Far off-resonance DLCZ (FORD) quantum memory.Image credit: Xianmin Jin

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  • Article | | open

    Understanding nanoscale temperature gradients in magnetic materials and how it affects their properties can help widen their potential applications. The authors analyze the anomalous Nernst effect in magnetic tunnel junctions and report how temperature gradients influence the thermomagnetic properties in three dimensions.

    • Ulrike Martens
    • , Torsten Huebner
    • , Henning Ulrichs
    • , Oliver Reimer
    • , Timo Kuschel
    • , Ronnie R. Tamming
    • , Chia-Lin Chang
    • , Raanan I. Tobey
    • , Andy Thomas
    • , Markus Münzenberg
    •  & Jakob Walowski
  • Article | | open

    Silicon holds the promise of hosting future photonic circuitries, but its centrosymmetric crystal structure precludes the exploitation of beneficial second-order nonlinearities. The authors demonstrate that strain fields can enable such nonlinearities in silicon, showing high-speed optical modulation through the so-called Pockels effect.

    • Mathias Berciano
    • , Guillaume Marcaud
    • , Pedro Damas
    • , Xavier Le Roux
    • , Paul Crozat
    • , Carlos Alonso Ramos
    • , Diego Pérez Galacho
    • , Daniel Benedikovic
    • , Delphine Marris-Morini
    • , Eric Cassan
    •  & Laurent Vivien
  • Article | | open

    Two-dimensional surface waves play an important role in optical systems such as sensing devices. The authors experimentally and theoretically demonstrate a method for multiple self-healing surface wave beams which can help overcome issues related to reduction in signal strength when surface waves encounter obstacles during their propagation.

    • Myun-Sik Kim
    • , Andreas Vetter
    • , Carsten Rockstuhl
    • , Babak Vosoughi Lahijani
    • , Markus Häyrinen
    • , Markku Kuittinen
    • , Matthieu Roussey
    •  & Hans Peter Herzig
  • Article | | open

    Astrophysical neutrinos are ideal to probe the high energy universe. By using observations from the IceCube Observatory, the authors demonstrate that ultrahigh energy neutrinos are associated with gamma-ray bursts and explain their energy dependent speed variation as due to Lorentz violation.

    • Yanqi Huang
    •  & Bo-Qiang Ma
  • Article | | open

    Electronic properties of domain walls and skyrmions are often discussed in the language of emergent fields. The authors theoretically investigate its applicability and the promises which lie beyond, revealing the unique fingerprints of chiral magnetic textures in the orbital magnetism.

    • Fabian R. Lux
    • , Frank Freimuth
    • , Stefan Blügel
    •  & Yuriy Mokrousov
  • Article | | open

    Crystal deformation has been the subject of intense studies and debates since the discovery of dislocation in 1934. The paper presents an experimental study via electron imaging of a high entropy alloy to follow dislocation activities that lead to the dislocation avalanche occurring in the material.

    • Yang Hu
    • , Li Shu
    • , Qun Yang
    • , Wei Guo
    • , Peter K. Liaw
    • , Karin A. Dahmen
    •  & Jian-Min Zuo
  • Article | | open

    A field effect transistor is a device which can alter its electrical conductivity by application of a voltage and is an important component of modern day circuitry. The authors construct an acoustic electronic device called a phonotransistor where the conductivity can instead be altered by sound pulses.

    • Caroline L. Poyser
    • , Lianhe H. Li
    • , Richard P. Campion
    • , Andrey V. Akimov
    • , Edmund H. Linfield
    • , A. Giles Davies
    • , John E. Cunningham
    •  & Anthony J. Kent
  • Article | | open

    Machine learning techniques are increasingly expanding their capabilities of making predictions on data across a variety of fields. The authors present a machine learning based approach capable of classifying the three-dimensional spatial electromagnetic field distributions of photonic crystals.

    • Carlo Barth
    •  & Christiane Becker
  • Article | | open

    Topological photonics is a growing field with applications spanning from integrated optics to lasers. This study presents a machine learning method to solve the inverse problem that may help finding optimized solutions to engineer the topology for each specific application

    • Laura Pilozzi
    • , Francis A. Farrelly
    • , Giulia Marcucci
    •  & Claudio Conti

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