Trapped ions are among the most advanced technology platforms for quantum simulation of spin models, due to their long coherence time, high fidelity initialization and detection of individual spins, and the ability to simulate various types of Hamiltonians. By manipulating phonon-mediated long-ranged interactions between ion spins, programmable spin-spin interaction graphs can be engineered. In this talk, I'll describe analog and analog-digital hybrid  quantum simulation protocols to simulate programmable 2D and 3D spin models in a linear ion chain. Modern machine learning methods can accelerate  the programming speed of such simulators. I'll introduce two experimental systems that we are building at Waterloo - a quantum simulator for programmable spin Hamiltonians, and 'QuantumION' - an open-access, multi-user quantum computer for the academic community.
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