EPJ Techniques and Instrumentation Highlight - Calibration samples to measure particle identification performance in the LHCb experiment

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Published on 05 March 2019

Deep underground in the Large Hadron Collider at CERN, beams of protons travel around in circles at almost the speed of light before they are collided head-on. These high-energy collisions produce large numbers of tiny, short-lived particles that quickly decay into lighter, more stable particles. Investigating these particle decays allows physicists to catch a glimpse of the early history of the universe. In new work published in EPJ Techniques and Instrumentation, Marianna Fontana and Donal Hill describe the method to create calibration samples that help determine the accuracy of the detector in the Large Hadron Collider beauty experiment in identifying different particles.

Read the guest post by Donal Hill & Marianna Fontana, originally published in the SpringerOpen blog.

EPJ A Highlight - Shape stability of pasta phases: Lasagna case

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Published on 01 March 2019

Exotic non-spherical shapes of nuclear matter, so called pasta phases, are possible because of the competition between the short-ranged nuclear attraction and the long-ranged Coulomb repulsion, leading to the phenomenon of Coulomb frustration, well known in statistical mechanics. Such complex phases are expected in the inner crust of neutron stars, as well as in core-collapse supernova cores.

The authors of the EPJ A (2018) 54:215 paper examine for the first time the stability of the «lasagna» phase, consisting of periodically placed slabs, by means of exact geometrical methods. Calculations are done in the framework of the compressible liquid drop model but obtained results are universal and do not depend on model parameters like surface tension and charge density. The stability analysis is done with respect to the different types of deformations corresponding to the eigenvalues of the deformation matrix.

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EPJ Data Science Highlight - Using deep learning to “see” inside homes across the world

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Published on 18 February 2019

How much does someone's living room tell about how they live? Peeking into another person's life might be just part of natural human curiosity, but the answer to this question may provide insights in a wide range of aspects of human behavior. A new study published in EPJ Data Science uses the power of machine learning to explore patterns of home decors—and what they could tell about their owners—in popular accommodation website Airbnb.

See guest post by Clio Andris and Xi Liu originally published in the SpringerOpen blog