A novel theoretical framework unravels how processes in complex systems that occur at different timescales are coupled together at the functional level by sharing information.

A theoretical study of self-assembly finds that hexagon-shaped building blocks can form large structures faster than triangular or square blocks.

A new theoretical framework for plastic neural networks predicts dynamical regimes where synapses rather than neurons primarily drive the network’s behavior, leading to an alternative candidate mechanism for working memory in the brain.

An innovative approach for analyzing complex systems sets the stage for a detailed understanding of the directions and strengths of pairwise and higher-order interactions in many fields ranging from neuroscience to finance to ecology.

An analytical framework describing ecosystems in which species interactions drive large population fluctuations provides a way to address fundamental questions about this dynamical state.

Shortcuts to adiabaticity provide fast protocols for quantum state preparation. A new way to construct the auxiliary controls for guiding the system’s dynamics boosts their application to many-body systems.

Most studies of quantum Hall droplets—2D electron fluids in strong magnetic fields—focus on isotropic cases. A first-principles analysis predicts behaviors of anisotropic droplets and proposes experimental signatures.

New theoretical work establishes an analogy between systems that are dynamically frustrated, such as glasses, and thermodynamic systems whose members have conflicting goals, such as predator–prey ecosystems.

A model of epithelial cell monolayers helps reveal how the interplay between globally external shear and locally internal activity determines the emergent mechanical properties of a biological tissue as a whole.

A proposed multimode optical cavity capable of realizing a quantum spin glass offers a practicable platform for developing a comprehensive understanding of such systems.

Identification of a large class of Hamiltonians that are easy to solve on quantum computers but difficult on classical ones provides a possible path to practical quantum advantage in the simulation of quantum systems.

A theoretical study finds that the most energy-efficient way to control an active-matter system is to drive it at finite speed—unlike passive-matter systems.

A new framework for approximate evaluation, or contraction, of a tensor network greatly expands the range of problems in quantum physics and computer science that may be accurately approximated by tensor network methods.

Disease contagion is suppressed when different social groups have a large overlap in membership.

A new model reproduces both the dynamical and steady-state behavior of a group of living organisms, a first for such systems.

Neural dynamics are typically described by neural field theories derived long ago using simplified neuron models. A new framework incorporates biophysical nonlinearities into these theories.

A field-theoretic description of monitored free fermions reveals the entanglement phase diagram of one class of such systems and new universality classes of phase transitions.

A framework for describing phase transitions generalizes the usual statistical mechanics approach to include systems that are out of equilibrium, extending such study to a wide range of applications.

Nonequilibrium activity may provide a surprisingly general way to improve the ability of a system to store and retrieve memory.

A new multiscale approach allows for estimating high-dimensional probability distributions and fast sampling of many-body systems in various domains, from statistical physics to cosmology.

Models of systems in physics usually start with elementary processes. New work with a neural network shows how models can also be built by observing the system as a whole and deducing the underlying interactions.

A new approach to computing optimal nonequilibrium controls applicable to complex systems far from equilibrium, providing a tool for expanded studies into optimized nanotechnology and the evolution of biomolecular systems.

A new model of a polymer folded into loops shows how such loops leave a distinct signature in experimental data and change chromosome topology, aiding understanding of how chromosomes fold themselves into the small volume of a cell nucleus.

A connection between a subclass of quantum circuits and existing frameworks of statistical mechanics allows one to extract genuine quantum-mechanical properties from the boundary of a classical model.

The Jarzynski equality is a fundamental law connecting equilibrium processes with nonequilibrium fluctuations. Experiments, for the first time, test it in the quantum many-body regime.