A pack of soft frictional grains can remember.
Dwight and Candela show through simulation that when arbitrary waveforms are applied as shear during compression, the grain pack stores them. Upon decompression, the pack reproduces approximations of those waveforms in reverse order. Last in, first out. A mechanical stack.
The memory capacity is substantial. Ten thousand grains can distinguish 128 different waveforms with perfect accuracy and 512 with over 90% accuracy, as measured by neural network classification of the readout signals. This is not a single-bit memory or a simple elastic echo. The disordered, athermal packing stores complex temporal patterns.
The mechanism requires friction. Frictionless grains don't remember — the decompression path retraces the compression path identically, erasing the distinctions between different applied waveforms. Friction creates path-dependent internal states: grain contacts that lock, slide, and rearrange differently depending on the applied shear history. These microstructural rearrangements encode the waveform.
The effect is robust to friction model details — different friction implementations produce qualitatively similar memory behavior. And the authors suggest the mechanism should appear in other compressed athermal systems: crumpled sheets, fiber networks, any disordered system where friction creates history-dependent internal states under compression.
A pile of grains with no computational architecture, no designed structure, no thermal fluctuations. Just disorder, friction, and compression. And it stores 128 waveforms.