The square lattice Ising model with quenched surface disorder
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866929483577032704 |
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| author | Cervellera, Luca Oing, Oliver Büddefeld, Jan Hucht, Alfred |
| author_facet | Cervellera, Luca Oing, Oliver Büddefeld, Jan Hucht, Alfred |
| contents | Using exact enumeration, the Casimir amplitude and the Casimir force are calculated for the square lattice Ising model with quenched surface disorder on one surface in cylinder geometry at criticality. The system shape is characterized by the aspect ratio $ρ=L/M$, where the cylinder length $L$ can take arbitrary values, while the circumference $M$ is varied from $M=4$ to $M=54$, resulting in up to $2^{54}$ numerically exact free energy calculations. A careful $M\to\infty$ extrapolation shows that quenched surface disorder is irrelevant in two dimensions, but gives rise to logarithmic corrections. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_01434 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The square lattice Ising model with quenched surface disorder Cervellera, Luca Oing, Oliver Büddefeld, Jan Hucht, Alfred Statistical Mechanics Disordered Systems and Neural Networks Mathematical Physics Using exact enumeration, the Casimir amplitude and the Casimir force are calculated for the square lattice Ising model with quenched surface disorder on one surface in cylinder geometry at criticality. The system shape is characterized by the aspect ratio $ρ=L/M$, where the cylinder length $L$ can take arbitrary values, while the circumference $M$ is varied from $M=4$ to $M=54$, resulting in up to $2^{54}$ numerically exact free energy calculations. A careful $M\to\infty$ extrapolation shows that quenched surface disorder is irrelevant in two dimensions, but gives rise to logarithmic corrections. |
| title | The square lattice Ising model with quenched surface disorder |
| topic | Statistical Mechanics Disordered Systems and Neural Networks Mathematical Physics |
| url | https://arxiv.org/abs/2409.01434 |