Data and code from: Yielding in dense active matter

This dataset contains Python scripts and data files to support an investigation of the yielding transition in dense active matter in the limit of slow driving and large persistence times, across a wide range of material preparations. Under shear, materials prepared to be very low energy or ‘ultrastable’ are brittle, and well-described by elastoplastic constitutive laws. We show that, under random active forcing, however, ultrastable materials are always ductile, as shown by plotting the stress-strain curve for both active and passive systems. We develop a modified elastoplastic model that captures and explains these observations, where the key parameter is the correlation length of the input active driving field. We also observe large parameter regimes where the plastic flow is surprisingly well-predicted by the input active driving field and not highly dependent on the structural disorder, suggesting new strategies for control. These are shown by plotting the average stress drops for d..., , # Data and code from: Yielding in dense active matter

Dataset DOI: [10.5061/dryad.1ns1rn976](https://doi.org/10.5061/dryad.1ns1rn976)

## Description of the data and file structure

These Python scripts and txt/npz files can be used to regenerate the figures for our manuscript titled 'Yielding in dense active matter'. The simulations are of dense particle systems driven by random fields, and the analyses include stress/strain data and information about the plastic avalanches.

### Files and variables

#### File: active_yielding.zip

**Description:** There is an associated Python file for each figure in the connected manuscript, named by the figure number. The required data for the figures is in the /data directory, again named by figure number. They are npz files with multiple arrays. The description of the data in the arrays exactly matches the captions in the manuscript; see for details if not specified here. Variable names are:

* xis: list of correlation lengths
* k_lambda: value o..., ,