4.7k citations · 15k across the 81 of their papers we have counts for
8 papers · 1 filter
Quantum computational finance: quantum algorithm for portfolio optimization
Patrick Rebentrost, Seth Lloyd
We present a quantum algorithm for portfolio optimization. We discuss the market data input, the processing of such data via quantum operations, and the output of financially relev…
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…
Bayesian Deep Learning on a Quantum Computer
Zhikuan Zhao, Alejandro Pozas-Kerstjens, Patrick Rebentrost +1
Bayesian methods in machine learning, such as Gaussian processes, have great advantages com-pared to other techniques. In particular, they provide estimates of the uncertainty asso…
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…
Smooth input preparation for quantum and quantum-inspired machine learning
Zhikuan Zhao, Jack K. Fitzsimons, Patrick Rebentrost +2
Machine learning has recently emerged as a fruitful area for finding potential quantum computational advantage. Many of the quantum enhanced machine learning algorithms critically…
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…