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.
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
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.
ETH physicists have developed a silicon wafer that behaves like a topological insulator when stimulated using ultrasound. They have thereby succeeded in turning an abstract theoretical concept into a macroscopic product.
Five ETH researchers receive one of the coveted Consolidator Grants from the European Research Council (ERC), among them physicist Sebastian Huber. Their projects are funded with around two million Swiss francs each.
Metamaterials are artificially designed materials which possess properties that go beyond those of their building blocks. In particular, mechanical metamaterials are used for the controlled manipulation of sound waves that travel through a medium. In our research we concentrate on the transfer of ideas and know-how from the study of low-temperature electronic phenomena, such as topological insulators, to the arena of classical mechanical systems. Topological metamaterials
Learning physics
We use machine learning to bring physical model buidling a step further. We believe that by formulating the scientific method in a way that is amenable to an automated learning process, we will be able to tackle problems that are intractable today. We use a variety of methods ranging from pure information theory over deep convolutional networks to tools from reinforcement learning to further our understanding of complex phases of matter.
Strong correlation effects can arise from a variety of sources. Our expertise lies in the study of systems with flat Bloch bands: systems where already individual particles behave fundamentally different from what we are used to. Our research spans from the investigation of the fate of Bose Einstein condensation on frustrated lattices over the description of topology-induced superconductivity on flat bands to the study of strongly inteacting quantum magnets. Correlations and flat bands
