Proof of product rule for gradients

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Discussion Overview

The discussion centers around proving the product rule for gradients, particularly in the context of the del operator applied to a dot product of vector fields. Participants express confusion regarding the nature of the output (scalar vs. vector) when applying the del operator to a dot product.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • Some participants express confusion about the application of the del operator on a dot product, noting that a dot product produces a scalar.
  • Others clarify that the del operator, being a vector operator, can yield a vector when applied to a scalar function, such as the dot product of two vector fields.
  • There is a discussion about whether the dot product of the vector fields is coordinate dependent, with some suggesting that if it is constant, then the gradient would evaluate to zero.
  • One participant emphasizes that A and B should be interpreted as vector fields, which assign vectors to points, leading to the conclusion that the dot product results in a scalar field and its gradient results in a vector field.

Areas of Agreement / Disagreement

Participants do not reach a consensus, as there are differing views on the implications of the del operator's application and the conditions under which the gradient evaluates to zero.

Contextual Notes

There are unresolved assumptions regarding the nature of the vector fields A and B, particularly their dependence on coordinates and the implications for the gradient operation.

Alvise_Souta
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Can someone please help me prove this product rule? I'm not accustomed to seeing the del operator used on a dot product. My understanding tells me that a dot product produces a scalar and I'm tempted to evaluate the left hand side as scalar 0 but the rule says it yields a vector. I'm very confused
 
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Alvise_Souta said:
My understanding tells me that a dot product produces a scalar and I'm tempted to evaluate the left hand side as scalar 0 but the rule says it yields a vector.
Del operator ##\nabla## is a vector operator, following the rule for well-defined operations involving a vector and a scalar, a del operator can be multiplied by a scalar using the usual product. ##\mathbf{A}\cdot \mathbf{B}## is a scalar, but a vector (operator) ##\nabla## comes in from the left, therefore the "product" ##\nabla (\mathbf{A}\cdot \mathbf{B})## will yield a vector.
 
So it becomes a vector because it doesn't evaluate to 0 since the del operator is used on a scalar function rather than a scalar constant?
 
Alvise_Souta said:
So it becomes a vector because it doesn't evaluate to 0 since the del operator is used on a scalar function rather than a scalar constant?
Well that's a matter of whether ##\mathbf{A}\cdot \mathbf{B}## is coordinate dependent or not. If this dot product turns out to be constant, then ##\nabla(\mathbf{A}\cdot \mathbf{B})=0##.
 
A and B are meant to be interpreted as vector fields (physics texts frequently conflate vector fields with vectors, using the word "vector" to refer to both vectors and vector fields, where the exact meaning is meant to be gleaned from context): functions that assign a unique vector to each point. The dot product of two vector fields is therefore a scalar field, as it is meant to be interpreted as the function that assigns the dot product of the two vectors assigned by A and B, respectively, at each point to each point. The gradient of a scalar field is a vector field (or covector field, depending on how formal you want to get).
 

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