Electronic crystals and quasicrystals in semiconductor quantum wells: an AI-powered discovery
Filippo Gaggioli, Pierre-Antoine Graham, Liang Fu
TL;DR
This work tackles strongly correlated electrons in semiconductor quantum wells with finite thickness, revealing a rich phase diagram that includes monolayer and bilayer metallic and crystalline states, and identifying a novel bilayer electronic quasicrystal stabilized by quantum fluctuations. An unbiased attention-based NN-VMC method is developed to solve the 3D many-body Hamiltonian from first principles, constructing a flexible variational wavefunction as a sum of Slater determinants augmented by a Jastrow factor. The results show a sequence of phases with density and well thickness: bilayer Fermi liquid → bilayer crystal → monolayer Fermi liquid → monolayer Wigner crystal, with a 30° twisted bilayer quasicrystal emerging in the bilayer regime. These findings demonstrate AI-powered, first-principles discovery of new quantum phases in realistic semiconductor platforms and point to experimental tests in quantum wells and heterostructures, with implications for quantum-device design and digital-twin modeling.
Abstract
The homogeneous electron gas is a cornerstone of quantum condensed matter physics, providing the foundation for developing density functional theory and understanding electronic phases in semiconductors. However, theoretical understanding of strongly-correlated electrons in realistic semiconductor systems remains limited. In this work, we develop a neural network based variational approach to study quantum wells in three dimensional geometry for a variety of electron densities and well thicknesses. Starting from first principles, our unbiased AI-powered method reveals metallic and crystalline phases with both monolayer and bilayer charge distributions. In the emergent bilayer, we discover a new quantum phase of matter: the electronic quasicrystal.
