7.2k citations · 7.3k across the 2 of their papers we have counts for
11 papers
Hartree-Fock on a superconducting qubit quantum computer
Frank Arute, Kunal Arya, Ryan Babbush +79
As the search continues for useful applications of noisy intermediate scale quantum devices, variational simulations of fermionic systems remain one of the most promising direction…
Demonstrating a Continuous Set of Two-qubit Gates for Near-term Quantum Algorithms
B. Foxen, C. Neill, A. Dunsworth +54
Quantum algorithms offer a dramatic speedup for computational problems in machine learning, material science, and chemistry. However, any near-term realizations of these algorithms…
Supplementary information for "Quantum supremacy using a programmable superconducting processor"
Frank Arute, Kunal Arya, Ryan Babbush +74
This is an updated version of supplementary information to accompany "Quantum supremacy using a programmable superconducting processor", an article published in the October 24, 201…
Direct measurement of non-local interactions in the many-body localized phase
B. Chiaro, C. Neill, A. Bohrdt +58
The interplay of interactions and strong disorder can lead to an exotic quantum many-body localized (MBL) phase. Beyond the absence of transport, the MBL phase has distinctive sign…
Discontinuous Galerkin discretization for quantum simulation of chemistry
Jarrod R. McClean, Fabian M. Faulstich, Qinyi Zhu +5
Methods for electronic structure based on Gaussian and molecular orbital discretizations offer a well established, compact representation that forms much of the foundation of corre…
Learning to learn with quantum neural networks via classical neural networks
Guillaume Verdon, Michael Broughton, Jarrod R. McClean +5
Quantum Neural Networks (QNNs) are a promising variational learning paradigm with applications to near-term quantum processors, however they still face some significant challenges.…