Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
Ground state representations with artificial neural network methods enable high-accuracy simulations of quantum many-body systems. The authors study the performance of the transformer network architecture on this task and demonstrate its vast potential for novel findings in quantum physics.
Understanding the physics that govern the dynamics of liquid droplets and their interaction with solid surfaces is crucial for a range of industrial applications, from pesticides to solar cells. Here, the authors develop a framework based on the Young-Laplace equation, to predict the force required to detach a drop from flat and microstructured solid surfaces.
Developing cryogenic memory is a crucial undertaking in advancing superconducting logic systems. Here, the authors demonstrate the realization of a superconducting memory cell, whose state is encoded by the number of current vortices within a Josephson junction, and the readout employs microwave currents for an energy-efficient, non-destructive process.
The distinct near- and far-field directionalities of three fundamental dipoles (electric, Huygens and Janus) can be used to manipulate electromagnetic waves. The authors juxtapose the properties for these dipoles and propose a realistic active Janus source which suppresses mutual coupling by close to 1000-fold for two closely-spaced antennas.
Quantitative models for real-world epidemics are typically memory-dependent, but this presents difficulties for data collection and computation, while such difficulties do not arise in traditional Markovian models. The authors develop a framework to study the conditions under which memory-dependent processes can be modeled as Markovian frameworks.
Typically, mJ lasers generate 50 keV temperature plasma electrons. Here, the authors use mJ laser pulses to chisel a liquid droplet surface and generate an electron temperature of 1 MeV, a feat previously possible only with 100 times more powerful lasers.
High-quality measurements with good statistics, especially in a single shot, require fluxes and energies beyond the current capabilities of laserbased betatron x-ray sources. Here, the authors propose a method to enhance the flux and brightness of such sources without increasing the laser energy, paving the way for single-shot x-ray measurements in ultrafast science.
There is no universal way of optimizing the variation quantum circuits used in Noisy Intermediate-Scale Quantum (NISQ) applications. In this paper the authors introduce a new classical Bayesian optimizer, which converges much more quickly than conventional approaches, and test it for solving the Quantum Approximate Optimization Algorithm (QAOA) problem.
There has been great success in observing the spontaneous symmetry breaking (SSB) of temporal cavity solitons (TCS) in Kerr ring resonators, but similar phenomena in linear Fabry-Pérot cavities are still unexplored. The authors establish the field polarization properties for the SSB of TCS, and characterize the SSB in a model Fabry-Perot resonator.
Generating stable frequency combs with desired features is crucial for enabling applications in diverse fields, such as telecommunications, spectroscopy, and artificial intelligence. In this work, the authors demonstrated an autonomous optimization scheme based on genetic algorithms to tailor coherent microcombs produced by a microring resonator.
The precision of the signal transduction process is fundamental for biological functions, and it builds on a trade-off between minimizing the response noise while retaining high sensitivity. The authors derive a general relationship between response noise and sensitivity in signaling systems, identifying the optimal conditions to minimize the noise.
The mechanism behind the transient emergence of superconductivity upon irradiation with light in some materials is highly debated, which is in part due to the strong correlations at play. Here, the authors investigate the dynamical emergence of superconductivity in the strongly correlated, yet exactly solvable, Yukawa-Sachdev-Ye-Kitaev model and discuss differences and similarities to the relaxation dynamics of conventional superconductors.
Optical intersite spin transfer (OISTR), which is driven by an ultrafast optical excitation, was recently found in several materials, but there is some disagreement over how this phenomenon can be observed experimentally. Here, the authors investigate the mechanism of intersite spin transfer in a set of FeNi alloys and make a comparison with pure Ni, demonstrating and discussing the challenges of observing OISTR using magneto-optical measurements.
Optical techniques adopted in optical computing rely on spatial multiplexing, requiring numerous integrated elements and restricting the architecture to perform a single kernel convolution per layer. The authors demonstrate a fiber-optic computing architecture based on temporal multiplexing that performs multiple convolutions in a single layer.
In this paper the authors explain the many-body non-Hermitian skin effect (NHSE) from the angle of doublon-holon pairs in the spin-full Hatano-Nelson model. The main result is that while strong interactions suppress doublon-holon pairs in the ground state, leading to the absence of the NHSE, excited eigenstates exhibit these excitations, with doublons and holons moving toward opposite directions.
To prepare steerable assembles from a bipartite quantum state is a cumbersome task due to the optimization over all possible incompatible measurements. Here the authors leverage the power of the deep learning model to infer the hierarchy of steering measurement settings and reveal the most compact parameters to characterize the Alice-to-Bob steerability.
One-dimensional conductance is governed by complex dynamics due to increased electron-electron correlations that give rise to a range of exotic physical phenomena. Here, the authors provide a theoretical description of recent experimental results showing fractional conductance plateaus under zero magnetic field that occur in ultra-clean quasi one-dimensional nanowires.
Rare-earth elements are effective for engineering the optical properties of materials for a range of applications from lasers to quantum information technologies. Here, the authors investigate the temperature-dependent properties of Er3+ photoluminescence in Er2O3 thin films, focusing on the Stark-Stark transitions and how their temperature-dependent behaviour results from electron-phonon interactions.
Generative modeling has become a widespread method in many areas of science. This work provides a comprehensive comparison between quantum and classical generative modeling techniques, with promising prospects for quantum generative modeling towards reaching practical quantum advantage.
The magnetospheric multiscale mission (MMS) consists of four identical spacecraft used to collect data on the interaction between the Sun and Earth’s magnetic fields and study how the various interactions govern the dynamics of phenomena such as plasmas and particle movement. Here, the authors analyse MMS data on charge distribution, showing that there is a separation of charge on the dawn and dusk sectors of the inner magnetosphere.
