Atomic, molecular & optical physics
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- Ultracold polar molecules for quantum science and technology
- Observation of Scaling of Higher-Order Flow in a Unitary Fermi Gas
- Vortices in a two-dimensional fermionic superfluid
- Synchronization in one-dimensional arrays of photon condensates
- Single-anchor Delta-learning with the cluster Gutzwiller approximation: predicting phase boundaries of strongly correlated bosons in optical lattices
- Rotating two-dimensional Bose--Einstein condensates in power-law traps: collapse, Thomas--Fermi scaling, and the inverse-square endpoint
- Bulk and edge states in Fibonacci-Bose-Hubbard clusters
- Bayesian optimization enhanced magnetic field gradient detection based on spin-orbit coupled Bose-Einstein condensates
- Wavefront engineering with atomic Huygens' surfaces made simple
- Altermagnetism-induced Fulde-Ferrell-Larkin-Ovchinnikov superfluids and momentum-selective pairing channels in optical lattices
- Accurate representation of the continuum orbital in a Gaussian basis set: application to Auger decay rates
- A Two-Dimensional Physics-Informed Neural Network Model of a Hall Effect Thruster Plasma: Self-Consistent Electrostatics and Physical-Consistency Diagnostics
- Observation of s-p Coupling in Ultralong-Range Rydberg Molecules
- State preparation and detection for quantum simulation of particle collisions
- Measurement-induced spatially nonuniform fluctuations of the local particle number and their crossover in a quasiperiodic free-fermion chain
- Nanoscale etching characteristics for controlled AFM tomography of amorphous chalcogenide thin films.
- An atomistic workflow for determining acid–base prototropic tautomer microstate populations
- Torsion induced anisotropic energy propagation due to external perturbation
- Coupled propagation of acoustic topological states
- Cross-scale temporal retrieval method for modulated electron beams via adaptive kernel reconstruction
- Optimal weight allocation for steering network dynamics to a target time scale
- Compact and stable representation of real-frequency spectral functions for machine learning
- Approaching the limit of quantum clock precision
- Fundamental limits to identifying node and tie memory in temporal networks: marginal artefacts and spreading dynamics
- Passage of particles through matter and the effective straggling-function: High-fidelity accelerated simulation via Physics-Informed Machine Learning