کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4964481 1447807 2017 31 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Energy probability distribution zeros: A route to study phase transitions
ترجمه فارسی عنوان
صفر توزیع احتمال احتمالی: یک مسیر برای مطالعه انتقال فاز
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی تئوریک و عملی
چکیده انگلیسی
In the study of phase transitions a very few models are accessible to exact solution. In most cases analytical simplifications have to be done or some numerical techniques have to be used to get insight about their critical properties. Numerically, the most common approaches are those based on Monte Carlo simulations together with finite size scaling analysis. The use of Monte Carlo techniques requires the estimation of quantities like the specific heat or susceptibilities in a wide range of temperaturesor the construction of the density of states in large intervals of energy. Although many of these techniques are well developed they may be very time consuming when the system size becomes large enough. It should be suitable to have a method that could surpass those difficulties. In this work we present an iterative method to study the critical behavior of a system based on the partial knowledge of the complex Fisher zeros set of the partition function. The method is general with advantages over most conventional techniques since it does not need to identify any order parameter a priori. The critical temperature and exponents can be obtained with great precision even in the most unamenable cases like the two dimensional XY model. To test the method and to show how it works we applied it to some selected models where the transitions are well known: The 2D Ising, Potts and XY models and to a homopolymer system. Our choices cover systems with first order, continuous and Berezinskii-Kosterlitz-Thouless transitions as well as the homopolymer that has two pseudo-transitions. The strategy can easily be adapted to any model, classical or quantum, once we are able to build the corresponding energy probability distribution.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Physics Communications - Volume 216, July 2017, Pages 77-83
نویسندگان
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