A determinant-based neural network ansatz computes multiple low-lying excited states of long-range interacting spin systems with up to 300 ions, with benchmarks on exactly solvable models.
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Solving excited states for long-range interacting trapped ions with neural networks
A determinant-based neural network ansatz computes multiple low-lying excited states of long-range interacting spin systems with up to 300 ions, with benchmarks on exactly solvable models.