Minimization of the square of the gradient in a volume

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SUMMARY

The discussion focuses on finding an expression for the function \(\phi(x_1, x_2, x_3)\) that minimizes the average value of the square of its gradient within a specified volume \(V\). The key equation involves the functional \(J[y]=\int_{x_1}^{x_2}f(y, y'; x)dx\), which is minimized when the condition \(\frac{\delta f}{\delta y}-\frac{d}{dx}(\frac{\delta f}{\delta y'})=0\) is satisfied. Participants emphasize the need to extend the minimization principle to multivariate functions, requiring simultaneous zeroing of first-order partial derivatives.

PREREQUISITES
  • Understanding of functionals in calculus of variations
  • Familiarity with partial derivatives and multivariable calculus
  • Knowledge of minimization principles in optimization theory
  • Basic concepts of gradient and its significance in vector calculus
NEXT STEPS
  • Study the calculus of variations to understand functional minimization
  • Learn about multivariable optimization techniques
  • Explore the application of the Euler-Lagrange equation in multiple dimensions
  • Investigate examples of minimizing gradients in physical systems
USEFUL FOR

Students and researchers in mathematics, physics, and engineering who are working on optimization problems involving multivariable functions and gradients.

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Homework Statement


Find an expression involving the function \phi(x_1, x_2, x_3) that has a minimum average value of the square of its gradient within a certain volume V of space.


Homework Equations



We are studying functionals, though so far it has only been of one variable. We're considering J[y]=\int_{x_1}^{x_2}f(y, y'; x)dx where y is a function of x. This functional is minimized when f satisfies \frac{\delta f}{\delta y}-\frac{d}{dx}(\frac{\delta f}{\delta y'})=0


The Attempt at a Solution


I have no idea how to apply this minimization principle with multiple variables.
 
Physics news on Phys.org
A multivariate function is minimized when its first-order partial derivatives with respect to all of its arguments are simultaneously zero.
 

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