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20162023
most citedCutQC: Using Small Quantum Computers for Large Quantum Circuit Evaluations

158 citations · 357 across the 13 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

quant-ph2021

Optimizing frequency allocation for fixed-frequency superconducting quantum processors

Alexis Morvan, Larry Chen, Jeffrey M. Larson +2

Fixed-frequency superconducting quantum processors are one of the most mature quantum computing architectures with high-coherence qubits and simple controls. However, high-fidelity…

math.OC2021

Derivative-Free Optimization of a Rapid-Cycling Synchrotron

Jeffrey S. Eldred, Jeffrey Larson, Misha Padidar +2

We develop and solve a constrained optimization model to identify an integrable optics rapid-cycling synchrotron lattice design that performs well in several capacities. Our model…

math.OC2021

Multistart Algorithm for Identifying All Optima of Nonconvex Stochastic Functions

Prateek Jaiswal, Jeffrey Larson

We propose a multistart algorithm to identify all local minima of a constrained, nonconvex stochastic optimization problem. The algorithm uniformly samples points in the domain and…

quant-ph2021

LEAP: Scaling Numerical Optimization Based Synthesis Using an Incremental Approach

Ethan Smith, Marc G. Davis, Jeffrey Larson +3

While showing great promise, circuit synthesis techniques that combine numerical optimization with search over circuit structures face scalability challenges due to a large number…

stat.CO2021★ 1 cited

Lookahead Acquisition Functions for Finite-Horizon Time-Dependent Bayesian Optimization and Application to Quantum Optimal Control

S. Ashwin Renganathan, Jeffrey Larson, Stefan M. Wild

We propose a novel Bayesian method to solve the maximization of a time-dependent expensive-to-evaluate stochastic oracle. We are interested in the decision that maximizes the oracl…

cs.DC2021

libEnsemble: A Library to Coordinate the Concurrent Evaluation of Dynamic Ensembles of Calculations

Stephen Hudson, Jeffrey Larson, John-Luke Navarro +1

Almost all applications stop scaling at some point; those that don't are seldom performant when considering time to solution on anything but aspirational/unicorn resources. Recogni…