Publications by Matthieu Wyart

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Sliding at a quasi-statically loaded frictional interface can occur via macroscopic slip events, which nucleate locally before propagating as rupture fronts very similar to fracture. We introduce a microscopic model of a frictional interface that includes ...

Disordered systems under applied loading display slow creep flows at finite temperature. Renormalization group arguments predicted that creep proceeds via thermal avalanches of activated events. Recently, thermal avalanches were argued to control the dynam ...

We present experimental results on dense corn-starch suspensions as examples of non-Brownian, nearly hard particles that undergo continuous and discontinuous shear thickening (DST) at intermediate and high densities, respectively. Our results offer strong ...

Supervised deep learning involves the training of neural networks with a large number N of parameters. For large enough N, in the so-called over-parametrized regime, one can essentially fit the training data points. Sparsitybased arguments would suggest th ...

We use numerical simulations to study the effect of particle friction on suspension flows of non-Brownian hard particles. By systematically varying the microscopic friction coefficient mu(p) and the viscous number J, we build a phase diagram that identifie ...

In amorphous materials, groups of particles can rearrange locally into a new stable configuration. Such elementary excitations are key as they determine the response to external stresses, as well as to thermal and quantum fluctuations. Yet, understanding w ...

Understanding the structure of real data is paramount in advancing modern deep-learning methodologies. Natural data such as images are believed to be composed of features organized in a hierarchical and combinatorial manner, which neural networks capture d ...

We study how neural networks compress uninformative input space in models where data lie in d dimensions, but the labels of which only vary within a linear manifold of dimension d(parallel to) < d. We show that for a one-hidden-layer network initialized wi ...

Several theories of the glass transition propose that the structural relaxation time tau(alpha) is controlled by a growing static length scale. that is determined by the free energy landscape but not by the local dynamic rules governing its exploration. We ...

Failure and flow of amorphous materials are central to various phenomena including earthquakes and landslides. There is accumulating evidence that the yielding transition between a flowing and an arrested phase is a critical phenomenon, but the associated ...

A dry frictional interface loaded in shear often displays stick–slip. The amplitude of this cycle depends on the probability that a microscopic event nucleates a rupture and on the rate at which microscopic events are triggered. The latter is determined by ...

We report the first measurements of the effect of pressure on vibrational modes in emulsions, which serve as a model for soft frictionless spheres at zero temperature. As a function of the applied pressure, we find that the density of states D(omega) exhib ...

Deep learning algorithms demonstrate a surprising ability to learn high-dimensional tasks from limited examples. This is commonly attributed to the depth of neural networks, enabling them to build a hierarchy of abstract, low-dimensional data representatio ...

The jamming transition is accompanied by a rich phenomenology such as hysteresis or nonlocal effects that is still not well understood. Here, we experimentally investigate a model frictionless granular layer flowing down an inclined plane as a way to disen ...

We study nonlocal effects associated with particle collisions in dense suspension flows, in the context of the Affine Solvent Model, known to capture various aspects of the jamming transition. We show that an individual collision changes significantly the ...

We introduce a new model to study the effect of surface roughness on the jamming transition. By performing numerical simulations, we show that for a smooth surface, the jamming transition density and the contact number at the transition point both increase ...

Modern deep networks are trained with stochastic gradient descent (SGD) whose key hyperparameters are the number of data considered at each step or batch size B, and the step size or learning rate n. For small B and large n, SGD corresponds to a stochastic ...

Amorphous solids yield at a critical value Sigma(c) of the imposed stress Sigma through a dynamical phase transition. While sharp in athermal systems, the presence of thermal fluctuations leads to the rounding of the transition and thermally activated flow ...

Flows of hard granular materials depend strongly on the interparticle friction coefficient mu(p) and on the inertial number I, which characterizes proximity to the jamming transition where flow stops. Guided by numerical simulations, we derive the phase di ...

Matthieu Wyart

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How collective asperity detachments nucleate slip at frictional interfaces

Dynamical heterogeneities of thermal creep in pinned interfaces

Unsteady flow and particle migration in dense, non-Brownian suspensions

Scaling description of generalization with number of parameters in deep learning

Effect of friction on dense suspension flows of hard particles

Mean-field description for the architecture of low-energy excitations in glasses

A phase transition in diffusion models reveals the hierarchical nature of data

Geometric compression of invariant manifolds in neural networks

Does a Growing Static Length Scale Control the Glass Transition?

Mean-Field Description of Plastic Flow in Amorphous Solids

Armouring of a Frictional Interface by Mechanical Noise

Evidence for Marginal Stability in Emulsions

How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model

Nonlocal Effects Reflect the Jamming Criticality in Frictionless Granular Flows Down Inclines

Effect of particle collisions in dense suspension flows

Jamming with Tunable Roughness

On the different regimes of stochastic gradient descent

Thermally activated flow in models of amorphous solids

On variational arguments for vibrational modes near jamming (vol 114, 26003, 2016)

Phase diagram for inertial granular flows