4-8 July 2016
Kramer Law building
Africa/Johannesburg timezone
<a href="http://events.saip.org.za/internalPage.py?pageId=10&confId=86">The Proceedings of SAIP2016</a> published on 24 December 2017

Yang-Lee and Fisher zeros in a model of adsorbing self-avoiding walks

5 Jul 2016, 10:00
20m
2A (Kramer Law building)

2A

Kramer Law building

UCT Middle Campus Cape Town
Oral Presentation Track G - Theoretical and Computational Physics Theoretical and Computational Physics (1)

Speaker

Prof. Esaias J Janse van Rensburg (Mathematics and Statistics, York University, Toronto, Ontario)

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no

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Would you like to <br> submit a short paper <br> for the Conference <br> Proceedings (Yes / No)?

Yes

Abstract content <br> &nbsp; (Max 300 words)<br><a href="http://events.saip.org.za/getFile.py/access?resId=0&materialId=0&confId=34" target="_blank">Formatting &<br>Special chars</a>

The theory of Yang-Lee zeros and the Fisher edge singularity is an accepted and useful approach in the understanding of phase transitions in statistical physics. While there are numerous studies of Yang-Lee and Fisher zeros on lattice spin systems, such as the $q$-state Potts models and lattice field theories, much less is known about these zeros and their relation to phase transitions in models of lattice clusters (such as the self-avoiding walk). In this talk numerical results on Yang-Lee and Fisher zeros in a model of an adsorbing self-avoiding walk will be presented. This is a model of polymer adsorption, and the properties of the Yang-Lee and Fisher zeros will be considered on the one hand, while the relation of the zeros to the physics of model will be considered as well. This includes, for example, the location of the critical point and scaling in the model. The numerical results are based on estimated microcanonical data, which were obtained by sampling states in the partition function of the model using the GAS algorithm.

Please indicate whether<br>this abstract may be<br>published online<br>(Yes / No)

Yes

Primary author

Prof. Esaias J Janse van Rensburg (Mathematics and Statistics, York University, Toronto, Ontario)

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