1 / 15

Monte Carlo Simulation of Ising Model and Phase Transition Studies By Gelman Evgenii

Monte Carlo Simulation of Ising Model and Phase Transition Studies By Gelman Evgenii. Introduction to Magnetism. Magnetic susceptibility χ : Types of magnetic materials: 1. D iamagneti c : χ <0 and constant (H elium );

kali
Download Presentation

Monte Carlo Simulation of Ising Model and Phase Transition Studies By Gelman Evgenii

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Monte Carlo Simulation of Ising Model and Phase Transition StudiesBy Gelman Evgenii

  2. Introduction to Magnetism • Magnetic susceptibilityχ: • Types of magnetic materials: • 1. Diamagnetic: χ<0 and constant (Helium); • 2. Paramagnetic: magnetic susceptibility χ>0 and χ∝1/T (Rare earth); • 3. Ferromagnetic: Iron. Below a critical temperature (Curie temperature), χ depends on magnetic field, and the M-H diagram shows a hysteresis loop; above this temperature, the material becomes paramagnetic; • 4. Anti-Ferromagnetic: Below a critical temperature, χ∝T; above this temperature, the material becomes paramagnetic. (MnO) Hysteresis loop

  3. Ising Model(2D) • A lattice model proposed to interpret ferromagnetism in materials(1925). • Basic idea: Elementary particles have an intrinsic property called “spin”. Spins carry magnetic moments. The magnetism of a bulk material is made up of the magnetic dipole moments of the atomic spins inside the material. • Ising model postulates a lattice with a spin σ(or magnetic dipole moment) on each site, defining the following Hamiltonian: • E is total energy of the system, J is the nearest spin-spin interaction energy, H is external magnetic field. σ=+1 or -1.

  4. Ising Model(2D) • Thermalproperties are defined, and computed, by the partition function, which is the normalization factor of the probability of a thermodynamic state: • Using Z(T), we can calculate the specific heat C, and magnetic susceptibilityχ

  5. Phase transitions • The abrupt sudden change in physical properties of the thermodynamic system around some critical value of thermodynamic variables(such astemperature). A particular quantity is the specific heat. • Ehrenfest classification of Phase Transition: • First-order phase transitions exhibit a discontinuity in the first derivative of the chemical potential with a thermodynamic variable. Such as solid/liquid/gas transitions. • Second-order phase transitions(also called continuous phase transition)have a discontinuity or divergence in a second derivative of the chemical potential with thermodynamic variables.

  6. Phase transitions • C and χaresecond derivative of chemical potential with T and H separately. • Onsager (1944) obtained the exact solution for 2D Ising model without external field. The solution shows that there exists second order phase transition in C andχ, because they diverge at some critical value of temperature (Tc≈2.269 in unit of (1/Boltzmann constant)). The studies can explain the ferromagnetic to paramagnetic transition of materials. • Monte Carlo simulations also reveal the phase transition properties of Ising model.

  7. Monte Carlo method and • Monte Carlo:A method using pseudorandom number to simulate the random thermal fluctuation from state to state of a system; • The probability of a particular state αfollows Boltzmann distribution: • In theory, sum over all possible states to calculate the statistical mean values of a physical quantity, weighing each state based on its Boltzmann factor; • Metropolis algorithm (importance sampling technique): 1.Flip one randomly picked spin; 2.Calculate the total energy difference between new and old spin state δE=E(new)-E(old); 3. If δE>0, the probability to accept the new state P(old->new) = exp[-δE/kT],otherwiseP(old->new) = 1.

  8. Simulation settings • Set the spin-spin interaction energy J=1, Boltzmann constant k=1, Bohr magneton • The unit of Energy is J; the unit of temperature T is

  9. Simulation interface

  10. Low temperature High magnetization High temperature Low magnetization

  11. Results: C versus T. Specific heat divergence is shown more clearly at Tc≈2.269 in this figure. Second order phase transition occurs.

  12. Results: Magnetization per spin versus Temperature (Zero external field).

  13. Results: Magnetization per spin versus External field H at T= 0.2. It shows a hysteresis loop, characteristic of ferromagnetic materials.

  14. Summary of Results • Demonstrate that second order phase transition of specific heat C and magnetic susceptibilityχoccur at Tc≈2.269, as predicted by Onsager’s exact solution. • Demonstrate the existence of spontaneous magnetization and hysteresis loop below Tc≈2.269 (J>0). These show that the system is ferromagnetic below Tc. • Combing these results, the ferromagnetic to paramagnetic phase transition of 2D Ising model is demonstrated.

  15. Plans • Write parallel algorithm (MPI or Pmatlab) • Check the performance as a function of: • Number of processors. • Lattice size. • Load equalization.

More Related