Learning 1D Ising Model With Nearest Site Interaction

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Discussion Overview

The discussion centers on the 1D and 2D Ising models, focusing on Hamiltonians, transition matrices, and methods for solving these models. Participants explore the complexities of the 2D case, particularly regarding nearest neighbor interactions and the implications for transition matrices.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant presents the Hamiltonian for the 1D Ising model and transitions to the 2D case, expressing confusion about the transition matrix's dimensions and meaning.
  • Another participant suggests that the transition matrix for the 2D model would be 4x4 based on considering four spins at a site.
  • Several participants challenge the Hamiltonian presented for the 2D model, indicating it is incomplete and suggesting corrections.
  • One participant mentions the exact solution of the 2D Ising model by Onsager and provides a link to an outline, while another expresses confusion about applying this to a 2xN lattice.
  • Some participants propose that transforming the 2D Ising model to a dimer model could simplify the solution process, suggesting combinatorial techniques instead of transfer matrix methods.
  • Another participant argues that using the 2D Ising model to learn about transfer matrices may not be the best approach due to the specific complexities involved.
  • A later reply introduces the idea of the Bethe Ansatz and Yang-Baxter equation as important concepts for solving models beyond the Ising model.
  • One participant questions whether the Onsager solution can be extended to 3D, raising the issue of its feasibility.

Areas of Agreement / Disagreement

Participants express differing views on the correctness of the Hamiltonian for the 2D Ising model, with multiple corrections proposed. There is no consensus on the best approach to learning about transfer matrices or the applicability of the Onsager solution to higher dimensions.

Contextual Notes

Participants note the complexities of the 2D Ising model compared to the 1D case, highlighting missing terms in Hamiltonians and the challenges in deriving transition matrices. There are also references to specific literature that may provide additional insights.

Who May Find This Useful

Readers interested in statistical mechanics, particularly those studying the Ising model, transfer matrix techniques, or seeking to understand the complexities of 2D and 3D models may find this discussion beneficial.

KFC
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I am learning the 1D ising model (spin 1/2), without external field and considering the nearest site interaction, the hamiltonian for 1D chain is simple

H = -J\sum_i S_iS_{i+1}

Since each spin can only take either +1 or -1, we can write the transition matrix as

<br /> T = <br /> \left(<br /> \begin{matrix}<br /> e^{K} &amp; e^{-K} \\<br /> e^{-K} &amp; e^{K}<br /> \end{matrix}<br /> \right)<br />
where K=\beta J

Now I try to learn 2D case, I read some book on it but seems quite complicated, so I started with the simplest case (no external field, only nearest interaction, rectangular lattics with only 2 rows and N columns and perodic boundary condition). The hamiltonian is

H = -J\sum_{i=1}^{2}\sum_{j=1}^N S_{ij}S_{i, j+1}

right?

What I am really consfuing is how to find the transition matrix? Now each site has four nearest neighbor (of course, to avoid double counting, we only need to count two one at a time, let's say we count the one next to and below the current site) and each spin can take 2 values, so what's the dimension of the transition matrix? and what does T_{ij} means?
 
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Here is my idea. Since we have to sum over all possible sites, so consider the site (1, 1), and (2, 1) (i.e. the current site and the site below it), the energy is

-J\left[\left(S_{11}S_{12}+S_{11}S_{21}\right) + \left(S_{21}S_{22} + S_{21}S{11}\right)\right]

All other sites has the same case as this specific site (1, 1), and in this case, we only need to consider four spin S_{11}, S_{12}, S_{21}, S_{22}. Note that each of them can take two values so there are totally 16 possible values. The transition matrix would be 4x4, right?
 
Your Hamiltonian is incorrect- it's missing a term like S_ij S_i+1,j .The 2-D ising model is significantly more complicated than the 1-D. There's a brief treatment in Landau and Lifgarbagez, vol. 5 (pp 498-506) and Chaikin and Lubensky "Principles of condensed matter physics" has additional detail along with the O_n model.
 
Andy Resnick said:
Your Hamiltonian is incorrect- it's missing a term like S_ij S_i+1,j .The 2-D ising model is significantly more complicated than the 1-D. There's a brief treatment in Landau and Lifgarbagez, vol. 5 (pp 498-506) and Chaikin and Lubensky "Principles of condensed matter physics" has additional detail along with the O_n model.

