick Rebentrost, Brajesh Gupt, Thomas R. Bromley
Financial derivatives are contracts that can have a complex payoff dependent upon underlying benchmark assets. In this work, we present a quantum algorithm for the Monte Carlo pric…
Quantum approximate optimization with Gaussian boson sampling
Juan Miguel Arrazola, Thomas R. Bromley, Patrick Rebentrost
Hard optimization problems are often approached by finding approximate solutions. Here, we highlight the concept of proportional sampling and discuss how it can be used to improve…
Using Gaussian Boson Sampling to Find Dense Subgraphs
Juan Miguel Arrazola, Thomas R. Bromley
Boson sampling devices are a prime candidate for exhibiting quantum supremacy, yet their application for solving problems of practical interest is less well understood. Here we sho…
Batched quantum state exponentiation and quantum Hebbian learning
Thomas R. Bromley, Patrick Rebentrost
Machine learning is a crucial aspect of artificial intelligence. This paper details an approach for quantum Hebbian learning through a batched version of quantum state exponentiati…
Accessible bounds for general quantum resources
Thomas R. Bromley, Marco Cianciaruso, Sofoklis Vourekas +2
The recent development of general quantum resource theories has given a sound basis for the quantification of useful quantum effects. Nevertheless, the evaluation of a resource mea…