Journal Club for Quantum Physics and Machine Learning

Schedule

 

Next Journal Club Meeting: Tuesday, 24th May 2022, 5:30pm CET.

Niklas Käming (University of Hamburg) will present the following paper: Unsupervised machine learning of topological phase transitions from experimental data

Abstract: 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 phase boundaries from noisy and imperfect data without the knowledge of the order parameter. Here, we apply different unsupervised machine learning techniques, including anomaly detection and influence functions, to experimental data from ultracold atoms. In this way, we obtain the topological phase diagram of the Haldane model in a completely unbiased fashion. We show that these methods can successfully be applied to experimental data at finite temperatures and to the data of Floquet systems when post-processing the data to a single micromotion phase. Our work provides a benchmark for the unsupervised detection of new exotic phases in complex many-body systems.

Upcoming Journal Club meetings:

Date Time Speaker Affiliation Reference
24th May 2022 5:30pm CET   Niklas Käming  Universität Hamburg Unsupervised machine learning of topological phase transitions from experimental data
7th June 2022  5:30pm CET   Francesco Carnazza   Universität Tübingen  Machine learning Markovian quantum master equations of few-body
observables in interacting spin chains
21st June 2022  5:30pm CET  Javier Robledo Moreno     Flatiron Institute / NYU   Fermionic wave functions from neural-network constrained hidden states

 

Past Journal Club Meetings:

Date Time Speaker Affiliation Reference
10th May 2022 5:30pm CET  Julian Arnold University of Basel

Replacing neural networks by optimal analytical predictors for the detection of phase transitions

26th April 2022 5:30pm CET Katerina Gratsea ICFO

Storage properties of a quantum perceptron 

12th April 2022 5:30pm CET  Anna Dawid  University of Warsaw / ICFO

Hessian-based toolbox for reliable and interpretable machine learning in physics

Slides

12th December 2021 5:30pm CET Jonathon Brown Queen's University Belfast Reinforcement learning-enhanced protocols for coherent population-transfer in three-level quantum systems
7th December 2021 5:30pm CET M. Michael Denner University of Zürich Efficient learning of a one-dimensional density functional theory
23rd November 2021  5:30pm CET Robert Huang California Institute of Technology Provably efficient machine learning for quantum many-body problems
9th November 2021  5:30pm CET Paolo Andrea Erdman Freie Universität Berlin  Identifying optimal cycles in quantum thermal machines with reinforcement-learning
26th October 2021  5:30pm CET Maciej Koch-Janusz  University of Zurich /  University of Chicago Relevant operators and symmetries through the lens of real-space mutual information
12th October 2021 5:30pm CET Moritz Reh Heidelberg University Time-dependent variational principle for open quantum systems with artificial neural networks
15th June 2021 4:30pm CET Nishad Maskara Harvard University A learning algorithm with emergent scaling behavior for classifying phase transitions
1st June 2021 4:30pm CET Rouven Koch Aalto University Neural network enhanced hybrid quantum many-body dynamical distributions
18th May 2021 4:30pm CET Wei Chen PUC Rio de Janeiro A supervised learning algorithm for interacting topological insulators based on local curvature
4th May 2021 4:30pm CET Agnes Valenti ETH Zürich  Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics
20th April 2021 4:30pm CET Rui Lin ETH Zürich 

Minimal model of permutation symmetry in unsupervised learning

Slides

6th April 2021 4:30pm CET Miriam Büttner University of Freiburg

Learning Potentials of Quantum Systems using Deep Neural Networks

Slides

 23rd March 2021 4:30pm CET Luuk Coopmans Trinity College Dublin/Dublin Institute for Advanced Studies Protocol Discovery for the Quantum Control of Majoranas by Differential Programming and Natural Evolution Strategies
 9th March 2021 4:30pm CET Axel Lode University of Freiburg

Interpretable Phase Detection and Classification with Persistent Homology

Slides

 23rd February 2021  4:30pm CET Evert van Nieuwenburg University of Copenhagen A NEAT Quantum Error Decoder
 9th February 2021  3pm CET Shahnawaz Ahmed  Chalmers University of  Technology Classification and reconstruction of optical quantum states with deep neural networks 
 26th January 2021  3pm CET Julian Arnold  University of Basel Interpretable and unsupervised phase classification
 12th January 2021  3pm CET Paolo Molignini  University of Cambridge

Scientific intuition inspired by machine learning generated hypotheses

Slides

Hits: 5351