5 Vector Field Proofs - apparently easy

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SUMMARY

The discussion revolves around the application of vector calculus, specifically the product rule in the context of scalar fields. Participants clarify that the gradient of the product of two scalar fields, represented as ##\nabla(\phi\psi)##, can be computed using the product rule, which states that ##\nabla(\phi\psi) = \phi \nabla\psi + \psi \nabla\phi##. This insight resolves the initial confusion regarding the use of the dot product and cross product in this scenario. The conversation emphasizes the importance of understanding the gradient operation in vector calculus.

PREREQUISITES
  • Understanding of vector calculus concepts, particularly gradients.
  • Familiarity with scalar fields and their derivatives.
  • Knowledge of the product rule in calculus.
  • Basic understanding of dot product and cross product operations.
NEXT STEPS
  • Study the application of the product rule in vector calculus.
  • Learn about gradients of scalar fields in more depth.
  • Explore examples of vector fields and their properties.
  • Investigate the relationship between scalar fields and vector fields in physics.
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Students and professionals in mathematics, physics, and engineering who are working with vector calculus and need to understand the manipulation of scalar fields and their gradients.

thomas49th
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Homework Statement


http://gyazo.com/94783c14f2d2d05e62e479ab33c73830


Homework Equations


I know the dot product and cross product, but even for the first one I don't see how either helps.



The Attempt at a Solution


1. the gradient of the 2 scalars multiplied together (not crossed or dotted just multiplied)
I know that the derivative of a scalar is a vector, but that won't help here

Can someone put me out of my misery?
Thomas
 
Physics news on Phys.org
The ith component of ##\nabla(\phi\psi)## is given by ##\frac{\partial}{\partial x_i} (\phi\psi)##. That derivative is the regular old derivative you know and love, so what do you get when you apply the product rule?
 

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