Author

M. Shrimali

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Preprint Sep 2026

Predicting Phase Ordering in Chaotic Maps and Coupled Map Lattices

Coupled logistic maps exhibit collective ordering of their directional phases. As the system parameter varies, the directional phases can undergo a transition from an in-phase state to an anti-phase state, while the individual map trajectories remain chaotic. In this work, we propose a data-driven machine learning (ML)...

S. Dixit, Swati Chauhan, M. Shrimali · 0 citations

#machine learning Preprint Jun 2026

Physics-Constrained Neural Surrogate for Domain Growth Prediction in Systems with Conserved Kinetics

This work proposes a physics-constrained deep neural network as a surrogate model to learn the microstructural evolution of a binary mixture, in which conservation of the order parameter is imposed directly on the network output as a hard constraint.

Vijay Yadav, Pallvi Pandey, M. Priya et al. · 0 citations

Open access Jul 2026

Suppression of explosive synchronization in adaptive Kuramoto oscillators with higher-order interactions

Adaptive higher-order interactions among coupled dynamical systems have found widespread applications in real-world systems. Such interactions are known to drive the system into an explosive first-order transition to synchronization. We employ a generalized adaptation function of the global order parameter to modulate...

Ankit Mishra, Richita Ghosh, M. Shrimali · Europhysics letters · 0 citations