383 citations · 1.2k across the 29 of their papers we have counts for
29 papers
Switching Time Optimization for Binary Quantum Optimal Control
Xinyu Fei, Lucas T. Brady, Jeffrey Larson +2
Quantum optimal control is a technique for controlling the evolution of a quantum system and has been applied to a wide range of problems in quantum physics. We study a binary quan…
Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem
Ruslan Shaydulin, Changhao Li, Shouvanik Chakrabarti +26
The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm for solving optimization problems on quantum computers. However, the potential of QAOA to tac…
Exploiting In-Constraint Energy in Constrained Variational Quantum Optimization
Tianyi Hao, Ruslan Shaydulin, Marco Pistoia +1
A central challenge of applying near-term quantum optimization algorithms to industrially relevant problems is the need to incorporate complex constraints. In general, such constra…
An Empirical Quantile Estimation Approach to Nonlinear Optimization Problems with Chance Constraints
Fengqiao Luo, Jeffrey Larson
We investigate an empirical quantile estimation approach to solve chance-constrained nonlinear optimization problems. Our approach is based on the reformulation of the chance const…
Multi-Angle QAOA Does Not Always Need All Its Angles
Kaiyan Shi, Rebekah Herrman, Ruslan Shaydulin +3
Introducing additional tunable parameters to quantum circuits is a powerful way of improving performance without increasing hardware requirements. A recently introduced multiangle…
Hardware-Conscious Optimization of the Quantum Toffoli Gate
Max Aksel Bowman, Pranav Gokhale, Jeffrey Larson +2
While quantum computing holds great potential in combinatorial optimization, electronic structure calculation, and number theory, the current era of quantum computing is limited by…
Structure-Aware Methods for Expensive Derivative-Free Nonsmooth Composite Optimization
Jeffrey Larson, Matt Menickelly
We present new methods for solving a broad class of bound-constrained nonsmooth composite minimization problems. These methods are specially designed for objectives that are some k…
Comparison of Multiobjective Optimization Methods for the LCLS-II Photoinjector
Nicole Neveu, Tyler H. Chang, Paris Franz +2
Particle accelerators are among some of the largest science experiments in the world and can consist of thousands of components with a wide variety of input ranges. These systems c…
Modeling Approaches for Addressing Simple Unrelaxable Constraints with Unconstrained Optimization Methods
Misha Padidar, Jeffrey Larson, Stefan M. Wild
We explore novel approaches for solving nonlinear optimization problems with unrelaxable bound constraints, which must be satisfied before the objective function can be evaluated.…
Characterizing Error Mitigation by Symmetry Verification in QAOA
Ashish Kakkar, Jeffrey Larson, Alexey Galda +1
Hardware errors are a major obstacle to demonstrating quantum advantage with the quantum approximate optimization algorithm (QAOA). Recently, symmetry verification has been propose…
Binary Control Pulse Optimization for Quantum Systems
Xinyu Fei, Lucas T. Brady, Jeffrey Larson +2
Quantum control aims to manipulate quantum systems toward specific quantum states or desired operations. Designing highly accurate and effective control steps is vitally important…
Parameter Transfer for Quantum Approximate Optimization of Weighted MaxCut
Ruslan Shaydulin, Phillip C. Lotshaw, Jeffrey Larson +2
Finding high-quality parameters is a central obstacle to using the quantum approximate optimization algorithm (QAOA). Previous work partially addresses this issue for QAOA on unwei…
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…
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…
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…
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…
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…
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…
CutQC: Using Small Quantum Computers for Large Quantum Circuit Evaluations
Wei Tang, Teague Tomesh, Martin Suchara +2
Quantum computing (QC) is a new paradigm offering the potential of exponential speedups over classical computing for certain computational problems. Each additional qubit doubles t…
Manifold Sampling for Optimizing Nonsmooth Nonconvex Compositions
Jeffrey Larson, Matt Menickelly, Baoyu Zhou
We propose a manifold sampling algorithm for minimizing a nonsmooth composition , where we assume is nonsmooth and may be inexpensively computed in closed form and…
Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints
Christian Kirches, Jeffrey Larson, Sven Leyffer +1
We propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a li…
Recursive Two-Step Lookahead Expected Payoff for Time-Dependent Bayesian Optimization
S. Ashwin Renganathan, Jeffrey Larson, Stefan Wild
We propose a novel Bayesian method to solve the maximization of a time-dependent expensive-to-evaluate oracle. We are interested in the decision that maximizes the oracle at a fini…
A Repeated Route-then-Schedule Approach to Coordinated Vehicle Platooning: Algorithms, Valid Inequalities and Computation
Fengqiao Luo, Jeffrey Larson
Platooning of vehicles is a promising approach for reducing fuel consumption, increasing vehicle safety, and using road space more efficiently. We consider the important but diffic…
Multistart Methods for Quantum Approximate Optimization
Ruslan Shaydulin, Ilya Safro, Jeffrey Larson
Hybrid quantum-classical algorithms such as the quantum approximate optimization algorithm (QAOA) are considered one of the most promising approaches for leveraging near-term quant…