activity
20242026
collaborators

12 papers

cond-mat.str-el2026

Real-space topology and charge order in the Haldane-Holstein Model

Sebastião dos Anjos Sousa-Júnior, Julián Faúndez, Tarik P. Cysne +2

We study the half-filled Haldane-Holstein model, where a paradigmatic Chern insulator is coupled to fully dynamical phonons, and provide an unbiased characterization of how retarde…

cond-mat.quant-gas2026

Trion formation and ordering in the attractive SU(3) Fermi-Hubbard model

Jonathan Stepp, Eduardo Ibarra-García-Padilla, Eduardo Ibarra-García-Padilla +2

Recent advances in microwave shielding have increased the stability and control of large numbers of polar molecules, allowing for the first realization of a molecular Bose-Einstein…

cond-mat.str-el2026

Photodynamic melting of phase-reversed charge stripes and enhanced condensation

Jianhao Sun, Richard T. Scalettar, Rubem Mondaini

The interplay between charge stripes and pairing has long been a subject of scrutiny in a broad class of unconventional superconductors, as in some cases it is unclear whether this…

cond-mat.str-el2025

Sign-Resolved Statistics and the Origin of Bias in Quantum Monte Carlo

Ryan Larson, Rubem Mondaini, Richard T. Scalettar

Quantum simulations are a powerful tool for exploring strongly correlated many-body phenomena. Yet, their reach is limited by the fermion sign problem, which causes configuration w…

cond-mat.quant-gas2025

Unit-density SU(3) Fermi-Hubbard Model with Spin Flavor Imbalance

Zewen Zhang, Qinyuan Zheng, Eduardo Ibarra-Garcia-Padilla +2

The advent of ultracold alkaline-earth atoms in optical lattices has established a platform for investigating correlated quantum matter with SU() symmetry, offering highly tunab…

cond-mat.str-el2025

Autoregressive neural quantum states of Fermi Hubbard models

Eduardo Ibarra-García-Padilla, Hannah Lange, Roger G Melko +4

Neural quantum states (NQS) have emerged as a powerful ansatz for variational quantum Monte Carlo studies of strongly-correlated systems. Here, we apply recurrent neural networks (…