Thermal vestiges of avalanches in the driven random field Ising model
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arXiv
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| Format: | Preprint |
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2022
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| _version_ | 1866915064139743232 |
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| author | Yao, Liheng Jack, Robert L. |
| author_facet | Yao, Liheng Jack, Robert L. |
| contents | We investigate the non-equilibrium behavior of the $3d$ random field Ising model at finite temperature, as an external field is increased through its coercive field. We show by numerical simulations that the phenomenology of avalanches -- which are sharply defined only at zero temperature -- also persists over a significant range of finite temperatures. We analyse the main differences between the thermal and zero-temperature systems, including an excess of small avalanches in the thermal case, whose behaviour is consistent with activated dynamical scaling. We also investigate the extent to which individual avalanches at finite temperature can be traced back to parent avalanches in the athermal system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2210_16268 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Thermal vestiges of avalanches in the driven random field Ising model Yao, Liheng Jack, Robert L. Statistical Mechanics Disordered Systems and Neural Networks We investigate the non-equilibrium behavior of the $3d$ random field Ising model at finite temperature, as an external field is increased through its coercive field. We show by numerical simulations that the phenomenology of avalanches -- which are sharply defined only at zero temperature -- also persists over a significant range of finite temperatures. We analyse the main differences between the thermal and zero-temperature systems, including an excess of small avalanches in the thermal case, whose behaviour is consistent with activated dynamical scaling. We also investigate the extent to which individual avalanches at finite temperature can be traced back to parent avalanches in the athermal system. |
| title | Thermal vestiges of avalanches in the driven random field Ising model |
| topic | Statistical Mechanics Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2210.16268 |