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Machine learning discovery of new phases in programmable quantum simulator snapshots
Cole Miles, Rhine Samajdar, Sepehr Ebadi +7
Machine learning has recently emerged as a promising approach for studying complex phenomena characterized by rich datasets. In particular, data-centric approaches lend to the poss…
A quantum processor based on coherent transport of entangled atom arrays
Dolev Bluvstein, Harry Levine, Giulia Semeghini +9
The ability to engineer parallel, programmable operations between desired qubits within a quantum processor is central for building scalable quantum information systems. In most st…
Dispersive optical systems for scalable Raman driving of hyperfine qubits
Harry Levine, Dolev Bluvstein, Alexander Keesling +7
Hyperfine atomic states are among the most promising candidates for qubit encoding in quantum information processing. In atomic systems, hyperfine transitions are typically driven…
Probing Topological Spin Liquids on a Programmable Quantum Simulator
Giulia Semeghini, Harry Levine, Alexander Keesling +13
Quantum spin liquids, exotic phases of matter with topological order, have been a major focus of explorations in physical science for the past several decades. Such phases feature…