Diagonalizing Hamiltonian for Multi-Qubit Ising Model

In summary, the conversation discusses the Ising Model, specifically the evolution of a multi-qubit system with an initial and final Hamiltonian. The Hamiltonian is given by three equations, with the second one stating that in order for Hf to be diagonalized, i must be greater than j in the second summation. The values for hi and Jij are chosen randomly. The conversation then discusses the possibility of diagonalizing the Hamiltonian and finding the lowest states for fixed t, with the suggestion of using the exponential function. The conversation concludes by recommending a book on numerical mathematics for more advanced methods.
  • #1
mehdi86
4
0
Hello,I am doing a research related to Ising Model
in m research, evolution of a multi-qubit Ising system with the initial and final
Hamiltonian is given by:
(1) Hi=(-1/2)[itex]\sum\sigma^{(i)}_{x}[/itex]
(2) Hf=(-1/2)[itex]\sumhi\sigma^{(i)}_{z}[/itex]+(1/2)[itex]\sumJ_{ij}\sigma^{(i)}_{z}\sigma^{(j)}_{z}[/itex]
(3) Hs(t)=(1-s(t))Hi+s(t)Hf
and in Hf must i>j in the second summation, and hi and Jij from{-1,0,1}. please help me how can I diagonalize the Hamiltonian (3) with (1) and (2) with random instances for 20 qubits by randomly choosing hi and Jij. mostly I have problem with multiplying two sigmas in Hf.
Thanks a lot.
 
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  • #2
Maybe you should first repair the display of your formulas so that they can be read by everybody in the forum.
I don't think it is a good idea to diagonalize the hamiltonian (which is a matrix of size 2^20 times 2^20 or 10^6 times 10^6) if you are only interested in the time evolution of selected states.
Your initial hamiltonian is diagonal (or practically so, if you interchange the roles of sigma_x and sigma_z) and it should be easy to follow the time evolution of a single state.
 
  • #3
excuse me,our Hamiltonian is:
Hi=(-1/2)[itex]\sum\sigma^{(i)}_{x}[/itex]
Hf=(-1/2)[itex]\sum\sigma^{(i)}_{z}[/itex]hi
+(1/2)[itex]\sum\sigma^{(i)}_{z}*sigma^{(j)}_{z}[/itex]Jij
Moreover if we want diagonalize hs(t) for two first states(i.e. 0 &1 states), what shall we do?
thank you very much.
 
Last edited:
  • #4
Finding the lowest states for fixed t is quite easy: It is easy to see that applying [itex] \exp(-\tau H) [/itex] on any starting function which is not orthogonal to the ground state. will converge to the eigenstate corresponding to the lowest eigenvalue in the limit tau to infinity. For small tau, you can write
[itex]\exp(-\tau H)\approx (1-\tau H)[/itex]. So you just have to apply the last expression with a small value of tau (smaller than the norm of H) repeatedly to some starting function. Eventually you have to rescale the function every now an then to avoid it to become to small. Once you have found the ground state, you can start again from a state orthogonal to it and repeat the procedure to find the first excited state. If you want to find more states, there exist more elaborate methods. Consider a book on numerical mathematics, e.g. "Numerical recipes" is a good starting point.
 

Related to Diagonalizing Hamiltonian for Multi-Qubit Ising Model

1. What is the Ising Model?

The Ising Model is a mathematical model used in statistical mechanics to study the behavior of systems made up of interacting particles. It was first proposed by physicist Ernst Ising in 1925 and has since been applied to various fields including magnetism, phase transitions, and social dynamics.

2. What are the key concepts of the Ising Model?

The Ising Model is based on the concepts of spins and interactions. Spins represent the orientation of particles in a system, while interactions represent the forces between these particles. In the simplest form of the model, each spin can only have two possible states (up or down) and interactions are limited to nearest neighbors.

3. What are some applications of the Ising Model?

The Ising Model has been used to study a wide range of phenomena in physics, chemistry, biology, and social sciences. Some examples include studying phase transitions in materials, predicting the behavior of magnetic materials, modeling the spread of diseases, and understanding opinion formation in society.

4. What is the significance of the critical temperature in the Ising Model?

The critical temperature is a key parameter in the Ising Model that represents the temperature at which a phase transition occurs. Below the critical temperature, the system is in an ordered state where all spins are aligned, while above the critical temperature, the system is in a disordered state where spins are randomly oriented. The critical temperature can provide insights into the behavior of materials and systems.

5. What are some limitations of the Ising Model?

While the Ising Model has been successful in explaining many phenomena, it also has its limitations. For example, the model only considers interactions between nearest neighbors and does not account for long-range interactions. It also assumes a simplified system where all particles are identical and have the same energy. Extensions of the Ising Model have been developed to address some of these limitations.

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