3 papers
math.OC2024
Estimating Computational Noise on Parametric Curves
Matt Menickelly
We consider ECNoise, a practical tool for estimating the magnitude of noise in evaluations of a black-box function. Recent developments in numerical optimization algorithms have se…
math.OC2024
Two-Stage Estimation and Variance Modeling for Latency-Constrained Variational Quantum Algorithms
Yunsoo Ha, Sara Shashaani, Matt Menickelly
The Quantum Approximate Optimization Algorithm (QAOA) has enjoyed increasing attention in noisy intermediate-scale quantum computing due to its application to combinatorial optimiz…
math.OC2023
Avoiding Geometry Improvement in Derivative-Free Model-Based Methods via Randomization
Matt Menickelly
We present a technique for model-based derivative-free optimization called \emph{basis sketching}. Basis sketching consists of taking random sketches of the Vandermonde matrix empl…