Uncertainty Propagation of Complex Functions

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SUMMARY

This discussion addresses the uncertainty propagation of complex functions, specifically in the context of eigenvalues of coupled oscillators. The participants explore how to handle standard error propagation when dealing with complex numbers, particularly when the function f(α, β, γ) has both real and imaginary components. A key conclusion is that while physical systems yield real values, the representation of measurements as complex numbers is valid and necessary in certain scenarios. The focus shifts to understanding the distribution of complex numbers and their associated functions.

PREREQUISITES
  • Understanding of uncertainty propagation in statistics
  • Familiarity with complex numbers and their properties
  • Knowledge of eigenvalues and eigenfunctions in physics
  • Basic principles of coupled oscillators in physical systems
NEXT STEPS
  • Research methods for uncertainty propagation in complex functions
  • Explore the statistical distribution of complex numbers
  • Study the implications of eigenvalue calculations in quantum mechanics
  • Learn about the role of complex analysis in physical systems
USEFUL FOR

Physicists, mathematicians, and engineers dealing with complex systems, particularly those involved in quantum mechanics and uncertainty analysis in physical measurements.

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Suppose I have some observables \alpha, \beta, \gamma whose central values and uncertainties \sigma_{\alpha}, \sigma_{\beta}, \sigma_{\gamma} are known.

Define a function f(\alpha, \beta, \gamma) which has both real and complex parts. How do I do standard error propagation when imaginary numbers are involved? This problem deals with the eigenvalues of a coupled oscillator. Here, some of the eigenvalue functions are complex, so I would like to know how to calculate the uncertainty on f, which is an eigenvalue. The claim is that since coupled oscillators are physical systems, their answers are real in nature. Thus, should I use Re(f) instead?
 
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Some physical systems are better represented by complex numbers than real numbers. So simply being a physical system doesn't imply the measurement is a real number.

The better question is what is the distribution of the complex number and the function.
 

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