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Obtaining the low-energy configurations of spin glasses that have rugged energy landscapes is of direct relevance to combinatorial optimization and fundamental science. Search-based heuristics have difficulty with this task due to the…

Disordered Systems and Neural Networks · Physics 2024-12-24 Adil A. Gangat , Johnnie Gray

An analysis of the dynamics is performed, of exactly solvable models for fragile and strong glasses, exploiting the partitioning of the free energy landscape in inherent structures. The results are compared with the exact solution of the…

Statistical Mechanics · Physics 2009-11-07 Luca Leuzzi , Theo M. Nieuwenhuizen

Recent experimental and theoretical studies suggest that crystallization and glass-like solidification are useful analogies for understanding cell ordering in confluent biological tissues. It remains unexplored how cellular ordering…

Cell Behavior · Quantitative Biology 2015-03-13 Margriet M. Palm , Roeland M. H. Merks

We present a simple mathematical model of glassy dynamics seen as a random walk in a directed, weighted network of minima taken as a representation of the energy landscape. Our approach gives a broader perspective to previous studies…

Statistical Mechanics · Physics 2009-08-25 Andrea Baronchelli , Alain Barrat , Romualdo Pastor-Satorras

Structural balance in social network theory starts from signed networks with active relationships (friendly or hostile) to establish a hierarchy between four different types of triadic relationships. The lack of an active link also provides…

We consider the problem of slow activation dynamics in glassy systems undergoing a random first order phase transition. Using an effective potential approach to supercooled liquids, we determine the spectrum of activation barriers for…

Disordered Systems and Neural Networks · Physics 2013-05-29 Maxim Dzero , Joerg Schmalian , Peter G. Wolynes

Lagrangian Neural Networks (LNNs) are a powerful tool for addressing physical systems, particularly those governed by conservation laws. LNNs can parametrize the Lagrangian of a system to predict trajectories with nearly conserved energy.…

Machine Learning · Computer Science 2025-07-29 Viviana Alejandra Diaz , Leandro Martin Salomone , Marcela Zuccalli

We formulate a control system model for the distributed flow of mixtures of highly heterogeneous gases through large-scale pipeline networks with time-varying injections of constituents, withdrawals, and control actions of compressors. This…

Optimization and Control · Mathematics 2023-05-23 Luke Baker , Saif R. Kazi , Rodrigo B. Platte , Anatoly Zlotnik

Bacterial assemblies exhibit rich collective behaviors that control their biological functions, making them a relevant object of study from an active matter physics perspective. Dense bacterial suspensions self-organize into distinct…

Soft Condensed Matter · Physics 2025-04-08 Martin Maliet , Nicolas Fix-Boulier , Ludovic Berthier , Maxime Deforet

We study a lattice model of attractive colloids. It is exactly solvable on sparse random graphs. As the pressure and temperature are varied it reproduces many characteristic phenomena of liquids, glasses and colloidal systems such as ideal…

Soft Condensed Matter · Physics 2008-10-15 Florent Krzakala , Marco Tarzia , Lenka Zdeborová

We present a realistic model of the fragile glass former orthoterphenyl and the results of extensive molecular dynamics simulations in which we investigated its basic static and dynamic properties. In this model the internal molecular…

Disordered Systems and Neural Networks · Physics 2009-10-31 S. Mossa , R. Di Leonardo , G. Ruocco , M. Sampoli

By means of an effective potential associated to a constrained equilibrium measure and apt to study frozen systems, we investigate glassy freezing in simple liquids in the hypernetted chain (HNC) approximation. Differently from other…

Statistical Mechanics · Physics 2009-10-31 Miguel Cardenas , Silvio Franz , Giorgio Parisi

A novel approach is presented for the solution of instantaneous chemical equilibrium problems. The chemical equilibrium can be considered, due to its intrinsically local character, as a mapping of the three-dimensional parameter space…

Astrophysics · Physics 2009-11-11 A. Asensio Ramos , H. Socas-Navarro

Information geometry is based on classical Legendre duality but allows to incorporate additional structure such as algebraic constraints and Bregman divergence functions. It is naturally suited, and has been successfully used, to describe…

Molecular Networks · Quantitative Biology 2025-03-26 Dimitri Loutchko , Yuki Sughiyama , Tetsuya J. Kobayashi

We have used molecular dynamics to simulate an amorphous glassy polymer with long chains to study deformation mechanism of crazing and associated void statistics. The Van der Waals interactions and the entanglements between chains…

We constructs a new network by superposition of hexahedron , which are scale-free, highly sparse,disassortative ,and maximal planar graphs. The network degree distribution, agglomeration coefficient and degree of correlation are computed…

Physics and Society · Physics 2021-04-12 Li Haijun , Lu Qingping

Optimizing paths on networks is crucial for many applications, from subway traffic to Internet communication. As global path optimization that takes account of all path-choices simultaneously is computationally hard, most existing routing…

Physics and Society · Physics 2013-09-05 Chi Ho Yeung , David Saad , K. Y. Michael Wong

We report an extensive and systematic investigation of the multi-point and multi-time correlation functions to reveal the spatio-temporal structures of dynamic heterogeneities in glass-forming liquids. Molecular dynamics simulations are…

Soft Condensed Matter · Physics 2013-01-04 Kang Kim , Shinji Saito

The random first order transition theory of the dynamics of supercooled liquids is extended to treat aging phenomena in nonequilibrium structural glasses. A reformulation of the idea of ``entropic droplets'' in terms of libraries of local…

Soft Condensed Matter · Physics 2009-11-10 Vassiliy Lubchenko , Peter G. Wolynes

A multitask deep neural network model was trained on more than 218k different glass compositions. This model, called GlassNet, can predict 85 different properties (such as optical, electrical, dielectric, mechanical, and thermal properties,…

Soft Condensed Matter · Physics 2023-11-21 Daniel R. Cassar