Why can,t we multiply two distributions?

In summary, the conversation discusses the concept of multiplying two distributions, specifically the Dirac delta distribution. One person tries to use the "usual" multiplication to obtain the product of two Dirac deltas, but the other person points out that this is not a valid approach and lists two possibilities for the mistake. They also discuss the exact statement of Schwartz's theorem and the need for understanding it fully before making conclusions. Finally, they clarify the difference between the Dirac delta function and the Dirac delta distribution.
  • #1
eljose
492
0
I think Schwartz proved that 2 distributions couldn,t be multiplied..but why?..if we had 2 delta functions then their "product" is:

[tex] \delta (x-a) \delta(x-b)=f(a,b,x) [/tex]


so i have obtained the product of 2 Dirac,s delta considering that delta is a distribution is not this a contradiction to Schwartz,s proof.
 
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  • #2
Here's one heuristic as to why it is not valid. What is the integral of d(x-a)d(x-b)? It ought to be 1, possibly after scaling, but at the same time it ought to be, in some sens d(b-a) and d(a-b) 'cos deltas ought to pick out values.

You have defined a symbol that is the product of two deltas, you have not at all shown that this symbol even begins to make sense, anymore than I have shown how to divide 0 by o when I define a symbol X=0/0.

You might also want to integrate f(x)d(x-a)d(x-b) by parts as well, that might produce an intereseting result.
 
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  • #3
so i have obtained the product of 2 Dirac,s delta
No you haven't.

You haven't given all the details, so I can't tell what mistake you made. So I'll list the two most likely possibilities:

(1) You simply wrote down a formal product. You've not said what that product is, or even given a reason why it should exist!

(2) You've not multiplied distributions; you've simply convolved them.
 
  • #4
I have used the "usual" multiplication...2x3=6 and

[tex] \delta (x-a) x \delta(x-b) [/tex]

The product is:

1 if x=a and a<b or b<a, or if x=b a<b or b<a
0 if x is different from a or b
oo if x=a=b
 
  • #5
And what do you think that symbol does? Why has an extraneous x appeared in it?

So, your now object is either:

The dirac delta, probably, if a=b, and if a=/=b then it is a function that that is zero everywhere except at a and b when it is 1.

Is that consistent?

Have you tried to understand the exact statement of Schwartz's theorem?

Further you should understand the even if this is acceptable, one example that shows it can be done does not prove that it can always be done. You are being disingenuous by not stating Schwartz's result in full.
 
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  • #6
Wait, let's start from the very beginning...

Just what do you think the dirac delta distribution is? Your posts make it sound like you're talking about something different: you seem to be talking about the function [itex]\delta:\mathbb{R} \rightarrow \mathbb{R}[/itex] defined by:

[tex]
\delta(x) := \begin{cases}
0 & x \neq 0 \\
1 & x = 0
\end{cases}
[/tex]

but this function is not the dirac delta distribution.
 
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FAQ: Why can,t we multiply two distributions?

Why can't we directly multiply two distributions?

Multiplying two distributions is not as straightforward as multiplying two numbers because distributions are not just single values, but rather a range of values with different probabilities. Multiplying distributions would not result in a meaningful value.

Can we approximate distributions by multiplying their means and variances?

No, multiplying the means and variances of two distributions would not accurately represent the combined distribution. This method assumes that the two distributions are independent, which may not always be the case.

Is there a way to combine or multiply distributions?

Yes, there are mathematical operations such as convolution and product measures that can be used to combine or multiply distributions. However, these methods require specific conditions to be met and may not always result in a meaningful distribution.

Why is it important to understand why we can't multiply distributions?

Understanding why we can't multiply distributions is important because it helps us avoid making incorrect assumptions and using incorrect methods in statistical analysis. It also allows us to accurately interpret and communicate our results.

Are there any exceptions where distributions can be multiplied?

There are some special cases where distributions can be multiplied, such as when dealing with independent and identically distributed variables. However, these exceptions are limited and should not be generalized to all distributions.

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