Optimizing the dynamical preparation of quantum spin lakes on the ruby lattice
arXiv:2512.09040 · doi:10.1103/7dnl-6kg2
Abstract
Quantum spin liquids are elusive long-range entangled states. Motivated by experiments in Rydberg quantum simulators, recent excitement has centered on the possibility of dynamically preparing a state with quantum spin liquid correlation even when the ground state phase diagram does not exhibit such a topological phase. Understanding the microscopic nature of such quantum spin "lake" states and their relationship to equilibrium spin liquid order remains an essential question. Here, we extend the use of approximately symmetric neural quantum states for real-time evolution and directly simulate the dynamical preparation in systems of up to atoms. We analyze a variety of spin liquid diagnostics as a function of the preparation protocol and optimize the extent of the quantum spin lake thus obtained. In the optimal case, the prepared state shows spin-liquid properties extending over half the system size, with a topological entanglement entropy plateauing close to . We extract two physical length scales and which constrain the extent of the quantum spin lake from above and below.
References in corpus (44)
- Topological entanglement entropy
- Solving the Quantum Many-Body Problem with Artificial Neural Networks
- Quantum Spin Liquids
- Rank-normalization, folding, and localization: An improved for assessing convergence of MCMC
- Spin Liquid State in an Organic Mott Insulator with Triangular Lattice
- Quantum Phases of Matter on a 256-Atom Programmable Quantum Simulator
- Probing Topological Spin Liquids on a Programmable Quantum Simulator
- A Field Guide to Spin Liquids
- Emergence and Frustration of Magnetic Order with Variable-Range Interactions in a Trapped Ion Quantum Simulator
- Measuring Renyi Entanglement Entropy with Quantum Monte Carlo
- Reconstructing quantum states with generative models
- Symmetries and many-body excited states with neural-network quantum states
- Study of the Two-Dimensional Frustrated J1-J2 Model with Neural Network Quantum States
- Experimental identification of quantum spin liquids
- Quantum many-body dynamics in two dimensions with artificial neural networks
- Prediction of Toric Code Topological Order from Rydberg Blockade
- Robustness of the thermal Hall effect close to half-quantization in a field-induced spin liquid state
- Backflow Transformations via Neural Networks for Quantum Many-Body Wave-Functions
- Non-Abelian Topological Order and Anyons on a Trapped-Ion Processor
- The planar thermal Hall conductivity in the Kitaev magnet α-RuCl3
- Latent Space Purification via Neural Density Operators
- Adiabatic Preparation of Topological Order
- Quantum phase transition dynamics in the two-dimensional transverse-field Ising model
- A tweezer array with 6100 highly coherent atomic qubits
- Diagnosing Deconfinement and Topological Order
- High-accuracy variational Monte Carlo for frustrated magnets with deep neural networks
- Non-Abelian braiding of Fibonacci anyons with a superconducting processor
- Gauge Invariant and Anyonic Symmetric Transformer and RNN Quantum States for Quantum Lattice Models
- Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution
- Unifying Kitaev magnets, kagome dimer models and ruby Rydberg spin liquids
- Purifying Deep Boltzmann Machines for Thermal Quantum States
- Spectral evidence for Dirac spinons in a kagome lattice antiferromagnet
- Gauge equivariant neural networks for quantum lattice gauge theories
- Gauge-theoretic origin of Rydberg quantum spin liquids
- Unconventional Magnetic Oscillations in Kagome Mott Insulators
- Trimer states with topological order in Rydberg atom arrays
- Preparing Atomic Topological Quantum Matter by Adiabatic Nonunitary Dynamics
- Highly resolved spectral functions of two-dimensional systems with neural quantum states
- Critical behavior of Fredenhagen-Marcu string order parameters at topological phase transitions with emergent higher-form symmetries
- Qutrit Toric Code and Parafermions in Trapped Ions
- Engineering the Kitaev spin liquid in a quantum dot system
- Quantum state preparation of topological chiral spin liquids via Floquet engineering
- Predicting Topological Entanglement Entropy in a Rydberg analog simulator
- Approximately-symmetric neural networks for quantum spin liquids