CMT-QO News
How to handle fragile states
A concept known as ‘fragile topology’ has been puzzling physicists ever since it emerged two years ago. Two teams, one led by ETH physicists, have now developed a comprehensive theoretical and experimental framework to pin down the essence of the concept — and establish ways how to potentially harness it in applications.
Weyl goes chiral
Quasiparticles that behave like massless fermions, known as Weyl fermions, have been in recent years at the centre of a string of exciting findings in condensed matter physics. The group of Sebastian Huber at ETH Zurich now reports experiments in which they got a handle on one of the defining properties of Weyl fermions — their chirality
Cluster-update recommenders in Monte Carlo simulations
Nobuyuki Yoshioka
Machine Learning with Tensor Networks
Eliska Greplova
Teaching machines to spot the essential
Two physicists at ETH Zurich and the Hebrew University of Jerusalem have developed a novel machine-learning algorithm that analyses large data sets describing a physical system and extract from them the essential information needed to understand the underlying physics.
Machine learning topological phases
Valerio Peri
Exact Wavefunctions with Deep Neural Networks
Frank Schindler
Reinforcement learning of the many-body wave function on RBMs
Luca Papariello
Supervised 'Machine Learning Phases of Matter'
Mark H Fischer
From PCA to Variational Autoencoders
Sebastian Huber