Functional derivative of normal function

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Discussion Overview

The discussion centers on the evaluation of the functional derivative of a normal function, specifically the expression involving the derivative of a function with respect to another function. Participants explore the implications of using the delta function and its derivatives in this context, examining the rigor of the proposed evaluations and assumptions.

Discussion Character

  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant questions whether the functional derivative of ##\partial_x \psi(x)## is trivial and presents an integral representation involving the delta function.
  • Another participant suggests that the last expression does not evaluate to zero and emphasizes that it represents the derivative of the delta distribution.
  • A participant reflects on viewing the delta function as the limit of a Gaussian and questions if this leads to an error in reasoning.
  • Further clarification is provided regarding the need to use different variables for the function being differentiated and the variable of differentiation.
  • One participant mentions using 'little o' notation to informally guess the derivative and suggests a composition rule for differentiable functions.
  • Another participant reiterates that the thread is focused on functional derivatives, not on derivatives of composite functions.

Areas of Agreement / Disagreement

Participants express differing views on the evaluation of the functional derivative, particularly regarding the treatment of the delta function and its derivatives. There is no consensus on whether the expression evaluates to zero or not, and the discussion remains unresolved.

Contextual Notes

Participants highlight the importance of variable distinction in functional derivatives and the implications of using distributional interpretations. The discussion includes assumptions about boundary terms and the nature of the delta function.

ChrisPhys
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I can't convince myself whether the following functional derivative is trivial or not:

##\frac \delta {\delta \psi(x)} \big[ \partial_x \psi(x)\big],##

where ##\partial_x## is a standard derivative with respect to ##x##.

One could argue that

## \partial_x \psi(x) = \int dx' [\partial_{x'} \psi(x')] \delta (x - x') = - \int dx' \psi(x') \partial_{x'} \delta (x - x'),##

assuming there is no boundary term in integration by parts.

In this case, the functional derivative would give

##\frac \delta {\delta \psi(x)}\Big[ - \int dx' \psi(x') \partial_{x'} \delta (x - x') \Big] = - \partial_{x'} \delta (x - x')\Big|_{x'=x} = 0.##

Any thoughts? Is this rigorous?
 
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You really should use different variables for the function you are differentiating and the function you are taking the derivative with respect to ...

What makes you think that the last expression evaluates to zero? In the distribution sense it is the derivative of the delta distribution.
 
To address your last point:
Orodruin said:
What makes you think that the last expression evaluates to zero? In the distribution sense it is the derivative of the delta distribution.
I just viewed the ##\delta## function as the limit of a Gaussian, whose derivative at zero is zero. Is that an error?
 
ChrisPhys said:
To address your last point:

I just viewed the ##\delta## function as the limit of a Gaussian, whose derivative at zero is zero. Is that an error?

This then falls back on your original problem with not using different variables for the function you are differentiating and the function you are differentiating with respect to. Your question should be: "What is ##\delta (\partial_\mu \psi(x))/\delta \psi(y)##?"
The result should be a distribution which picks out the derivative of a function, i.e., the derivative (in the distributional sense) of the delta distribution.
 
@Orodruin
Thank you, that makes sense. I appreciate your help.
 
Hi
To informally guess the derivative, I use the 'little o' notation and then check the details. However, for the details. I think it is easiest to use composition rule, ie, if f,g are (Fréchet) differentiable with appropriate domains/ranges, then Df∘g(x)=Df(g(x))Dg(x).
Thanks.
 
Gracie thomas said:
Hi
To informally guess the derivative, I use the 'little o' notation and then check the details. However, for the details. I think it is easiest to use composition rule, ie, if f,g are (Fréchet) differentiable with appropriate domains/ranges, then Df∘g(x)=Df(g(x))Dg(x).
Thanks.
This thread is about functional derivatives, not derivatives of composite functions.
 

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