1.1k citations
- Ames Research CenterUS122 papers
- Universities Space Research AssociationUS34 papers
- Fermi National Accelerator LaboratoryUS15 papers
- Massachusetts Institute of TechnologyUS15 papers
- Google (United States)US14 papers
- University of Colorado BoulderUS14 papers
- KBR (United States)US13 papers
- Princeton UniversityUS11 papers
- Stinger Ghaffarian Technologies (United States)US11 papers
- University of California, BerkeleyUS10 papers
- Center for Astrophysics Harvard & SmithsonianUS9 papers
- Centre National de la Recherche ScientifiqueFR9 papers
6 papers · 2 filters
Quantum Annealing Applied to De-Conflicting Optimal Trajectories for Air Traffic Management
Tobias Stollenwerk, Bryan O'Gorman, Davide Venturelli +6
We present the mapping of a class of simplified air traffic management (ATM) problems (strategic conflict resolution) to quadratic unconstrained boolean optimization (QUBO) problem…
From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
Stuart Hadfield, Zhihui Wang, Bryan O'Gorman +3
The next few years will be exciting as prototype universal quantum processors emerge, enabling implementation of a wider variety of algorithms. Of particular interest are quantum h…
Quantum-assisted Helmholtz machines: A quantum-classical deep learning framework for industrial datasets in near-term devices
Marcello Benedetti, John Realpe-Gómez, Alejandro Perdomo-Ortiz
Machine learning has been presented as one of the key applications for near-term quantum technologies, given its high commercial value and wide range of applicability. In this work…
Readiness of Quantum Optimization Machines for Industrial Applications
Alejandro Perdomo-Ortiz, Alexander Feldman, Asier Ozaeta +9
There have been multiple attempts to demonstrate that quantum annealing and, in particular, quantum annealing on quantum annealing machines, has the potential to outperform current…
Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
Alejandro Perdomo-Ortiz, Marcello Benedetti, John Realpe-Gómez +1
With quantum computing technologies nearing the era of commercialization and quantum supremacy, machine learning (ML) appears as one of the promising "killer" applications. Despite…
Compiling quantum circuits to realistic hardware architectures using temporal planners
Davide Venturelli, Minh Do, Eleanor Rieffel +1
To run quantum algorithms on emerging gate-model quantum hardware, quantum circuits must be compiled to take into account constraints on the hardware. For near-term hardware, with…