Thanks. I will check
 
Andy Resnick said:
Your Hamiltonian is incorrect- it's missing a term like S_ij S_i+1,j .The 2-D ising model is significantly more complicated than the 1-D. There's a brief treatment in Landau and Lifgarbagez, vol. 5 (pp 498-506) and Chaikin and Lubensky "Principles of condensed matter physics" has additional detail along with the O_n model.

I checked it, now the Hamiltonian is modified as

H = -J\sum_{i=1}^{2}\sum_{j=1}^N S_{ij}S_{i, j+1} + S_{ij}S_{i+1,j}

So, the for site (i, j), the energy could take 16 possible values. For

S_{ij}, S_{i+1, j}, S_{i, j+1}, S_{i+1, j+1} \Longrightarrow E

++++: 4
+++-: 2
++-+: 2
++--: 0
+-++: 2
+-+-: 0
+--+:-2
+---: -2
-+++: 2
-+-+: 0
-+--: -2
--++: 0
--+-: -2
---+: -2
----: 4

So could I just use this values to setup the transition matrix?
 
The exact solution of the 2D Ising model was done by Onsager. See here for a brief outline: http://www.nyu.edu/classes/tuckerman/stat.mech/lectures/lecture_26/node2.html
 
genneth said:
The exact solution of the 2D Ising model was done by Onsager. See here for a brief outline: http://www.nyu.edu/classes/tuckerman/stat.mech/lectures/lecture_26/node2.html

Thanks. I read that before, but I found this quite confusing.

The above outline is about n x n lattices, now let's apply his result to 2 x n, we get the matrix element

<br /> T_{jk} = \exp\left[\beta J\left(\sigma_{1j}\sigma_{1k} + \sigma_{1j}\sigma_{2j} + \sigma_{2j}\sigma_{2k} + \sigma_{2j}\sigma_{1j}\right)\right]<br />

For the last term, we apply the periodic boundary condition.

My doubt is \sigma_{ij} is the eigenvalue and could be -1 or +1, so each terms in above expression couble be either +1 or -1, how come do we get a certain value for specific matrix element T_{jk} ?
 
Solvng the 2D Ising model is almost trivial by transforming it to a close packed dimer model. The dimer model can be solved using very simple combinatorial techiques, you don't need complicated transfer matrix techniques. See e.g. here:

http://arxiv.org/abs/cond-mat/0212363
 
Count Iblis said:
Solvng the 2D Ising model is almost trivial by transforming it to a close packed dimer model. The dimer model can be solved using very simple combinatorial techiques, you don't need complicated transfer matrix techniques. See e.g. here:

http://arxiv.org/abs/cond-mat/0212363

Thank you very much. I will read that later.

I am learning this problem because there is one chapter about transfer matrix in my text and this method is useful in some other place. So I want to learn it by studying 2D ising model as an example.
 
  • #10
KFC said:
Thank you very much. I will read that later.

I am learning this problem because there is one chapter about transfer matrix in my text and this method is useful in some other place. So I want to learn it by studying 2D ising model as an example.



Then you should read this book:

http://tpsrv.anu.edu.au/Members/baxter/book

You can download it free of charge. The transfer matrix technique that most textbooks explain for solving the Ising model is of no use for most other models. The Ising model is a so-called "free fermion model", the transfer matrix can then be diagonalized using a Bogoliubov transformation. This won't work for the vast class of integrable models.

So, if you want to learn about solving models, you should learn about the Bethe Ansatz, the Yang-Baxter equation etc. etc. This is explained in detail in the book by Baxter.
 
  • #11
Using the 2D Ising model to learn about the Transfer matrix is probably not the best approach. First, the Transfer Matrices are somewhat obscure (although certainly doable), and second, it doesn't even get you half way there in solving the model (i.e. you still need perform some other steps as well - steps that are quite specific to the Ising model).

But just to throw in another book, I know that this one solves the Ising model using Transfer matrices:
https://www.amazon.com/dp/9810216424/?tag=pfamazon01-20
(Chapter 5.1)
 
  • #12
ok. Thank you for all your help.
 
  • #13
Is the Onsager Solution extendable to 3D ? is it do-able in principle ?
 

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