Generalizing: Curl of a Function

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The discussion focuses on the challenge of generalizing the curl of a vector field beyond three dimensions. While the gradient and divergence can be extended to higher dimensions, the curl, defined as ∇×F, is limited to three components. The key to generalization lies in using the "alternating tensor" represented by ε, which helps define operations in n dimensions. For n dimensions, the curl can be expressed as the Hodge dual of the exterior derivative of the vector field, resulting in a higher-rank tensor for dimensions greater than three. This indicates a need for deeper understanding of advanced mathematical concepts in vector calculus.
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Hello. I have tried to search all day for the answer to my question but could not find anything.

Is there a way to generalize the curl of a vector field to dimensions greater than three? It seems pretty straightforward to find the gradient and divergence of higher dimensional vector fields, but my calculus book only offers the definition: curl F := ∇×F, which appears to only work if F has three components. Or am getting something wrong?

I am also only in my first real analysis course, so I have not come across this kind of topic in that class yet.
 
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Not easily. The problem is that the best way to generalize the cross product itself is to use the "alternating tensor". That is the operator represented by \epsilon_{i_1i_2\cdot\cdot\cdot i_n} equal to 1 if i_1i_2\cdot\cdot\cdot i_n is an even permutation of 1 2 3 \cdot\cdot\cdot\ n, -1 if it s an odd permutation, and 0 if neither of those is true.
For example, when n= 3, \epsilon_{ijk} has 27 entries. \epsilon_{123}= \epsilon_{231}= \epsilon_{312}= 1, \epsilon_{132}= \epsilon_{213}= \epsilon_{321}= -1, and the other 21 entries are all 0.

With that w_i= \sum_{j=1}^3\sum_{k=1}^3\epsilon_{ijk}u_jv_k gives w_1= \epsilon_{123}u_{2}v_{3}+ \epsilon_{132}u_3v_2= u_2v_3- u_3v_2
w_2= \epsilon_{213}u_1v_3+ \epsilon_{231}u_3v_2= -u_2v_3+ u_3v_2
w_3= \epsilon_{312}u_1v_2+ \epsilon_{321}u_2v_1= u_1v_2- u_2v_3
precisely the cross product.


But, in n dimensions, \epsilon has n indices. In order to get a vector result, we would have to multiply n-1 vectors, not just two.
 
In a general space whose dimension is not necessarily three, the generalization of curl is a Hodge dual of an exterior derivative of the vector field. The vector field is a 1-form, its exterior derivative is a 2-form, and its Hodge dual is a (n-2)-form. Which is a scalar (a number) for n=2, a vector for n=3, a higher-rank tensor for n>=4.
 
Thank you for the help! Looks like I have a few things to learn about the topic.
 
There are probably loads of proofs of this online, but I do not want to cheat. Here is my attempt: Convexity says that $$f(\lambda a + (1-\lambda)b) \leq \lambda f(a) + (1-\lambda) f(b)$$ $$f(b + \lambda(a-b)) \leq f(b) + \lambda (f(a) - f(b))$$ We know from the intermediate value theorem that there exists a ##c \in (b,a)## such that $$\frac{f(a) - f(b)}{a-b} = f'(c).$$ Hence $$f(b + \lambda(a-b)) \leq f(b) + \lambda (a - b) f'(c))$$ $$\frac{f(b + \lambda(a-b)) - f(b)}{\lambda(a-b)}...

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