2 citations · 2 across the 1 of their papers we have counts for
4 papers
Physics-Informed Neural Networks for the Quantum Droplets in Binary Bose-Einstein Condensates
Dongshuai Liu, Boris A. Malomed, Wen Zhang
Physics-Informed Neural Networks (PINNs), which integrate deep learning with physical prior knowledge, have proven to be a powerful tool for studying the dynamics of high-dimension…
Robust quantum-droplet necklace clusters in three dimensions
Liangwei Dong, Dongshuai Liu, Boris A. Malomed
We report the existence of quasi-stable ring-shaped (necklace-shaped) clusters built, in the free space, of 3D quantum droplets (QDs) in a binary Bose-Einstein condensate, modeled…
Physics-informed neural network for nonlinear dynamics of self-trapped necklace beams
Dongshuai Liu, Wen Zhang, Yanxia Gao +3
A physics-informed neural network (PINN) is used to produce a variety of self-trapped necklace solutions of the (2+1)-dimensional nonlinear Schrödinger/Gross-Pitaevskii equation.…
Rotating dipole and quadrupole quantum droplets in binary Bose-Einstein condensates
Dongshuai Liu, Yanxia Gao, Dianyuan Fan +2
Quantum droplets (QDs) are self-trapped modes stabilized by the Lee-Huang-Yang correction to the mean-field Hamiltonian of binary atomic Bose-Einstein condensates. The existence an…