HZB Newsroom

With increasing size and complexity, quantum computers become a sort of black box. Using methods from mathematical physics, a team has now succeeded in deriving concrete numbers from random, data sequences that can serve as a benchmark for the performance of a quantum computer system. Experts from Helmholtz-Zentrum Berlin, Freie Universität Berlin, Qusoft Research Centre Amsterdam, the University of Copenhagen and the Technology Innovation Institute Abu Dhabi were involved in the work, which has now been published in Nature Communications.

X-ray microscopy (cryo-SXT) enables high-resolution insights into cells and cell organelles - in three dimensions. Until now, the 3D data sets have been analysed manually, which is very time-consuming. A team from Freie Universität Berlin has now developed a self-learning algorithm based on a convolutional neural network. In collaboration with experts in cell biology (FU Berlin) and X-ray microscopy at the Helmholtz Zentrum Berlin, this algorithm has now been used for the first time to analyse cell components in cryo-SXT data sets. It identified cell organelles and produced highly detailed, complex 3D images within a few minutes.