A trapped-ion quantum computer simulates 2+1D Z2 lattice gauge theory dynamics, revealing glueball excitations and multi-order string breaking.
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Helios achieves 98 qubits with single-qubit gate infidelity 2.5(1)×10^{-5}, two-qubit 7.9(2)×10^{-4}, and SPAM 4.8(6)×10^{-4}, enabling circuits beyond classical simulation.
Reinforcement learning optimizes ion shuttling on trapped-ion quantum chips and reduces operations by up to 36.3% versus heuristics across multiple architectures.
citing papers explorer
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Observation of glueball excitations and string breaking in a $2+1$D $\mathbb{Z}_2$ lattice gauge theory on a trapped-ion quantum computer
A trapped-ion quantum computer simulates 2+1D Z2 lattice gauge theory dynamics, revealing glueball excitations and multi-order string breaking.
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Helios: A 98-qubit trapped-ion quantum computer
Helios achieves 98 qubits with single-qubit gate infidelity 2.5(1)×10^{-5}, two-qubit 7.9(2)×10^{-4}, and SPAM 4.8(6)×10^{-4}, enabling circuits beyond classical simulation.
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Reinforcement learning for ion shuttling on trapped-ion quantum computers
Reinforcement learning optimizes ion shuttling on trapped-ion quantum chips and reduces operations by up to 36.3% versus heuristics across multiple architectures.