activity
20072023
most citedMany-body localization, thermalization, and entanglement

1.8k citations · 10.5k across the 67 of their papers we have counts for

collaborators

67 papers

cond-mat.dis-nn2023★ 8 cited

Many-body localization proximity effect in two-species bosonic Hubbard model

Pietro Brighi, Marko Ljubotina, Dmitry A. Abanin +1

The many-body localization (MBL) proximity effect is an intriguing phenomenon where a thermal bath localizes due to the interaction with a disordered system. The interplay of therm…

cond-mat.supr-con2022★ 51 cited

Multilayer graphenes as a platform for interaction-driven physics and topological superconductivity

Areg Ghazaryan, Tobias Holder, Erez Berg +1

Motivated by the recent discoveries of superconductivity in bilayer and trilayer graphene, we theoretically investigate superconductivity and other interaction-driven phases in mul…

quant-ph2022★ 48 cited

Hilbert space fragmentation and slow dynamics in particle-conserving quantum East models

Pietro Brighi, Marko Ljubotina, Maksym Serbyn

Quantum kinetically constrained models have recently attracted significant attention due to their anomalous dynamics and thermalization. In this work, we introduce a hitherto unexp…

cond-mat.mes-hall2022★ 4 cited

Deep learning extraction of band structure parameters from density of states: a case study on trilayer graphene

Paul Henderson, Areg Ghazaryan, Alexander A. Zibrov +2

The development of two-dimensional materials has resulted in a diverse range of novel, high-quality compounds with increasing complexity. A key requirement for a comprehensive quan…

cond-mat.stat-mech2022★ 46 cited

Superdiffusive Energy Transport in Kinetically Constrained Models

Marko Ljubotina, Jean-Yves Desaules, Maksym Serbyn +1

Universal nonequilibrium properties of isolated quantum systems are typically probed by studying transport of conserved quantities, such as charge or spin, while transport of energ…

quant-ph2022★ 20 cited

Recursive greedy initialization of the quantum approximate optimization algorithm with guaranteed improvement

Stefan H. Sack, Raimel A. Medina, Richard Kueng +1

The quantum approximate optimization algorithm (QAOA) is a variational quantum algorithm, where a quantum computer implements a variational ansatz consisting of layers of alter…