How Do We Find the Parametrization σ?

In summary: We can therefore find $\sigma$ by solving for $\sigma$: \oint\int_\Pi (\nabla\times f)d\Pi=\oint\int_\Pi (0)d\sigma. So, the equation is $\sigma=\oint\int_\Pi (0)d\sigma$.
  • #1
mathmari
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Hey! :eek:

I want to show that $\iint_{\Sigma}(\nabla\times f)\cdot d\Sigma=0$ for the function $f(x,y,z)=(1,1,1)\times g(x,y,z)$ when $\Sigma$ is the surfcae that is defined by the relations $x^2+y^2+z^2=1$ and $x+y+z\geq 1$.
I have done the following:

Let $g(x,y,z)=(g_1, g_2, g_3)$. Then $f(x,y,z)=(1,1,1)\times (g_1, g_2, g_3)=(g_3-g_2, g_1-g_3, g_2-g_1)$.

From Stokes theorem we have that $$ \iint_{\Sigma}(\nabla\times f)\cdot d\Sigma=\oint_{\sigma}f\cdot d\sigma$$

So, we have to find the boundary of the surface, $\sigma$. For that do we have to set equal the relations $x^2+y^2+z^2=1$ and $x+y+z= 1$. I yes, we get the following:

$$x^2+y^2+z^2=x+y+z\\ \Rightarrow x^2-x+y^2-y+z^2-z=0 \\ \Rightarrow x^2-x+\frac{1}{4}+y^2-y+\frac{1}{4}+z^2-z+\frac{1}{4}=\frac{3}{4} \\ \Rightarrow \left (x-\frac{1}{2}\right )^2+\left (y-\frac{1}{2}\right )^2+\left (z-\frac{1}{2}\right )^2=\frac{3}{4} \\ \Rightarrow \frac{4}{3}\left (x-\frac{1}{2}\right )^2+\frac{4}{3}\left (y-\frac{1}{2}\right )^2+\frac{4}{3}\left (z-\frac{1}{2}\right )^2=1 \\ \Rightarrow \left (\frac{2}{\sqrt{3}}x-\frac{1}{\sqrt{3}}\right )^2+\left (\frac{2}{\sqrt{3}}y-\frac{1}{\sqrt{3}}\right )^2+\left (\frac{2}{\sqrt{3}}z-\frac{1}{\sqrt{3}}\right )^2=1 $$

How can we continue? How can we get $\sigma$ ?
 
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  • #2
mathmari said:
Hey! :eek:

I want to show that $\iint_{\Sigma}(\nabla\times f)\cdot d\Sigma=0$ for the function $f(x,y,z)=(1,1,1)\times g(x,y,z)$ when $\Sigma$ is the surfcae that is defined by the relations $x^2+y^2+z^2=1$ and $x+y+z\geq 1$.

Doesn't that depend on exactly what the function, g, is?
 
  • #3
HallsofIvy said:
Doesn't that depend on exactly what the function, g, is?

We don't have any information about g. So, we cannot show that without an expression for g? (Wondering)
 
  • #4
well, I expect that the key point here is that the vector (1, 1, 1) is perpendicular to the plane x+ y+ z= 1. And notice that, of course, the spherical surface and the plane have the same boundary. By Stokes theorem, as you say, \(\displaystyle \int\int_\Sigma (\nabla \times f)d\Sigma= \oint f\cdot d\sigma\). Applying exactly the same theorem to the plane, and writing \(\displaystyle \Pi\) for the region of the plane bounded by the circle of intersection, we have \(\displaystyle \int\int_\Pi (\nabla \times f)d\Pi= \oint f\cdot (\nabla\times f) d\sigma\).

Together, \(\displaystyle \int\int_\Sigma (\nabla \times f)d\Sigma= \int\int_\Pi (\nabla\times f)d\Pi\).
 

FAQ: How Do We Find the Parametrization σ?

What does the parametrization σ represent?

The parametrization σ represents the standard deviation of a statistical distribution. It is a measure of how spread out the data is from the mean.

How is the parametrization σ calculated?

The parametrization σ is calculated by taking the square root of the variance of the data. It can also be calculated using the formula σ = √(∑(xi - x̄)^2 / n), where xi is each individual data point, x̄ is the mean, and n is the total number of data points.

What is the relationship between the parametrization σ and the mean?

The parametrization σ and the mean are both measures of central tendency in a data set. However, while the mean represents the average value, the parametrization σ represents the spread of the data.

How does the parametrization σ affect the shape of a distribution?

The parametrization σ can affect the shape of a distribution by determining how spread out the data is. A larger σ value will result in a wider distribution, while a smaller σ value will result in a narrower distribution.

Can the parametrization σ be negative?

No, the parametrization σ cannot be negative. It represents a measure of variability, and cannot have a negative value. If a negative value is obtained, it is likely due to an error in calculation.

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