Saddles-to-minima topological crossover and glassiness in the Rubik's Cube
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909354222944256 |
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| author | Gower, Alex Hart, Oliver Castelnovo, Claudio |
| author_facet | Gower, Alex Hart, Oliver Castelnovo, Claudio |
| contents | Slow relaxation and glassiness have been the focus of extensive research attention, along with popular and technological interest, for many decades. While much understanding has been attained through mean-field and mode-coupling models, energy landscape paradigms, and real-space descriptions of dynamical heterogeneities and facilitation, a complete framework about the origins and existence of a glass transition is yet to be achieved. In this work we propose a discrete model glass-former, inspired by the famous Rubik's Cube, where these questions can be answered with surprising depth. By introducing a swap-move Monte Carlo algorithm, we are able to access thermal equilibrium states above and below the temperature of dynamical arrest. Exploiting the discreteness of the model, we probe directly the energy-resolved connectivity structure of the model, and we uncover a saddles-to-minima topological crossover underpinning the slowing down and eventual arrest of the dynamics. We demonstrate that the smooth behaviour in finite-size systems tends asymptotically to a sharp step-change in the thermodynamic limit, identifying a well-defined energy threshold where the onset of stretched exponential behaviour and the dynamical arrest come to coincide. Our results allow us to shed light on the origin of the glassy behaviour, and how this is resolved by changing connectivity upon introducing swap-moves. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_14552 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Saddles-to-minima topological crossover and glassiness in the Rubik's Cube Gower, Alex Hart, Oliver Castelnovo, Claudio Disordered Systems and Neural Networks Slow relaxation and glassiness have been the focus of extensive research attention, along with popular and technological interest, for many decades. While much understanding has been attained through mean-field and mode-coupling models, energy landscape paradigms, and real-space descriptions of dynamical heterogeneities and facilitation, a complete framework about the origins and existence of a glass transition is yet to be achieved. In this work we propose a discrete model glass-former, inspired by the famous Rubik's Cube, where these questions can be answered with surprising depth. By introducing a swap-move Monte Carlo algorithm, we are able to access thermal equilibrium states above and below the temperature of dynamical arrest. Exploiting the discreteness of the model, we probe directly the energy-resolved connectivity structure of the model, and we uncover a saddles-to-minima topological crossover underpinning the slowing down and eventual arrest of the dynamics. We demonstrate that the smooth behaviour in finite-size systems tends asymptotically to a sharp step-change in the thermodynamic limit, identifying a well-defined energy threshold where the onset of stretched exponential behaviour and the dynamical arrest come to coincide. Our results allow us to shed light on the origin of the glassy behaviour, and how this is resolved by changing connectivity upon introducing swap-moves. |
| title | Saddles-to-minima topological crossover and glassiness in the Rubik's Cube |
| topic | Disordered Systems and Neural Networks |
| url | https://arxiv.org/abs/2410.14552 |