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We use simulations within the Migdal-Kadanoff real space renormalization approach to probe the scales relevant for rejuvenation and memory in spin glasses. One of the central questions concerns the role of temperature chaos. First we…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. Sasaki , O. C. Martin

The mitogen-activated protein kinase (MAPK) signaling cascade, an evolutionarily conserved motif present in all eukaryotic cells, is involved in coordinating critical cell-fate decisions, regulating protein synthesis, and mediating learning…

Subcellular Processes · Quantitative Biology 2024-06-11 Tanmay Mitra , Shakti N. Menon , Sitabhra Sinha

Learning and memory relies on synapses changing their strengths in response to neural activity. However there is a substantial gap between the timescales of neural electrical dynamics (1-100 ms) and organism behaviour during learning…

Neurons and Cognition · Quantitative Biology 2023-08-08 Cian O'Donnell

A generalization of the economic model of logistic growth, which takes into account the effects of memory and crises, is suggested. Memory effect means that the economic factors and parameters at any given time depend not only on their…

Economics · Quantitative Finance 2017-12-27 Valentina V. Tarasova , Vasily E. Tarasov

We have used mesoscale simulations to study the effect of immobile particles on microstructure formation during spinodal decomposition in ternary mixtures such as polymer blends. Specifically, we have explored a regime of interparticle…

Materials Science · Physics 2017-06-12 Supriyo Ghosh , Arnab Mukherjee , T. A. Abinandanan , Suryasarathi Bose

The influence of a periodic spatial forcing on the pattern formation in a generalized Cahn-Hilliard model is studied in order to describe the pattern formation in Langmuir-Blodgett transfer onto prestructured substrates. The occurring…

Pattern Formation and Solitons · Physics 2014-11-13 Markus Wilczek , Svetlana V. Gurevich

We present a phenomenological treatment of diffusion-driven martensitic phase transformations in multi-component crystalline solids that arise from non-convex free energies in mechanical and chemical variables. The treatment describes…

Chemical Physics · Physics 2016-09-29 Shiva Rudraraju , Anton Van der Ven , Krishna Garikipati

A disordered material that cannot relax to equilibrium, such as an amorphous or glassy solid, responds to deformation in a way that depends on its past. In experiments we train a 2D athermal amorphous solid with oscillatory shear, and show…

Soft Condensed Matter · Physics 2020-01-28 Nathan C. Keim , Jacob Hass , Brian Kroger , Devin Wieker

We study the late stages of spinodal decomposition in a Ginzburg-Landau mean field model with quenched disorder. Random spatial dependence in the coupling constants is introduced to model the quenched disorder. The effect of the disorder on…

Condensed Matter · Physics 2016-08-31 M. F. Gyure , S. T. Harrington , R. Strilka , H. E. Stanley

Proteins have been empirically linked to memory. If memory relates to protein structure, then each conformation would_functionally_ code only one bit, making it difficult to explain large memories. Nor is there a simple way to relate memory…

General Physics · Physics 2011-07-22 C. K. Raju

Memory effects play a key role in the dynamics of strongly correlated systems driven out of equilibrium. In the present study, we explore the nature of memory in the nonequilibrium Anderson impurity model. The Nakajima--Zwanzig--Mori…

Strongly Correlated Electrons · Physics 2013-01-28 Guy Cohen , Eran Rabani

Employing a recently proposed measure for quantum non-Markovianity, we carry out a systematic study of the size of memory effects in the spin-boson model for a large region of temperature and frequency cutoff parameters. The dynamics of the…

Quantum Physics · Physics 2012-07-26 Govinda Clos , Heinz-Peter Breuer

In Phys. Rev. Lett. 91 167206 (2003), Sun et al. study memory effects in an interacting nanoparticle system with specific temperature and field protocols. The authors claim that the observed memory effects originate from spin-glass dynamics…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. Sasaki , P. E. Jönsson , H. Takayama , P. Nordblad

The role of axonal synaptic delays in the efficacy and performance of artificial neural networks has been largely unexplored. In step-based analog-valued neural network models (ANNs), the concept is almost absent. In their spiking…

A large class of linear memory differential equations in one dimension, where the evolution depends on the whole history, can be equivalently described as a projection of a Markov process living in a higher dimensional space. Starting with…

Classical Analysis and ODEs · Mathematics 2018-04-09 Artur Stephan , Holger Stephan

We discuss the implications of finite size effects on the determination of the order of a phase transition which may occur in infinite systems. We introduce a specific model to which we apply different tests. They are aimed to characterise…

Nuclear Theory · Physics 2009-10-31 J. M. Carmona , N. Michel , J. Richert , P. Wagner

Understanding the statistical properties of recurrence intervals of extreme events is crucial to risk assessment and management of complex systems. The probability distributions and correlations of recurrence intervals for many systems have…

Statistical Finance · Quantitative Finance 2012-05-10 Hao Meng , Fei Ren , Gao-Feng Gu , Xiong Xiong , Yong-Jie Zhang , Wei-Xing Zhou , Wei Zhang

Memory systems can store vastly different amounts of information despite similar hardware constraints. Here, we show that superior spatial memory emerges from a discrete stiffening of hippocampal population geometry-a transition from…

Neurons and Cognition · Quantitative Biology 2026-05-19 Prashant C. Raju

We study domain growth dynamics when the target state is suddenly changed on all length scales. This procedure mimics the `chaos' effect postulated by the droplet theory of spin-glasses, and allows us to investigate in details its various…

Disordered Systems and Neural Networks · Physics 2009-10-31 Hajime Yoshino , Anael Lemaitre , Jean-Philippe Bouchaud

Many living and artificial systems improve their fitness or performance by adapting to changing environments or diverse training data. However, it remains unclear how such environmental variation influences adaptation, what is learned in…

Computational Physics · Physics 2026-04-09 Mengjie Zu , Carl P. Goodrich