Journal Club for Quantum Physics and Machine Learning



Next Journal Club Meeting: Tuesday, 26th January 2021, 3pm CET.

Julian Arnold (University of Basel) will present the following paper: Interpretable and unsupervised phase classification.

Abstract: Fully automated classification methods that yield direct physical insights into phase diagrams are of current interest. Here, we demonstrate an unsupervised machine learning method for phase classification which is rendered interpretable via an analytical derivation of its optimal predictions and allows for an automated construction scheme for order parameters. Based on these findings, we propose and apply an alternative, physically-motivated, data-driven scheme which relies on the difference between mean input features. This mean-based method is computationally cheap and directly interpretable. As an example, we consider the physically rich ground-state phase diagram of the spinless Falicov-Kimball model.


Upcoming Journal Club meetings:

Date Time Speaker Affiliation Reference
26th January 2021 3pm CET  Julian Arnold  University of Basel Interpretable and unsupervised phase classification
9th February 2021 3pm CET  Shahnawaz Ahmed  Chalmers University of  Technology Classification and reconstruction of optical quantum states with deep neural networks
23rd February 2021 4:30pm CET  TBA  TBA   TBA
9th March 2021 4:30pm CET  Axel Lode  University of Freiburg  TBA
23rd March 2021 4:30pm CET  TBA  TBA  TBA


Past Journal Club Meetings:

Date Time Speaker Affiliation Reference
 12th January 2021  3pm CET  Paolo Molignini  University of Cambridge Scientific intuition inspired by machine learning generated hypotheses
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