- #1
kryptyk
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Recently, I've begun to study the Geometric Algebra approach to differential geometry (Hestenes[84]) and although I do not claim to be an expert in this area (not at all!) I'm really starting to like what I see.
It seems a major problem with the differential forms approach is that it confuses directed measures with scalar measures - differential forms behave a bit like directed quantities but they also behave a bit like scalars.
For instance, take [tex]d x[/tex] and [tex]d y[/tex]. We could construct 1-forms from linear combinations:
[tex]A\, d x + B\, d y[/tex]
So in a sense, these 1-forms could be thought of as maps from vectors to scalars. On the other hand, when we use these 1-forms in integrals,
[tex]\int_S (A\, d x + B\, d y)[/tex]
they are better thought of as scalar infinitesimals. This latter view is the way differentials are usually taught to all of us at first whereas the former seems totally foreign and weird, even for many advanced students of mathematics.
GA seems to provide a much more elegant way to deal with these ideas through the use of directed measures:
[tex]d\mathbf{x} = d x\, \mathbf{e}_x[/tex]
[tex]d\mathbf{y} = d y\, \mathbf{e}_y[/tex]
where [tex]\{\mathbf{e}_x,\mathbf{e}_y\}[/tex] is a frame.
This allows us to separate the scalar infinitesimals from the frame vectors. I think (I am still sketchy on the details) we can now explicitly write the 1-form as:
[tex]\alpha (d\mathbf{u})= (A\, d\mathbf{x} + B\, d\mathbf{y})^{\dagger}\cdot d\mathbf{u}[/tex]
The integral now becomes:
[tex]\int_S (A\, d x\, \mathbf{e}_x + B\, d y\, \mathbf{e}_y)[/tex]
and indeed, [tex]d x[/tex] and [tex]d y[/tex] can be treated the same way we always did and grew to know and love.
Also, we can construct a 2-dimensional directed measure by:
[tex]d\mathbf{x}\wedge d\mathbf{y}=(d x\, \mathbf{e}_x)\wedge(d y\, \mathbf{e}_y)[/tex]
And since here, [tex]d x[/tex] and [tex]d y[/tex] are true scalar infinitesimals, they will commute with all elements of our algebra and the vectors [tex]\mathbf{e}_x[/tex] and [tex]\mathbf{e}_y[/tex] anticommute. So,
[tex](d x\, \mathbf{e}_x)\wedge(d y\, \mathbf{e}_y)=\mathbf{e}_x\wedge\mathbf{e}_y\, d x\, d y[/tex]
and
[tex]d x\, d y = d y\, d x[/tex]
[tex]\mathbf{e}_x\wedge\mathbf{e}_y= - \mathbf{e}_y\wedge\mathbf{e}_x[/tex]
The wedge product of two vectors produces a bivector - this bivector uniquely identifies a tangent plane at point [tex](x,y)[/tex] and expresses an orientation for the plane. The scalar differentials just multiply directly. This extends naturally to higher-dimensional spaces, but to complete this 2-dimensional example, let's define bivector field [tex]I[/tex]:
[tex]I=\mathbf{e}_x\wedge\mathbf{e}_y[/tex]
[tex]d\mathbf{x}\wedge d\mathbf{y}=I\, d x\, d y[/tex]
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To my novice mind, this already begins to look much nicer than the typical differential forms methods - any particular reason it is not more often used?
It seems a major problem with the differential forms approach is that it confuses directed measures with scalar measures - differential forms behave a bit like directed quantities but they also behave a bit like scalars.
For instance, take [tex]d x[/tex] and [tex]d y[/tex]. We could construct 1-forms from linear combinations:
[tex]A\, d x + B\, d y[/tex]
So in a sense, these 1-forms could be thought of as maps from vectors to scalars. On the other hand, when we use these 1-forms in integrals,
[tex]\int_S (A\, d x + B\, d y)[/tex]
they are better thought of as scalar infinitesimals. This latter view is the way differentials are usually taught to all of us at first whereas the former seems totally foreign and weird, even for many advanced students of mathematics.
GA seems to provide a much more elegant way to deal with these ideas through the use of directed measures:
[tex]d\mathbf{x} = d x\, \mathbf{e}_x[/tex]
[tex]d\mathbf{y} = d y\, \mathbf{e}_y[/tex]
where [tex]\{\mathbf{e}_x,\mathbf{e}_y\}[/tex] is a frame.
This allows us to separate the scalar infinitesimals from the frame vectors. I think (I am still sketchy on the details) we can now explicitly write the 1-form as:
[tex]\alpha (d\mathbf{u})= (A\, d\mathbf{x} + B\, d\mathbf{y})^{\dagger}\cdot d\mathbf{u}[/tex]
The integral now becomes:
[tex]\int_S (A\, d x\, \mathbf{e}_x + B\, d y\, \mathbf{e}_y)[/tex]
and indeed, [tex]d x[/tex] and [tex]d y[/tex] can be treated the same way we always did and grew to know and love.
Also, we can construct a 2-dimensional directed measure by:
[tex]d\mathbf{x}\wedge d\mathbf{y}=(d x\, \mathbf{e}_x)\wedge(d y\, \mathbf{e}_y)[/tex]
And since here, [tex]d x[/tex] and [tex]d y[/tex] are true scalar infinitesimals, they will commute with all elements of our algebra and the vectors [tex]\mathbf{e}_x[/tex] and [tex]\mathbf{e}_y[/tex] anticommute. So,
[tex](d x\, \mathbf{e}_x)\wedge(d y\, \mathbf{e}_y)=\mathbf{e}_x\wedge\mathbf{e}_y\, d x\, d y[/tex]
and
[tex]d x\, d y = d y\, d x[/tex]
[tex]\mathbf{e}_x\wedge\mathbf{e}_y= - \mathbf{e}_y\wedge\mathbf{e}_x[/tex]
The wedge product of two vectors produces a bivector - this bivector uniquely identifies a tangent plane at point [tex](x,y)[/tex] and expresses an orientation for the plane. The scalar differentials just multiply directly. This extends naturally to higher-dimensional spaces, but to complete this 2-dimensional example, let's define bivector field [tex]I[/tex]:
[tex]I=\mathbf{e}_x\wedge\mathbf{e}_y[/tex]
[tex]d\mathbf{x}\wedge d\mathbf{y}=I\, d x\, d y[/tex]
-------------
To my novice mind, this already begins to look much nicer than the typical differential forms methods - any particular reason it is not more often used?
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