What is the gradient of a function f(x,y) = x^y on the complex plane?

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In summary, The conversation is about the topic of exponentiation and its properties. The speaker had initially come up with an explanation for why 0^0 is undefined when treating exponentiation as a function from R^2 to R. However, they later realized that the gradient of a function f(x,y) = x^y would be complicated and potentially deserving of extra credit on exams. The speaker then presents their solution to the problem and asks for feedback. Another participant points out a mistake in the speaker's initial explanation and suggests extending the function to C^2->C for a more relaxed gradient. Overall, the conversation highlights the complexities and pitfalls of exponentiation.
  • #1
Tac-Tics
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Earlier today, I came up with an explanation of why 0^0 is undefined in terms of properties of exponentiation. In it, I was treating exponentiation as a function from R^2 to R. Then, it occurred to me that the gradient of a function f(x,y) = x^y would be a horrible nightmare. Perhaps something very deserving of an extra credit question on some finals or something.

Anyway, I took a stab at the problem, and I wanted to double check I got the right answer.

Let grad f = (df/dx, df/dy). (The d's should be dels, but I'm lazy right now).

(grad f)(0, y) is undefined for all y <= 0.
(df/dy)(x, 0) = 0, for all x /= 0.
(df/dy)(x, y) = ln(y) y^x, for all other x and y
(df/dx)(x, 0) = 0, for all x /= 0
(df/dx)(x, y) = y x^(y-1), for y > 0, x /= 0.

It's really a mess! Exponentiation is a deadly mine field of holes and infinities! I even messed up on paper, saying when y = -1, df/dx = ln(x), which is true, but the gradient is complex at that point.

Can anyone find any mistakes I made? Does anyone have any other simple functions with crazy behavior like this? I think it's crazy at least =-)
 
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  • #2
Maybe this is a minute point but your f is not R^2 -> R, for one thing that would imply that (0,0) is in your domain which you are claiming is impossible. Also you are implying that (-1, 1/2) is in your domain but that would map to C not R.
 
  • #3
NoMoreExams said:
Maybe this is a minute point but your f is not R^2 -> R, for one thing that would imply that (0,0) is in your domain which you are claiming is impossible. Also you are implying that (-1, 1/2) is in your domain but that would map to C not R.

This is exactly why I posed to this forum... because I knew I'd miss something.

I realized that what I really meant was f was a partial function on R^2. I totally missed the negative numbers to non-integral powers bit, though. Maybe it would make more sense to extend it to C^2->C, where the gradient would be a little more relaxed.
 

What is the gradient of exponentiation?

The gradient of exponentiation refers to the rate of change of a function with respect to its input, specifically when the input is raised to a power. It represents the slope of the tangent line to the curve at a specific point.

How is the gradient of exponentiation calculated?

The gradient of exponentiation can be calculated using the power rule, which states that the derivative of a function raised to a power is equal to the power multiplied by the original function to the power minus one, multiplied by the derivative of the original function.

Why is the gradient of exponentiation important?

The gradient of exponentiation is important because it allows us to understand the behavior of a function as the input increases or decreases. It also helps us to find critical points and optimize functions.

How does the gradient of exponentiation relate to logarithms?

The gradient of exponentiation is closely related to logarithms, as they are inverse operations. The derivative of a logarithmic function is equal to the reciprocal of the original function, while the derivative of an exponential function is equal to the original function itself.

Can the gradient of exponentiation be negative?

Yes, the gradient of exponentiation can be negative. This indicates that the function is decreasing as the input increases, and the slope of the tangent line is negative. Similarly, a positive gradient indicates that the function is increasing and the slope is positive.

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