41 citations · 74 across the 3 of their papers we have counts for
3 papers
Fully scalable randomized benchmarking without motion reversal
Jordan Hines, Daniel Hothem, Robin Blume-Kohout +2
We introduce binary randomized benchmarking (BiRB), a protocol that streamlines traditional RB by using circuits consisting almost entirely of i.i.d. layers of gates. BiRB reliably…
Demonstrating scalable randomized benchmarking of universal gate sets
Jordan Hines, Marie Lu, Ravi K. Naik +12
Randomized benchmarking (RB) protocols are the most widely used methods for assessing the performance of quantum gates. However, the existing RB methods either do not scale to many…
Efficient hybridization fitting for dynamical mean-field theory via semi-definite relaxation
Carlos Mejuto-Zaera, Leonardo Zepeda-Núñez, Michael Lindsey +3
We introduce a nested optimization procedure using semi-definite relaxation for the fitting step in Hamiltonian-based cluster dynamical mean-field theory (DMFT) methodologies. We s…