activity
20172024
most citedNeural-Network Quantum States, String-Bond States, and Chiral Topological States

213 citations · 559 across the 10 of their papers we have counts for

collaborators

9 papers

cond-mat.stat-mech2024★ 3 cited

State-dependent mobility edge in kinetically constrained models

Manthan Badbaria, Nicola Pancotti, Rajeev Singh +2

In this work, we show that the kinetically constrained quantum East model lies between a quantum scarred and a many-body localized system featuring an unconventional type of mobili…

cond-mat.stat-mech2023★ 26 cited

Rydberg platform for non-ergodic chiral quantum dynamics

Riccardo J. Valencia-Tortora, Nicola Pancotti, Michael Fleischhauer +2

We propose a mechanism for engineering chiral interactions in Rydberg atoms via a directional antiblockade condition, where an atom can change its state only if an atom to its righ…

cond-mat.stat-mech2021★ 33 cited

Kinetically Constrained Quantum Dynamics in Superconducting Circuits

Riccardo J. Valencia-Tortora, Nicola Pancotti, Jamir Marino

We study the dynamical properties of the bosonic quantum East model at low temperature. We show that a naive generalization of the corresponding spin-1/2 quantum East model does no…

quant-ph2019★ 50 cited

Speed-ups to isothermality: Enhanced quantum thermal machines through control of the system-bath coupling

Nicola Pancotti, Matteo Scandi, Mark T. Mitchison +1

Isothermal transformations are minimally dissipative but slow processes, as the system needs to remain close to thermal equilibrium along the protocol. Here, we show that smoothly…

cond-mat.stat-mech2019★ 91 cited

Quantum East model: localization, non-thermal eigenstates and slow dynamics

Nicola Pancotti, Giacomo Giudice, J. Ignacio Cirac +2

We study in detail the properties of the quantum East model, an interacting quantum spin chain inspired by simple kinetically-constrained models of classical glasses. Through a com…

cs.LG2019★ 23 cited

Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning

Ivan Glasser, Ryan Sweke, Nicola Pancotti +2

Tensor-network techniques have enjoyed outstanding success in physics, and have recently attracted attention in machine learning, both as a tool for the formulation of new learning…

quant-ph2018★ 10 cited

From probabilistic graphical models to generalized tensor networks for supervised learning

Ivan Glasser, Nicola Pancotti, J. Ignacio Cirac

Tensor networks have found a wide use in a variety of applications in physics and computer science, recently leading to both theoretical insights as well as practical algorithms in…

quant-ph2017★ 213 cited

Neural-Network Quantum States, String-Bond States, and Chiral Topological States

Ivan Glasser, Nicola Pancotti, Moritz August +2

Neural-Network Quantum States have been recently introduced as an Ansatz for describing the wave function of quantum many-body systems. We show that there are strong connections be…

cond-mat.dis-nn2017★ 19 cited

Almost-conserved operators in nearly many-body localized systems

Nicola Pancotti, Michael Knap, David A. Huse +2

We construct almost conserved local operators, that possess a minimal commutator with the Hamiltonian of the system, near the many-body localization transition of a one-dimensional…