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I'm just wondering about why $y_i=A_{ij}x_j$ implies $$d^Ny=|\det A|d^Nx.$$

I see that $\det A$ is the product of the eigenvalues of a diagonal matrix but still don't exactly see how. Please help.

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    $\begingroup$ The Jacobian determinant! Actually it should be absolute value $|{\rm det} A|$ $\endgroup$
    – higgsss
    Commented Sep 15, 2014 at 21:21
  • $\begingroup$ You may diagonalize $\hat{A}$: $\hat{A} = \hat{U}\hat{A}{'}\hat{U}^{T}$, where $det U = 1 , \hat{A}{'} = diag (A_{1}, ...)$. Then $det A = det U det A{'}det U^{T} = det A{'}$. $\endgroup$ Commented Sep 15, 2014 at 21:21
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    $\begingroup$ If $A$ is not a normal matrix it cannot be diagonalized that way. Instead $^T$ has to be replaced by $^{-1}$. However, in general $A$ is not diagonalizable and its determinant is not the product of its eigenvalues... $\endgroup$ Commented Sep 15, 2014 at 21:36
  • $\begingroup$ "Linear Algebra is linear". In the end, it's that simple. The multiplication is just a basis transform. Physical reality does not change by your arbitrary choice of a basis, so the (differential) equations describing reality should hold up in any basis. $\endgroup$
    – MSalters
    Commented Sep 16, 2014 at 8:39
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    $\begingroup$ This is pure math question with absolutely no physical context. $\endgroup$
    – DanielSank
    Commented Jan 4, 2015 at 22:38

2 Answers 2

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In German, this property is known as the Transformationssatz, but I do not know any appropriate translation for it.

This is, however, a special case of coordinate tranformations changing the measure by the determinant of their Jacobian, since obviously $\frac{\partial y_i}{\partial x_j} = A_{ij}$. That it is the determinant that plays a role in the transformation of the measure follows from some rather general algebraic considerations:

First off: $\mathrm{d}^Nx$, however widespread it may be, is a terrible notation (in my opinion, obscuring the underlying differential geometry). Properly, we should say that we are integrating the $n$-form $\mathrm{d}x_1 \wedge \dots \wedge \mathrm{d}x_N$ (with some prefactor $f(\vec x)$). Now, each $\mathrm{d}x_i$, as a $1$-form, i.e. a section of the cotangent bundle, transforms by the inverse of the Jacobian matrix, i.e. $\mathrm{d}x_i \mapsto \frac{\partial x_i}{\partial y_j}\mathrm{d}y_j = A^{-1}_{ij}\mathrm{d}y_j$ (summation over repeated indices implied).

Using the abstract exterior algebra definition of the determinant, it follows that

$$\mathrm{d}x_1 \wedge \dots \wedge \mathrm{d}x_N \mapsto A^{-1}_{1i_1}\mathrm{d}y_{i_1} \wedge \dots \wedge A^{-1}_{Ni_N}\mathrm{d}y_{i_N} = \det(A^{-1})\mathrm{d}y_1 \wedge \dots \wedge \mathrm{d}y_N$$

Or, returning to the initial notation,

$$\mathrm{d}^N x \mapsto \det(A^{-1})\mathrm{d}^N y$$

Using $\det(A^{-1}) = \det(A)^{-1}$ now yields the desired result.

We should remark that it is also possible to forgo just applying the definition of the determinant in abstract terms, but that we may also just use the antisymmetry of the $\wedge$ to gain some antisymmetrization by the Levi-Civita $\epsilon$, and then just compare the obtained sum with the expression for the determinant using the Levi-Civita symbol.

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  • $\begingroup$ Thank you very much. Could you please be explicit on how the $dx$'s turn into the $dy$'s in $$A^{-1}_{1i_1}\mathrm{d}x_{i_1} \wedge \dots \wedge A^{-1}_{Ni_N}\mathrm{d}x_{i_N} = \det(A^{-1})\mathrm{d}y_1 \wedge \dots \wedge \mathrm{d}y_N$$ $\endgroup$ Commented Sep 16, 2014 at 1:27
  • $\begingroup$ Perhaps "contangent bundle" and differential forms are a bit far afield for OP and typical readers of this question? $\endgroup$
    – DanielSank
    Commented Sep 16, 2014 at 2:16
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    $\begingroup$ @DanielSank: No, not for all readers. Regardless, recall answers are not just for the OP, they are for the entire community and a responder has the right to pitch at any level of physics. The fact you can get a variety of answers with different approaches for a single question is a great aspect of the physics SE. $\endgroup$
    – JamalS
    Commented Sep 16, 2014 at 6:29
  • $\begingroup$ @JamalS: Ok, just trying to suggest that a lot of folks might appreciate a more direct answer. $\endgroup$
    – DanielSank
    Commented Sep 16, 2014 at 7:19
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    $\begingroup$ @LorentzNoether: They don't, I simply can't type :P (Corrected it, they're $y$ from the start since $\mathrm{d}x_i \mapsto \frac{\partial x_i}{\partial y_j}\mathrm{d}y_j = A^{-1}_{ij}\mathrm{d}y_j$) $\endgroup$
    – ACuriousMind
    Commented Sep 16, 2014 at 12:57
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To add to the answer of @ACuriousMind, it may be remarked that the determinant of a square matrix is equal to the (signed) volume of the parallelepiped spanned by its columns.

Since this parallelepiped is exactly the image of the unit cube, the intuitive meaning of the substitution theorem (the name under which I know it) is that you can change your coordinates and still get the same value of the integral as long as you correct for the infinitesimal deformation of the unit cube at every point.

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  • $\begingroup$ In other words, the determinant is the factor by which the change of variables stretches an infinitesimal n-dimensional cube, so it tells you how to rescale the integrand when you change coordinates. The fact that the determinant is the product of the eigenvalues is roughly just another way of saying that it is the product of how much the transformation scales along each direction. $\endgroup$
    – DanielSank
    Commented Sep 16, 2014 at 2:12

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