most citedPotential Applications of Quantum Computing at Los Alamos National Laboratory

3 citations · 3 across the 1 of their papers we have counts for

collaborators

5 papers

quant-ph20263 cited

Potential Applications of Quantum Computing at Los Alamos National Laboratory

Andreas Bärtschi, Francesco Caravelli, Carleton Coffrin +16

The emergence of quantum computing technology over the last decade indicates the potential for a transformational impact in the study of quantum mechanical systems. It is natural t…

quant-ph2026

Snapshot-QAOA: Extending QAOA to Quantum Hamiltonian Simulation

Reuben Tate, Quinn Langfitt, Elijah Pelofske +4

We present Snapshot-QAOA, a variation of the Quantum Approximate Optimization Algorithm (QAOA) that finds approximate minimum energy eigenstates of a large set of quantum Hamiltoni…

quant-ph2026

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms

Elijah Pelofske, Marek Rams, Andreas Bärtschi +4

The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One…

quant-ph2025

Quantum Data Learning of Topological-to-Ferromagnetic Phase Transitions in the 2+1D Toric Code Loop Gas Model

Shamminuj Aktar, Rishabh Bhardwaj, Andreas Bärtschi +2

Quantum data learning (QDL) provides a framework for extracting physical insights directly from quantum states, bypassing the need for any identification of the classical observabl…

quant-ph2025

Variational Quantum Simulations of a Two-Dimensional Frustrated Transverse-Field Ising Model on a Trapped-Ion Quantum Computer

Ammar Kirmani, Elijah Pelofske, Andreas Bärtschi +2

Quantum computers are an ideal platform to study the ground state properties of strongly correlated systems due to the limitation of classical computing techniques particularly for…