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most citedPotential Applications of Quantum Computing at Los Alamos National Laboratory

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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-ph2025

Lower bounds on the number of rounds of the quantum approximate optimization algorithm required for guaranteed approximation ratios

Naphan Benchasattabuse, Andreas Bärtschi, Luis Pedro García-Pintos +3

The quantum approximate optimization algorithm, also known in its generalization as the quantum alternating operator ansatz, (QAOA) is a heuristic hybrid quantum-classical algorith…

quant-ph2025

Scalable Experimental Bounds for Entangled Quantum State Fidelities

Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy +1

Estimating the state preparation fidelity of highly entangled states on noisy intermediate-scale quantum (NISQ) devices is important for benchmarking and application considerations…

quant-ph2024

Scaling Whole-Chip QAOA for Higher-Order Ising Spin Glass Models on Heavy-Hex Graphs

Elijah Pelofske, Andreas Bärtschi, Lukasz Cincio +2

We show through numerical simulation that the Quantum Approximate Optimization Algorithm (QAOA) for higher-order, random-coefficient, heavy-hex compatible spin glass Ising models h…

quant-ph2024

Simulating Heavy-Hex Transverse Field Ising Model Magnetization Dynamics Using Programmable Quantum Annealers

Elijah Pelofske, Andreas Bärtschi, Stephan Eidenbenz

Recently, a Hamiltonian dynamics simulation was performed on a kicked ferromagnetic 2D transverse field Ising model with a connectivity graph native to the 127 qubit heavy-hex IBM…

quant-ph2024

Limitations for Quantum Algorithms to Solve Turbulent and Chaotic Systems

Dylan Lewis, Stephan Eidenbenz, Balasubramanya Nadiga +1

We investigate the limitations of quantum computers for solving nonlinear dynamical systems. In particular, we tighten the worst-case bounds of the quantum Carleman linearisation (…