Research

The rare-earth element erbium could play a key role in future quantum networks: Researchers from the Max Planck Institute of Quantum Optics (MPQ) and the Technical University of Munich (TUM), led by Andreas Reiserer, have succeeded in spectrally resolving and individually controlling up to 360 erbium ions in a thin crystal membrane — more than three times as many as before. Their findings were published in the scientific journal Advanced Optical Materials. more

Theorists have made a significant stride in the field of quantum computing. Their research addresses a long-standing question: can quantum computers really outperform classical computers in solving complex problems, despite the presence of errors? In a new study focusing on analogue quantum simulators – specialised quantum devices used to mimic physical systems – the researchers could show precisely that. more

A team of researchers from the Munich Quantum Valley, led by the Max Planck Institute of Quantum Optics in collaboration with the quantum computing start-up planqc, has succeeded in running a register of 1200 atoms continuously for over an hour. Until now, arrangements of this size have been difficult to maintain due to unavoidable atomic losses. This new achievements marks a breakthrough on the way to scalable quantum computers. more

Systems consisting of many small particles can be highly complex and chaotic – and yet some can still be described using simple theories. However, whether this also extends to the world of quantum physics has remained unclear. Researchers from Ludwig Maximilian University and the Max Planck Institute for Quantum Optics have now found indications that quantum many-body systems can be macroscopically described by simple diffusion equations with random noise. The results were recently published in Nature Physics. more

Some common diseases could be easier and quicker to diagnose in the future. A team from MPQ, LMU and Helmholtz Zentrum München has demonstrated that infrared light measurements of blood plasma when combined with machine learning can be used to detect various metabolic disorders such as type-2 diabetes and high blood pressure. The method also detected prediabetes, a precursor stage of diabetes that other diagnostic methods often overlook. more