Deep learning algorithms are responsible for a technological revolution in a variety of tasks
including image recognition or Go playing. Yet, why they work is not understood. Ultimately …

Deep learning has been immensely successful at a variety of tasks, ranging from
classification to artificial intelligence. Learning corresponds to fitting training data, which is …

The field of soft matter physics has expanded rapidly over the past several decades, as
physicists realize that a broad set of materials and systems are amenable to a physical …

Note: This Perspective offers a progress report for the Simons collaboration “Cracking the
Glass Problem,” of which the authors are some of the principal investigators. While the …

The introduction of transient degrees of freedom into a system can lead to novel material
design and training protocols that guide a system into a desired metastable state. In this …

We investigate the structural, vibrational, and mechanical properties of jammed packings of
deformable particles with shape degrees of freedom in three dimensions (3D). Each 3D …

Two drastically different theories predict the marginal criticality of jamming. The full replica
symmetry breaking (fullRSB) theory predicts the power-law distributions of weak contact …

A wide range of disordered materials, from biological to geological assemblies, feature
discrete elements undergoing large shape changes. How significant geometrical variations …

Soft, amorphous solids such as tissues, foams, and emulsions are composed of deformable
particles. However, the effect of single-particle deformability on the collective behavior of soft …

Critical jamming transitions are characterized by an astonishing degree of universality.
Analytic and numerical evidence points to the existence of a large universality class that …