A distributed quantum Gaussian process framework is introduced for multi-agent systems with a consensus Riemannian ADMM algorithm, evaluated on elevation datasets via quantum simulator.
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Combining dynamical decoupling and zero-noise extrapolation on real quantum hardware improves energy gap estimates by at least 60% and reduces time-evolution errors by up to 99% for the Ising model in dynamic circuit Hamiltonian simulations.
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Distributed Quantum Gaussian Processes for Multi-Agent Systems
A distributed quantum Gaussian process framework is introduced for multi-agent systems with a consensus Riemannian ADMM algorithm, evaluated on elevation datasets via quantum simulator.
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Error Mitigation in Dynamic Circuits for Hamiltonian Simulation
Combining dynamical decoupling and zero-noise extrapolation on real quantum hardware improves energy gap estimates by at least 60% and reduces time-evolution errors by up to 99% for the Ising model in dynamic circuit Hamiltonian simulations.