2.2k citations · 4.9k across the 12 of their papers we have counts for
13 papers
Adaptive pruning-based optimization of parameterized quantum circuits
Sukin Sim, Jonathan Romero, Jerome F. Gonthier +1
Variational hybrid quantum-classical algorithms are powerful tools to maximize the use of Noisy Intermediate Scale Quantum devices. While past studies have developed powerful and e…
Noise robustness and experimental demonstration of a quantum generative adversarial network for continuous distributions
Abhinav Anand, Jonathan Romero, Matthias Degroote +1
The potential advantage of machine learning in quantum computers is a topic of intense discussion in the literature. Theoretical, numerical and experimental explorations will most…
An application benchmark for fermionic quantum simulations
Pierre-Luc Dallaire-Demers, Michał Stęchły, Jerome F. Gonthier +3
It is expected that the simulation of correlated fermions in chemistry and material science will be one of the first practical applications of quantum processors. Given the rapid e…
Variational quantum generators: Generative adversarial quantum machine learning for continuous distributions
Jonathan Romero, Alan Aspuru-Guzik
We propose a hybrid quantum-classical approach to model continuous classical probability distributions using a variational quantum circuit. The architecture of the variational circ…
Quantum Chemistry in the Age of Quantum Computing
Yudong Cao, Jonathan Romero, Jonathan P. Olson +10
Practical challenges in simulating quantum systems on classical computers have been widely recognized in the quantum physics and quantum chemistry communities over the past century…
A framework for algorithm deployment on cloud-based quantum computers
Sukin Sim, Yudong Cao, Jonathan Romero +2
In recent years, the field of quantum computing has significantly developed in both the improvement of hardware as well as the assembly of various software tools and platforms, inc…
Quantum chemistry calculations on a trapped-ion quantum simulator
Cornelius Hempel, Christine Maier, Jonathan Romero +10
Quantum-classical hybrid algorithms are emerging as promising candidates for near-term practical applications of quantum information processors in a wide variety of fields ranging…
Low-depth circuit ansatz for preparing correlated fermionic states on a quantum computer
Pierre-Luc Dallaire-Demers, Jonathan Romero, Libor Veis +2
Quantum simulations are bound to be one of the main applications of near-term quantum computers. Quantum chemistry and condensed matter physics are expected to benefit from these t…
QVECTOR: an algorithm for device-tailored quantum error correction
Peter D. Johnson, Jonathan Romero, Jonathan Olson +2
Current approaches to fault-tolerant quantum computation will not enable useful quantum computation on near-term devices of 50 to 100 qubits. Leading proposals, such as the color c…
Quantum Information and Computation for Chemistry
Jonathan Olson, Yudong Cao, Jonathan Romero +7
The NSF Workshop in Quantum Information and Computation for Chemistry assembled experts from directly quantum-oriented fields such as algorithms, chemistry, machine learning, optic…
Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz
Jonathan Romero, Ryan Babbush, Jarrod R. McClean +3
The variational quantum eigensolver (VQE) algorithm combines the ability of quantum computers to efficiently compute expectation values with a classical optimization routine in ord…
Quantum autoencoders for efficient compression of quantum data
Jonathan Romero, Jonathan P. Olson, Alan Aspuru-Guzik
Classical autoencoders are neural networks that can learn efficient low dimensional representations of data in higher dimensional space. The task of an autoencoder is, given an inp…
The theory of variational hybrid quantum-classical algorithms
Jarrod R. McClean, Jonathan Romero, Ryan Babbush +1
Many quantum algorithms have daunting resource requirements when compared to what is available today. To address this discrepancy, a quantum-classical hybrid optimization scheme kn…