\documentclass[../ising_model.tex]{subfiles} \begin{document} \section{Conclusion}\label{sec:conclusion} We studied the ferromagnetic behavior of the Ising model, and observed a phase transition at temperatures close to the critical temperature. We used a Markov chain Monte Carlo sampling method to generate spin configurations, while utilizing parallel programming techniques. When increasing number of processes, and number of threads we observed a speed-up in runtime. We initialized the lattices using both ordered and unordered spin configuration, and started sampling after the system reached an equilibrium. The number of Monte Carlo cycles necessary to reach a system equilibrium, referred to as burn-in time, was estimated to be $5000$ cycles. We found that excluding the samples generated during the burn-in time, improves the estimated expectation value of energy and magnetization, in addition to the heat capacity and susceptibility, when samples are sparse. However, when we increase number of samples, excluding the burn-in samples does not affect the estimated values. Continuing, we used the generated samples to compute energy per spin $\langle \epsilon \rangle$, magnetization per spin $\langle |m| \rangle$, heat capacity $C_{V}$, and $\chi$. In addition, we estimated the probability distribution for temperatures $T_{1} = 1.0 J / k_{B}$, and $T_{2} = 2.4 J / k_{B}$. We found that for $T_{1}$ the expected mean energy per spin is $\langle \epsilon \rangle \approx -1.9969 J$, with a variance $\text{Var} (\epsilon) = 0.0001$. And for $T_{2}$, the mean energy per spin is $\langle \epsilon \rangle \approx -1.2370 J$, with a variance $\text{Var} (\epsilon) = 0.0203$. We estimated the expected energy and magnetization per spin, in addition to the heat capacity and susceptibility for lattices of size $L = {20, 40, 60, 80, 100}$. We observed a phase transition in the temperature range $T \in [2.1, 2.4] J / k_{B}$. Using the values from the finite lattices, we approximated the critical temperature of a lattice of infinite size. Using linear regression, we numerically estimated $T_{c}(L = \infty) \approx 2.2695 J/k_{B}$ which is close to the analytical solution $T_{C}(L = \infty) \approx 2.269 J/k_{B}$ Lars Onsager found in 1944. \end{document}