Memories of amplitude and direction coexist and compete in non-Brownian suspensions
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866910183764000768 |
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| author | Padamata, Surendra Keim, Nathan C. |
| author_facet | Padamata, Surendra Keim, Nathan C. |
| contents | Steadily shearing a non-Brownian suspension forms a memory of direction, while shearing back and forth forms a memory of amplitude. Each memory is evident in the systems response to further shear, exemplifying its strong history-dependence. By combining the steady and oscillatory experiments, we show these memories are distinct but intersecting aspects of the same non-equilibrium physics: they can coexist, yet a specific amplitude suppresses directional memory and makes the system symmetric. Combined with prior results from disordered solids, our work presents a simple motif for limited memory capacity in non-equilibrium matter. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2510_11825 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Memories of amplitude and direction coexist and compete in non-Brownian suspensions Padamata, Surendra Keim, Nathan C. Soft Condensed Matter Disordered Systems and Neural Networks Statistical Mechanics Steadily shearing a non-Brownian suspension forms a memory of direction, while shearing back and forth forms a memory of amplitude. Each memory is evident in the systems response to further shear, exemplifying its strong history-dependence. By combining the steady and oscillatory experiments, we show these memories are distinct but intersecting aspects of the same non-equilibrium physics: they can coexist, yet a specific amplitude suppresses directional memory and makes the system symmetric. Combined with prior results from disordered solids, our work presents a simple motif for limited memory capacity in non-equilibrium matter. |
| title | Memories of amplitude and direction coexist and compete in non-Brownian suspensions |
| topic | Soft Condensed Matter Disordered Systems and Neural Networks Statistical Mechanics |
| url | https://arxiv.org/abs/2510.11825 |