Bulletin of the American Physical Society
APS March Meeting 2024
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session Y44: DMFT for Classical Systems of Interacting ObjectsInvited

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Sponsoring Units: DSOFT Chair: Patrick Charbonneau, Duke University Room: Auditorium 2 
Friday, March 8, 2024 8:00AM  8:36AM 
Y44.00001: On the memory of the initial state during gradient descent dynamics in random energy landscapes Invited Speaker: Francesco Zamponi The weak ergodicity breaking hypothesis postulates that, after a quench from high to low temperature, outofequilibrium glassy systems lose memory of their initial state despite being unable to reach an equilibrium stationary state. It is a milestone of glass physics, and has provided a lot of insight on the physical properties of glass aging. Despite its undoubted usefulness as a guiding principle, its general validity remains a subject of debate. I will discuss evidence that this hypothesis does not hold in the special case of gradient descent dynamics in a specific class of random energy landscapes, corresponding to meanfield spin glass models. I will discuss how this impacts our understanding of gradient descent dynamics in more general disordered landscapes, such as glassy energy landscape or cost functions in random optimization problems. 
Friday, March 8, 2024 8:36AM  9:12AM 
Y44.00002: Regaining physical intuition on the infinitedimensional limit of driven amorphous materials Invited Speaker: Elisabeth Agoritsas Amorphous materials are ubiquitous around us: emulsions as mayonnaise, foams, sandpiles or biological tissues are all structurally disordered, and this has key implications for their mechanical, rheological and transport properties. A minimal model for amorphous materials, which allows to focus generically on the key role of this disorder, is provided by dense systems of pairwiseinteracting particles. The limit of infinite spatial dimension then plays a very special role: it uniquely provides exact analytical benchmarks, otherwise scarce, for static and dynamic features of such manybody systems. Those include for instance the critical scalings in the vicinity of the jamming transition, the stressstrain curve of glasses under quasistatic shear, or their equilibrium phase diagram depending on their temperature and packing fraction. In the last couple of years, we also derived an exact set of equations for the outofequilibrium ‘dynamical meanfield theory’ (DMFT) of these models. These pave the way to a dynamical understanding of previous static results, and more importantly, towards a characterization of the outofequilibrium properties of driven amorphous materials. 
Friday, March 8, 2024 9:12AM  9:48AM 
Y44.00003: Searching for solutions to the dynamical meanfield theory of glasses by simulating minimally structured glass formers Invited Speaker: Peter K Morse The glass problem is fundamentally one of dynamics. The recently formulated dynamical meanfield theory (DMFT) of glasses, which is exact in the infinitedimensional limit d→∞, therefore has the potential to answer several questions about jamming as well as about the nonequilibrium dynamics and rheology of glasses. As yet, however, solutions of the DMFT equations can only be obtained within a narrow range of equilibrium and lowdensity conditions. Fundamental questions about the nature of jamming and relaxation thus hinge on our understanding of low d systems, which when extrapolated to d→∞, should help distinguish meanfield physics from activated and other nonperturbative processes. Because the rich structure of lowd liquids interferes with such extrapolations, we here turn to two minimally structured glass formers whose descriptions converge to the DMFT in the infinite dimensional limit: the random Lorentz gas (RLG) and hard spheres with the MariKurchan interaction (MK). Surprisingly, extrapolation differences persist between the two models, most notably in the values of the jamming density. Resolving the origin of such discrepancies is essential to understanding the structure of the glass landscape, in particular, and the solutions of the DMFT more generally. 
Friday, March 8, 2024 9:48AM  10:24AM 
Y44.00004: Dynamical mean field theory of learning Invited Speaker: Pierfrancesco Urbani Training algorithms are key to the success of artificial and recurrent neural networks. However we know very little about them. The main example of these algorithms is stochastic gradient descent which is the workhorse of the deep learning technology. I will review how dynamical mean field theory can be used to gain some understanding of training algorithms in prototypical settings. 
Friday, March 8, 2024 10:24AM  11:00AM 
Y44.00005: Dynamical MeanField Theory: from glassy systems to large ecological communities with asymmetric interactions Invited Speaker: Ada Altieri The emergence of numerous metastable states, slow relaxation dynamics, and aging are hallmarks of glassiness. By focusing on systems with soft disordered interactions, I will show how to incorporate aging within Dynamical MeanField Theory and deduce the main quantities of interest – such as effective temperatures, correlations, and responses – in the slow regime. I will present both the case with only one slow timescale and that with an infinite hierarchy of slower and slower timescales. Remarkably, for the latter, aging dynamics is governed by a selfconsistent stochastic equation, which can be shown to precisely correspond to the ultrametric protocol proposed by Parisi for the static counterpart. 
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