Calculus of Variations: Nature of the Functional

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Discussion Overview

The discussion revolves around the nature of the functional in the calculus of variations, specifically the form of the function \( f[y, \dot{y}, x] \) within the integral that defines the functional \( S[y] \). Participants explore the implications of different forms of \( f \) and their relevance to minimization problems.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • One participant questions why the function \( f \) must take the specific form \( f[x, y, \dot{y}] \) for minimization and whether other forms could also be minimized.
  • Another participant clarifies that \( f[x,y,\dot{y}] \) can depend on any of its variables, including cases where the dependence is zero, suggesting a broad generality in its definition.
  • A third participant introduces a more general form of the functional \( S[y] = \int_a^b f(x,y,y', \dots, y^{(n)})\,dx \) for any \( n \geq 1 \), discussing the implications for optimal solutions and boundary conditions, while noting that physical applications typically restrict \( n \) to 1.
  • A later reply acknowledges understanding of the form \( f(x, y, y') \) and expresses interest in generalizations, indicating a perception that many texts are physically motivated and may not cover the general form extensively.

Areas of Agreement / Disagreement

Participants express varying levels of understanding and interest in the generality of the functional form, with some agreeing on the limitations of higher-order derivatives in practical applications, while others seek clarification on the broader implications of different forms of \( f \). The discussion remains unresolved regarding the necessity of the specific form of \( f \) for minimization.

Contextual Notes

Participants note that the method of deriving the optimal solution involves more integrations by parts for higher-order derivatives, but the physical relevance of such generalizations is questioned. There is an acknowledgment that many texts may not address these general forms adequately.

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Let \normalsize S[y] = \int ^{a}_{b} f[y, \dot{y}, x] dx be the functional i want to minimize. Why does \normalsize f (inside the integral) take this specific form?

Would i not be able to minimize the integral, \normalsize S , if f had any other form instead of f = f[x, y, \dot{y}]?
 
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Do you understand what "f[x,y,y˙]" means? f is a function that can depend upon x, y, or the derivative of y but the "dependence" on anyone can be 0- that is, this includes f(x), with f depending on x only, f(y) with f depending on y only, or f(y') with f depending on the derivative of y only. What more generality do you want?
 
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Mathematically one can consider a functional of the form <br /> S[y] = \int_a^b f(x,y,y&#039;, \dots, y^{(n)})\,dx<br /> for any n \geq 1, where the optimal solution satisfies <br /> \sum_{k=0}^n (-1)^k \frac{d^k}{dx^k}\left( \frac{\partial f}{\partial y^{(k)}}\right) = 0,<br /> which is in principle a 2n-order ODE subject to boundary conditions on y, y&#039;, ..., y^{(n-1)} at both x = a and x = b. However in physical applications one generally has
<br /> \frac{\partial f}{\partial y^{(k)}} = 0<br /> for k \geq 2 so there is no point in going beyond n = 1. Also the method of deriving the above ODE does not involve any ideas which are not required for the derivation of the Euler-Lagrange equation for the case n = 1; it just requires more integrations by parts.
 
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Yes, i understand what f(x, y, y') means here. I was thinking about generalizations of the form that pasmith mentioned. Most of the texts are physically motivated, i guess. Probably that's why i didn't find the general form. Thanks, all! :)
 

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