79 citations · 129 across the 2 of their papers we have counts for
3 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…
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.…
For Fixed Control Parameters the Quantum Approximate Optimization Algorithm's Objective Function Value Concentrates for Typical Instances
Fernando G. S. L. Brandao, Michael Broughton, Edward Farhi +2
The Quantum Approximate Optimization Algorithm, QAOA, uses a shallow depth quantum circuit to produce a parameter dependent state. For a given combinatorial optimization problem in…