collaborators

6 papers

cond-mat.mes-hall2026

Relaxation-driven flat bands and topology in moiré transition metal dichalcogenide heterobilayers

Mitchell Luskin, Max Geier, Liang Fu +1

Moiré transition metal dichalcogenide (TMD) heterobilayers are commonly modeled by a continuum theory that yields topologically trivial bands, in contrast to their homobilayer coun…

cond-mat.str-el2026

Attention-Based Foundation Model for Quantum States

Timothy Zaklama, Daniele Guerci, Liang Fu

We present an attention-based foundation model architecture for learning and predicting quantum states across Hamiltonian parameters, system sizes, and physical systems. Using only…

cond-mat.str-el2026

Large Electron Model: A Universal Ground State Predictor

Timothy Zaklama, Max Geier, Liang Fu

We introduce Large Electron Model, a single neural network model that produces variational wavefunctions of interacting electrons over the entire Hamiltonian parameter manifold. Ou…

cond-mat.str-el2025

Is attention all you need to solve the correlated electron problem?

Max Geier, Khachatur Nazaryan, Timothy Zaklama +1

The attention mechanism has transformed artificial intelligence research by its ability to learn relations between objects. In this work, we explore how a many-body wavefunction an…

cond-mat.str-el2025

Solving fractional electron states in twisted MoTe with deep neural network

Di Luo, Timothy Zaklama, Liang Fu

The emergence of moiré materials, such as twisted transition-metal dichalcogenides (TMDs), has created a fertile ground for discovering novel quantum phases of matter. However, so…

cond-mat.str-el2025

Structure factor and topological bound of twisted bilayer semiconductors at fractional fillings

Timothy Zaklama, Di Luo, Liang Fu

The structure factor is a useful observable for probing charge density correlations in real materials, and its long-wavelength behavior encapsulated by ``quantum weight'' has recen…