About Achieving self-consistency in solving KS equation

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In summary, using the output density as the new input for the next iteration of a self-consistent algorithm can lead to wild oscillations and slow convergence. Implementing intelligent mixing schemes like conjugate-gradient or Anderson mixing can greatly improve convergence. Proper citation of papers should include journal name, volume, page number, and year.
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pcthu
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Why cannot simply taking the output density as the new input to the next?
I've read the paper by [P.H.Dederichs and R.Zeller],but more physics picture like answer I wonder to know. Thanks all
 
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Usually with self-consistent algorithms like this, the output will have moved in approximately the right direction from the input, but much too far. So if you just take the output as the input for your next iteration, your density will wildly oscillate and never converge. Even if it does converge, it may go extremely slowly, taking thousands of iterations before converging. Implementing some intelligent mixing scheme like conjugate-gradient or Anderson mixing will greatly improve the convergence.

By the way, writing the paper by [author x] is not a proper citation, we need the journal name, volume and page number of the first page (year is good too) to know what paper you are talking about.
 

Related to About Achieving self-consistency in solving KS equation

1. What is the KS equation?

The KS (Kohn-Sham) equation is a fundamental equation in Density Functional Theory (DFT), which is used to describe the electronic structure of molecules and materials. It is a set of non-linear equations that relates the electron density to the effective potential in a system.

2. Why is self-consistency important in solving the KS equation?

Self-consistency is important because it ensures that the calculated electronic density and effective potential are in agreement with each other. This is crucial for accurately predicting the properties of a system, as any discrepancies can lead to incorrect results.

3. How is self-consistency achieved in solving the KS equation?

Self-consistency is achieved through an iterative process, where the electron density is calculated from the effective potential and then used to update the potential. This process is repeated until a consistent solution is reached, where the density and potential no longer change significantly with each iteration.

4. What challenges are associated with achieving self-consistency in solving the KS equation?

One of the main challenges is determining the convergence criteria for the iterative process. If the criteria are too strict, it can lead to a long and computationally expensive calculation. On the other hand, if the criteria are too loose, it can result in an inaccurate solution. Another challenge is dealing with systems that have a complex or highly correlated electronic structure.

5. Are there any alternative methods for solving the KS equation?

Yes, there are alternative methods such as the GW approximation and time-dependent DFT. These methods can provide more accurate results for certain systems, but they also have their own limitations and challenges. Self-consistent solutions are still necessary in these methods to ensure consistency and accuracy in the calculations.

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