Explainable Representation Learning of Small Quantum States

1 code implementation • 9 Jun 2023 • Felix Frohnert, Evert van Nieuwenburg

The insights from this study represent proof of concept towards interpretable machine learning of quantum states.

Feature Engineering Interpretable Machine Learning +1

Learning Coulomb Diamonds in Large Quantum Dot Arrays

1 code implementation • 3 May 2022 • Oswin Krause, Anasua Chatterjee, Ferdinand Kuemmeth, Evert van Nieuwenburg

We introduce an algorithm that is able to find the facets of Coulomb diamonds in quantum dot arrays.

A NEAT Quantum Error Decoder

3 code implementations • 20 Jan 2021 • Hugo Théveniaut, Evert van Nieuwenburg

We investigate the use of the evolutionary NEAT algorithm for the optimization of a policy network that performs quantum error decoding on the toric code, with bitflip and depolarizing noise, one qubit at a time.

Quantum Physics Computational Physics

Roof Age Determination for the Automated Site-Selection of Rooftop Solar

2 code implementations • 8 Jan 2020 • Chris Heinrich, Michael Laskin, Simas Glinskis, Evert van Nieuwenburg

Rooftop solar is one of the most promising tools for drawing down greenhouse gas (GHG) emissions and is cost-competitive with fossil fuels in many areas of the world today.

Other Computer Science

NetKet: A Machine Learning Toolkit for Many-Body Quantum Systems

1 code implementation • 29 Mar 2019 • Giuseppe Carleo, Kenny Choo, Damian Hofmann, James E. T. Smith, Tom Westerhout, Fabien Alet, Emily J. Davis, Stavros Efthymiou, Ivan Glasser, Sheng-Hsuan Lin, Marta Mauri, Guglielmo Mazzola, Christian B. Mendl, Evert van Nieuwenburg, Ossian O'Reilly, Hugo Théveniaut, Giacomo Torlai, Alexander Wietek

We introduce NetKet, a comprehensive open source framework for the study of many-body quantum systems using machine learning techniques.

Quantum Physics Disordered Systems and Neural Networks Strongly Correlated Electrons Computational Physics Data Analysis, Statistics and Probability