3 papers
cond-mat.quant-gas2021
Unsupervised machine learning of topological phase transitions from experimental data
Niklas Käming, Anna Dawid, Korbinian Kottmann +4
Identifying phase transitions is one of the key challenges in quantum many-body physics. Recently, machine learning methods have been shown to be an alternative way of localising p…
quant-ph2020
Phase Detection with Neural Networks: Interpreting the Black Box
Anna Dawid, Patrick Huembeli, Michał Tomza +2
Neural networks (NNs) usually hinder any insight into the reasoning behind their predictions. We demonstrate how influence functions can unravel the black box of NN when trained to…
physics.atom-ph2018
Two interacting ultracold molecules in a one-dimensional harmonic trap
Anna Dawid, Maciej Lewenstein, Michał Tomza
We investigate the properties of two interacting ultracold polar molecules described as distinguishable quantum rigid rotors, trapped in a one-dimensional harmonic potential. The m…