collaborators

5 papers

math.OC2026

Birkhoff interpolation models for optimization with some available derivatives

Jeffrey Larson, Matt Menickelly, Evan Toler

We consider interpolation-based derivative-free optimization in settings where only some derivatives are available. Such situations arise in scientific computing applications invol…

quant-ph2026

Variational quantum state preparation within an entangle-rotate circuit framework for quantum-enhanced metrology in noisy systems

Juan C. Zuñiga Castro, Jeffrey Larson, Matt Menickelly +4

We investigate the generation of quantum states for precision metrology in noisy two-level systems. These states are obtained by optimizing a variational quantum circuit to maximiz…

quant-ph2025

Roadblocks and Opportunities in Quantum Algorithms -- Insights from the National Quantum Initiative Joint Algorithms Workshop, May 20--22, 2024

Eliot Kapit, Peter Love, Jeffrey Larson +6

The National Quantum Initiative Joint Algorithms Workshop brought together researchers across academia, national laboratories, and industry to assess the current landscape of quant…

quant-ph2025

A Noise-Aware Scalable Subspace Classical Optimizer for the Quantum Approximate Optimization Algorithm

Kwassi Joseph Dzahini, Jeffrey M. Larson, Matt Menickelly +1

We introduce ANASTAARS, a noise-aware scalable classical optimizer for variational quantum algorithms such as the quantum approximate optimization algorithm (QAOA). ANASTAARS lever…

quant-ph2025

State Dependent Optimization with Quantum Circuit Cutting

Xinpeng Li, Ji Liu, Jeffrey M. Larson +4

Quantum circuits can be reduced through optimization to better fit the constraints of quantum hardware. One such method, initial-state dependent optimization (ISDO), reduces gate c…