What Is the General Formula for Q in Multivariable Calculus?

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SUMMARY

The discussion focuses on deriving the general formula for the matrix Q in the context of multivariable calculus, specifically when changing variables in a scalar function f dependent on multiple variables x_i. The relationship is established using the chain rule, where Q_{ij} is defined as the partial derivative of y_j with respect to x_i, expressed as Q_{ij} = \frac{\partial y_j}{\partial x_i}. This formula is confirmed to be valid for any invertible matrix M that transforms the variables.

PREREQUISITES
  • Understanding of multivariable calculus concepts, particularly the chain rule.
  • Familiarity with scalar functions and their partial derivatives.
  • Knowledge of matrix operations, specifically with invertible matrices.
  • Basic understanding of variable transformations in calculus.
NEXT STEPS
  • Study the application of the chain rule in multivariable calculus.
  • Explore the properties of invertible matrices and their role in variable transformations.
  • Learn about Jacobian matrices and their significance in multivariable functions.
  • Investigate advanced topics in multivariable calculus, such as implicit differentiation and coordinate transformations.
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Students and professionals in mathematics, particularly those studying calculus, as well as researchers and educators looking to deepen their understanding of variable transformations and the chain rule in multivariable contexts.

evilcman
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I have a scalar function f dependent on a few variables $x_i$, and I would like to change variables, so that [tex]y_i = \sum_j {M_{ij} x_j},[/tex] where M is an invertible matrix independent of the x_i-s, and compute:
[tex] \frac{\partial f}{\partial x_i} = \frac{\partial f}{\partial \left( \sum_j {M^{-1}_{ij} y_j} \right)} = \sum_j Q_{ij} \frac{\partial f}{\partial y_j}[/tex]

I suggest that the last identity is true for some matrix Q. Is there a general formula for Q?
 
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by the chain rule
[tex] \frac{\partial f}{\partial x_i} = \sum_j \frac{\partial y_j}{\partial x_i} \frac{\partial f}{\partial y_j}= \sum_j Q_{ij} \frac{\partial f}{\partial y_j}[/tex]
so
[tex]Q_{ij}=\frac{\partial y_j}{\partial x_i}[/tex]

"I suggest that the last identity is true for some matrix Q. Is there a general formula for Q?"

It is, use the chain rule to compute it. It is obvious.
 
Last edited:

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