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  • The volume of muon beams in position–momentum space is too large to be used in a collider. A clear reduction in this volume has now been demonstrated, which brings particle physics closer to a practical muon collider for exploring the energy frontier.

    • Masashi Otani
    News & Views
  • Laser-driven acceleration is a promising path towards more compact machines. Now, proton beams with energies up to 150 MeV have been achieved with a repetitive petawatt laser.

    • Jianhui Bin
    News & Views
  • Topological quantum computers are predicted to perform calculations by manipulating quasiparticles known as non-Abelian anyons. A type of non-Abelian anyon that supports universal quantum gates has now been simulated using superconducting qubits.

    • Trond I. Andersen
    • Xiao Mi
    News & Views
  • Plasmonic excitations can enhance the interaction between a metal and molecules adsorbed onto its surface. This Review summarizes the different effects involved in this process and places them into a framework based on electron scattering.

    • Andrei Stefancu
    • Naomi J. Halas
    • Emiliano Cortes
    Review Article
  • Inducing superconductivity in quantum anomalous Hall insulators is crucial to realize topological superconductors. Now a study shows superconducting correlations in the quantum anomalous Hall state, which can convert electrons on its one-way path into holes.

    • Jing Wang
    • Zhaochen Liu
    News & Views
  • An improved optimization algorithm enables the training of large-scale neural quantum states in which the enormous number of neuron connections capture the intricate complexity of quantum many-body wavefunctions. This advance leads to unprecedented accuracy in paradigmatic quantum models, opening up new avenues for simulating and understanding complex quantum phenomena.

    Research Briefing
  • Nonlinearity is crucial for sophisticated tasks in machine learning but is often difficult to engineer outside of electronics. By encoding the inputs in parameters of the system, linear systems can realize efficiently trainable nonlinear computations.

    • Peter L. McMahon
    News & Views
  • As the energy consumption of neural networks continues to grow, different approaches to deep learning are needed. A neuromorphic method offering nonlinear computation based on linear wave scattering can be implemented using integrated photonics.

    • Clara C. Wanjura
    • Florian Marquardt
    ArticleOpen Access
  • The growth of a biofilm—a bacterial colony attached to a surface—is governed by a trade-off between horizontal and vertical expansion. Now, it is shown that this process significantly depends on the contact angle at the biofilm’s edge.

    • Aawaz R. Pokhrel
    • Gabi Steinbach
    • Peter J. Yunker
    Article
  • Rhombohedral graphene is an emerging material with a rich correlated-electron phenomenology, including superconductivity. The magnetism of symmetry-broken trilayer graphene has now been explored, revealing important details of the physics and providing a roadmap for broader explorations of rhombohedral graphene.

    Research Briefing
  • It has many names and yet no name. The designation of the universal gas constant as R has remained a mystery, as Karen Mudryk recounts.

    • Karen Mudryk
    Measure for Measure
  • A multiscale model of muscle as a fluid-filled sponge suggests that hydraulics limits rapid contractions and that the mechanical response of muscle is non-reciprocal.

    • Suraj Shankar
    • L. Mahadevan
    Article
  • The complexity of a many-body quantum state grows exponentially with system size, hindering numerical studies. A unitary flow-based method now enables accurate estimates of long-term properties of one- and two-dimensional quantum systems.

    • S. J. Thomson
    • J. Eisert
    ArticleOpen Access
  • The observation of continuous time crystals has been hindered by atom loss in the ultracold regime. Long-range time-crystalline order has now been demonstrated in a dissipative Rydberg gas at room temperature.

    • Xiaoling Wu
    • Zhuqing Wang
    • Li You
    Article