Collective dynamics and long-range order in thermal neuristor networks

This repository contains source code for reproducing the results in the paper Collective dynamics and long-range order in thermal neuristor networks. ArXiv link: arXiv:2312.12899.

Here is another relevant paper on thermal neuristors: Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

Requirements: NumPy, PyTorch >= 2.0

Usage:

python main.py computes the avalanche size distribution with specific parameters. One can change the parameters by modifying the file main.py.

python optimizer.py uses reservoir computing to classify the MNIST handwritten digit dataset. Parameters of the reservoir (which is an array of thermal neuristors) are pre-tuned, while a fully-connected output layer is trained for 20 epochs.