2018/03/09 by Stefanos Papanikolaou, Papanikolaou, Stefanos
Biochemistry, Genetics and Molecular Biology · Physics and Astronomy · #Cellular Automata and Lattice Gases (nlin.CG) #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Materials Science (cond-mat.mtrl-sci) #Mesoscale and Nanoscale Physics (cond-mat.mes-hall) #Model Reduction and Neural Networks #Protein Structure and Dynamics #Statistical Mechanics (cond-mat.stat-mech) #Theoretical and Computational Physics
paper · pdf · doi:10.48550/arxiv.1803.03603
openalex publication_date 2018/03/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
When far from equilibrium, many-body systems display behavior that strongly\ndepends on the initial conditions. A characteristic such example is the\nphenomenon of plasticity of crystalline and amorphous materials that strongly\ndepends on the material history. In plasticity modeling, the history is\ncaptured by a quenched, local and disordered flow stress distribution. While it\nis this disorder that causes avalanches that are commonly observed during\nnanoscale plastic deformation, the functional form and scaling properties have\nremained elusive. In this paper, a generic formalism is developed for deriving\nlocal disorder distributions from field-response (e.g. stress/strain)\ntimeseries in models of crackling noise. We demonstrate the efficiency of the\nmethod in the hysteretic random-field Ising model and also, models of elastic\ninterface depinning that have been used to model crystalline and amorphous\nplasticity. We show that the capacity to resolve the quenched disorder\ndistribution improves with the temporal resolution and number of samples.\n