Undergrad Why Does the Partial Derivative of a Sum Cancel Out?

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The discussion centers on understanding why the partial derivative of a sum cancels out when differentiating with respect to a specific variable, x_i. The key point is that when differentiating the sum of squares of independent variables, only the term corresponding to x_i contributes to the derivative, while all other terms yield zero. This results in the derivative being equal to 2x_i, as the differentiation applies only to the specific term in the sum. Participants emphasize the importance of distinguishing between the summation index and the variable of differentiation. Overall, the clarification helps solidify the understanding of how partial derivatives work in the context of summation.
Ryan187
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Why the summation of the following function will be canceled out when we take the partial derivative with respect to the x_i?
Notice that x_i is the sub of (i), which is the same lower limit of the summation! Can someone, please explain in details?
118541109_630427871231244_6999212244547890627_n.jpg
 
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The ##x_i## are, I assume, independent variables. If ##i \ne j## then ##\frac{\partial x_j}{\partial x_i} = 0##.

Note that the answer should be ##2x_i##.
 
Thank you PeroK! Even if x_i is an independent variable. why the summation is canceled out? can you explain the derivative in detail, please? and you're right the answer is 2x_i not x_i
 
Ryan187 said:
Thank you PeroK! Even if x_i is an independent variable. why the summation is canceled out? can you explain the derivative in detail, please? and you're right the answer is 2x_i not x_i
The summation is not needed because most terms in the sum are zero.
 
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PS it might help is you use a different dummy variable for the definition of ##y##. Use ##j = 1## to ##n## instead of ##i##, for example.
 
@Ryan187 if you replace the free index ##i## with a concrete number, can you for instance evaluate$$\frac{\partial}{\partial x_3} \sum_{k=1}^5 ({x_k}^2)= \frac{\partial}{\partial x_3} ({x_1}^2 + {x_2}^2 + {x_3}^2 + {x_4}^2 + {x_5}^2)$$assuming the ##x_i## are independent variables?
 
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Ryan187 said:
explain
Differentiation is a linear function: ##\dfrac{\partial}{\partial x_j}(\alpha \cdot f(x)+\beta\cdot g(x))=\alpha\cdot \dfrac{\partial}{\partial x_j}f(x)+\beta\cdot \dfrac{\partial}{\partial x_j} g(x)##.

Here we only have a longer sum: ##x_1^2+x_2^2+\ldots+x_N^2##
 
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etotheipi said:
@Ryan187 if you replace the free index ##i## with a concrete number, can you for instance evaluate$$\frac{\partial}{\partial x_3} \sum_{k=1}^5 ({x_k}^2)= \frac{\partial}{\partial x_3} ({x_1}^2 + {x_2}^2 + {x_3}^2 + {x_4}^2 + {x_5}^2)$$assuming the ##x_i## are independent variables?
This is the key -- expanding the sum, and then differentiating with respect to one of the terms in the sum.
 
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So, in this case, I am kind of differentiating over one term that's why the sum will be canceled out?
 
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Ryan187 said:
So, in this case, I am kind of dif\displaystyle{}ferentiating over one term that's why the sum will be canceled out?
No. You differentiate all terms. ##\displaystyle{\dfrac{\partial}{\partial x_i}\left(\sum_{j=1}^N x_j^2\right) = \sum_{j=1}^N \dfrac{\partial}{\partial x_i} (x_j^2)}##
 
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  • #11
I'll use my example again$$\begin{align*}\frac{\partial}{\partial x_3} \sum_{k=1}^5 ({x_k}^2)&= \frac{\partial}{\partial x_3} ({x_1}^2 + {x_2}^2 + {x_3}^2 + {x_4}^2 + {x_5}^2)\\ \\&= \frac{\partial}{\partial x_3}({x_1}^2) + \frac{\partial}{\partial x_3}({x_2}^2) + \frac{\partial}{\partial x_3}({x_3}^2)+ \frac{\partial}{\partial x_3}({x_4}^2)+\frac{\partial}{\partial x_3}({x_5}^2) \\ \\

&= 0 + 0 + \frac{\partial}{\partial x_3}({x_3}^2) + 0 + 0\end{align*}$$I see I've been beaten to it by @fresh_42 :wink:
 
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etotheipi said:
I see I've been beaten to it by @fresh_42 :wink:
I have these shortcuts on the keyboard:

\displaystyle{}
\dfrac{}{}
\left(\right)
\partial

:smile:
 
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  • #13
but in this case, we derive with respect to x3 (i=3) which is one term, but the original derivative is with respect to (x_i) which is the whole i's values?!
 
  • #14
Ryan187 said:
but in this case, we derive with respect to x3 (i=3) which is one term, but the original derivative is with respect to (x_i) which is the whole i's values?!
No. ## i ## is just one specific index, an arbitrary one, but a specific one. That's why we have to distinguish this index from the summation index which runs over all. One of them matches ##j=i## whereas all others do not: ##j\neq i##. The former yields ##2x_i##, the latter yields the zeros.
 
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  • #15
Got it now! Thanks, guys, you're amazing! It is my first thread to this community!
 
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