Statistical physics articles from across Nature Portfolio

Using quantum gas microscopy, Hilbert space fragmentation and fractonic excitations are observed in a two-dimensional tilted Bose–Hubbard model.

Quantum chaos is a useful framework for quantum many-body systems, but it has been mostly applied to isolated systems. Here the authors study the interplay of chaos and dissipation in open quantum circuits, showing that chaos is robust against weak dissipation but can also assist and anomalously enhance relaxation.

Changes in muscovite caused by environmental factors can be detected in nanoindentation data with a statistical physics model for plastic deformation. The model’s simplicity implies these findings may generalize to other layered materials.

Fluctuation dynamics of an observable offers a primary signal for understanding non-equilibrium statistical mechanics. Here, the author derives a principle that the speed of an observable’s fluctuation is upper bounded by the fluctuation of an observable describing velocity, which is valid for various non-equilibrium systems from quantum many-body systems to nonlinear population dynamics.

Understanding the training dynamics of quantum neural networks is a fundamental task in quantum information science. Here, the authors show how these follow generalized Lotka-Volterra equations, revealing a transition between frozen-kernel, critical point and frozen-error dynamics. Theoretical findings, validated on IBM devices, provide insight to cost function design.

Exact analytic calculation shows that optimal control protocols for passive molecular systems often involve rapid variations and discontinuities. However, similar analytic baselines are not generally available for active-matter systems, because it is more difficult to treat active systems exactly. Here, the authors use machine learning to derive efficient control protocols for active-matter systems, and find that they are characterized by sharp features similar to those seen in passive systems.

A deep learning algorithm is presented to classify single-particle tracking trajectories into theoretical models of anomalous diffusion and detect if the trajectory is related to a model not originally found within the training dataset.

Amid growing urbanization, the 15-minute city model seeks to transform city living by ensuring that essential services are just a short walk away from city inhabitants. New research now quantitatively measures this urban ideal, revealing significant disparities in access across cities globally.

A model of voters, based on the Ising model, gives an explanation for why elections are often so close.

Multidisciplinary residential programmes and workshops help advance all the fields involved.

Historically, most renormalization group studies have been performed for equilibrium systems. Here, I give a personal reflection on the unexpected outcome of studying non-equilibrium flocking using renormalization methods.

Twenty-five years after the proposal of a jamming phase diagram, Andrea Liu and Sidney Nagel discuss how linking jammed granular materials with glasses helps us understand the physics of many systems.