Computing normalized oscillator states for very large N (Matlab)

In summary: However, for very large values of N, the normalization term may become very small and could potentially cause numerical issues. As a workaround, one could use asymptotic expansions for the Hermite polynomials, which are available in literature. These expansions can help in accurately calculating the polynomials for large values of N, while also ensuring that they are properly normalized. Overall, using a combination of these methods can help in accurately calculating oscillator wavefunctions numerically without running into issues of exactly zero values. In summary, the most common approach for numerically calculating oscillator wavefunctions involves using recursion relations and asymptotic expansions for the Hermite polynomials to ensure proper normalization and avoid issues with exactly zero values.
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srihari83
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Hi everyone, I have a rather fundamental question about building oscillator wavefunctions numerically. I'm using Matlab. Since it's 1/√(2nn!∏)*exp(-x2/2)*Hn(x), the normalization term tends to zero rapidly. So for very large N (N>=152 in Matlab) it is zero to machine precision! Though asymptotic expansions for Hn(x) exist in literature (Abromowitz&Stegun, Polyanin&Manzhirov etc), they never say whether these Hermite polynomials are unit normalized for large N. They don't seem to be, i.e these expressions are just Hn(x). Numerically is not unlikely to be able to unit normalize unless one takes a extremely large & dense grid. But it is ok for my calculations if these functions have a ||ψN||2 <1, only if they are exactly zero, they drive certain matrices to singularity. so how do people calculate these polynomials without numbers getting exactly zero?? Any help/advice is greatly appreciated!
 
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The most common approach for calculating oscillator wavefunctions numerically is to use the recursion relations. These recurrence relations can be used to iteratively calculate the Hermite polynomials for large values of N. Once the Hermite polynomial is calculated, the wavefunction can then be obtained by multiplying the Hermite polynomial with the appropriate normalization constant. This approach will also ensure that the wavefunction is always properly normalized.
 

FAQ: Computing normalized oscillator states for very large N (Matlab)

What is the purpose of computing normalized oscillator states for very large N?

The purpose of computing normalized oscillator states for very large N is to study the behavior of a large number of coupled oscillators, which can be used to model a wide range of physical systems such as molecular dynamics, quantum mechanics, and economics. By normalizing the states, we can analyze the relative amplitudes and phases of the oscillators, which can reveal important patterns and dynamics in the system.

What is the significance of using Matlab for computing normalized oscillator states?

Matlab is a powerful and widely used software tool for scientific computing, making it an ideal choice for computing normalized oscillator states. It offers a variety of built-in functions and tools for numerical analysis, data visualization, and programming, which can greatly simplify the process of computing and analyzing large amounts of data. Additionally, Matlab has a user-friendly interface and extensive documentation, making it accessible to both experienced scientists and beginners.

How do you determine the appropriate value for N when computing normalized oscillator states?

The value of N refers to the number of oscillators in the system. The appropriate value for N depends on the specific system being modeled and the level of detail desired. In general, a larger value of N will provide a more accurate representation of the system, but it will also require more computational resources and time. It is important to strike a balance between accuracy and feasibility when choosing the value of N.

What are some challenges that may arise when computing normalized oscillator states for very large N?

One challenge that may arise is the computational cost associated with large values of N. As the number of oscillators increases, so does the amount of data to be processed and the time it takes to complete the computation. This can lead to longer processing times and potential memory limitations. Additionally, the accuracy of the results may be affected by numerical errors, which can be more pronounced when dealing with very large numbers.

Can the computed normalized oscillator states be used to predict future behavior of the system?

The computed normalized oscillator states can provide valuable insights into the behavior of the system, but they cannot be used to predict future behavior with certainty. This is because the results are based on a mathematical model, which may not fully capture the complexity and unpredictability of the real system. However, the normalized oscillator states can help identify trends and patterns that may aid in making predictions or informing future experiments.

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