Reprogrammable, in-materia matrix-vector multiplication with floppy modes
<|reference_start|>Reprogrammable, in-materia matrix-vector multiplication with floppy modes: Matrix-vector multiplications are a fundamental building block of artificial intelligence; this essential role has motivated their implementation in a variety of physical substrates, from memristor crossbar arrays to photonic integrated circuits. Yet their realization in soft-matter intelligent systems remains elusive. Here, we experimentally demonstrate a reprogrammable elastic metamaterial that computes matrix-vector multiplications using floppy modes -- deformations with near-zero stored elastic energy. Floppy modes allow us to program complex deformations without being hindered by the natural stiffness of the material; but their practical application is challenging, as their existence depends on global topological properties of the system. To overcome this challenge, we introduce a continuously parameterized unit cell design with well-defined compatibility characteristics. This unit cell is then combined to form arbitrary matrix-vector multiplications that can even be reprogrammed after fabrication. Our results demonstrate that floppy modes can act as key enablers for embodied intelligence, smart MEMS devices and in-sensor edge computing.<|reference_end|>
@article{louvet2024reprogrammable,,
    title={Reprogrammable, in-materia matrix-vector multiplication with floppy
  modes},
    author={Theophile Louvet, Parisa Omidvar, Marc Serra-Garcia},
    journal={arXiv preprint arXiv:2409.20425},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.20425},
    primaryClass={cond-mat.soft cs.ET}
}