522 citations · 671 across the 3 of their papers we have counts for
8 papers · 1 filter
Probing many-body localization on a noisy quantum computer
D. Zhu, S. Johri, N. H. Nguyen +5
A disordered system of interacting particles exhibits localized behavior when the disorder is large compared to the interaction strength. Studying this phenomenon on a quantum comp…
Noise reduction using past causal cones in variational quantum algorithms
Omar Shehab, Isaac H. Kim, Nhung H. Nguyen +5
We introduce an approach to improve the accuracy and reduce the sample complexity of near term quantum-classical algorithms. We construct a simpler initial parameterized quantum st…
Toward convergence of effective field theory simulations on digital quantum computers
Omar Shehab, Kevin A. Landsman, Yunseong Nam +5
We report results for simulating an effective field theory to compute the binding energy of the deuteron nucleus using a hybrid algorithm on a trapped-ion quantum computer. Two inc…
Training of Quantum Circuits on a Hybrid Quantum Computer
D. Zhu, N. M. Linke, M. Benedetti +10
Generative modeling is a flavor of machine learning with applications ranging from computer vision to chemical design. It is expected to be one of the techniques most suited to tak…
Verified Quantum Information Scrambling
Kevin A. Landsman, Caroline Figgatt, Thomas Schuster +4
Quantum scrambling is the dispersal of local information into many-body quantum entanglements and correlations distributed throughout the entire system. This concept underlies the…
Machine learning assisted readout of trapped-ion qubits
Alireza Seif, Kevin A. Landsman, Norbert M. Linke +3
We reduce measurement errors in a quantum computer using machine learning techniques. We exploit a simple yet versatile neural network to classify multi-qubit quantum states, which…