Browse Articles

From the cardiac system of various human patients, to changes in sea surface temperature across different oceans, dynamical systems often exhibit many common characteristics. Here we develop a framework for jointly learning the dynamics of multiple interrelated systems while leveraging their shared traits.

Reconstructing unstable heavy particles is a crucial aspect of many analyses at the Large Hadron Collider (LHC). We introduce SPA-Net, a machine-learning approach to this problem which outperforms existing baseline methods, performs several auxiliary tasks, and leads to significant improvements in three example flagship LHC analyses

Non-Hermitian (NH) systems have recently attracted great attention, and the NH bulk-boundary correspondence is a key question. The authors propose an approach to restore NH bulk-boundary correspondence by a “doubling and swapping" construction which eliminates the NH skin effect, resulting in a new NH Hamiltonian with the same energy spectrum.

Energetic neutrino beams from symmetric muon and anti-muon decays are used to study long-baseline neutrino oscillation, and constrain the Charge-Parity (CP) violation phase in the three-flavour neutrino mixing. Here, the authors provide results based on neutrino oscillation simulations to show that more than five standard deviation sensitivity on CP violation can be obtained from 5-10 years of data taken with the help of DUNE-like detectors.

Interacting electrons can collectively act as a viscous flow resembling a classical fluid, a phenomenon termed electron hydrodynamics. Here, the authors develop a framework to describe electron flow in narrow channels, demonstrating that the requirements for achieving electron hydrodynamic transport can be extended beyond what is currently considered possible.

By studying inertial spinners on an air table with different ratios between counterclockwise and clockwise species, the authors found that underdamped chiral spinners display phenomena usually unseen in overdamped chiral spinners. These include higher energy pumped into the minority species and oscillatory entropy when one species dominates the other.

Simulating turbulent fluids is a major computational challenge, the main obstacle being the large size of discretized meshes required to accurately describe turbulent flows. The authors develop a quantum-inspired framework, based on matrix product states, to solve for flows around immersed bodies with complexity scaling logarithmically in the mesh size.

In quantum physics, superposition—illustrated by Schrödinger’s cat being both dead and alive—inspires ‘cat states’, utilized in quantum technologies. The authors propose a theory where the optical state, through multiple indirect atom interactions in an interferometric setup, can generate large-amplitude optical cat states, advancing quantum applications.

Precision measurements with atom interferometers benefit from reducing the expansion rate of the atomic ensemble within the interferometric beam through matter-wave collimation. Here we demonstrate a collimation method based on time-averaged optical potentials and tunable interactions, realizing expansion energies of a few hundred picokelvin.

The first-order phase boundary between the liquid and gaseous phases ends at a critical point where the fluid, kept at thermodynamic equilibrium, displays a turbidity known as ‘critical opalescence’. The authors quench a fluid across its critical point, find blackness instead of turbidity, and argue that, out of equilibrium, photons can be absorbed, not merely scattered.

Topological solitons can be realised in a range of platforms that have the potential for processing topologically protected information. Here, the authors identify a class of vector solitons in a mechanical lattice, showing superposed kinks and invertible polarizations, with implications for nonlinear topological mechanics.

Baryon Acoustic Oscillations (BAO) are formed in the early universe and can be measured galaxy redshift survey to probe dark energy, but this feature is degraded with galaxy structure evolution. The authors propose a method that simultaneously use pre- and post-reconstruction power spectra to extract higher order information for surveys to constrain cosmological models.

Directed hypergraphs emerge as a potent framework for analyzing social contagion phenomena, incorporating the nuances of individual heterogeneity and the amplifying effects of environmental contagion reinforcement. The authors demonstrate that the interval of bistability within discontinuous phase transitions contracts with diminishing directedness strength

Multiple parameter estimation techniques are employed to empirically validate theoretical propositions regarding complex systems by discerning relevant free parameters from often scarce experimental data. In this tutorial, the authors provide a beginner’s guide to parameter estimation via adjoint optimization, and show its efficiency in prototypical problems across different fields of physics.

Active nematics are driven, non-equilibrium systems relevant to tissue mechanics and morphogenesis in biology, and with prospects as active metamaterials. The authors study the three-dimensional spontaneous flow transition with normal anchoring and show that it involves both chiral and rotational symmetry breaking, resulting in a fully three-dimensional flow with a twisted director field.

Quantum networks require a synergistic integration of terrestrial infrastructure employing optical fibers and wireless free-space communication technologies. In their study, the authors numerically investigate a satellite-based entanglement distribution and quantum teleportation across diverse freespace communication channels, such as diffraction or turbulence, finding that entanglement preservation endures throughout the downlink (satellite-to-ground) propagation for over 1000 km.

Silicon carbide polytypes (SiC) exhibit second-order optic nonlinearity to act as on-chip nonlinear and quantum light sources, but their integration is typically challenging. The authors demonstrate the performance of 3C-SiC --a fully integrable polytype-- as an on-chip quantum light source based on its second-order susceptibility.

The next generation of high energy particle colliders will have features that allows for highly granular detectors and current methods for particle collision reconstruction are limited. The authors explore machine learning algorithms for reconstructing events in electron-positron collisions for such future colliders obtaining a best-performing graph neural network that enhances the jet transverse momentum resolution by up to 50%, outperforming traditional methods and promising significant advancements in future collider measurements.

While numerical simulations for metalenses frequently show efficiencies above 90% at low numerical apertures, the experimental counterpart struggles to reach such efficiencies. The authors modify the model for prediction and systematically realise a set of high-precision meta-lenses with high efficiencies across the whole numerical aperture range.

Bound states in the continuum (BICs) emerge in cavities with a theoretically infinite quality factor, but the experimental measurement of such modes is challenging as they are not accessible from external perturbations. The Draft approved authors realize a fully open acoustic resonator supporting BICs, that allows for the direct measurement of the in-cavity field.