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I've started studying differential geometry by myself and I ran into dual spaces in a section on 1-forms. I'm not very well versed in linear algebra so any help is much appreciated.

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    It is in your best interest to run an intensive refresher course in linear algebra before starting to learn differential geometry. Diff geo has some pretty heavy linear algebra, especially when you start working with tensors (i.e, exterior, symmetric, and tensor products, etc.). Dual spaces, quotient spaces, etc are also important concepts. BTW, how is this a soft question? It seems rather well-posed. – shalop Oct 29 '15 at 05:04
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    I was hoping to get some intuition behind a dual space rather than just the mathematical definition. I don't think I will be delving that deep into differential geometry just yet. Thank you for your suggestion. – Shojul000 Oct 29 '15 at 05:07
  • If "vector" means "column vector", then "dual vector" means "row vector". And/or vice-versa. E.g., we'd not consider adding a row vector to a column vector, so there's a "type" distinction, and $r\cdot c$ with row-vector $r$ and column vector $c$ is "evaluation", while $c\cdot r$ is a matrix, not a scalar, and is identifiable with the tensor product. Linear algebra: done. Next? :) (Srsly, I'm not a fan of needless coordinatizing, but sometimes it does cut Gordian knots...) – paul garrett Oct 29 '15 at 22:00

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In the context of vector spaces, the dual space is a space of linear "measurements". When a dual vector $f$ acts on a vector $v$, the scalar output $f(v)$ provides information about $v$; in particular, it gives you something about a coordinate of $v$ in some direction. A vector $v$ can be reconstructed from knowing all the values $f(v)$ for $f$ in the dual space.

As a rough example from engineering, consider vector space $V$ the space of continuous, periodic functions on $[0, 2\pi]$. Then there are certain dual vectors $f_k$ which returns how much of the function $v(x) \in V$ contains a frequency $k$. So if $v(x)$ was a sound wave, then $f_k(v)$ tells you whether the musical note of frequency $k$ is in the sound. Then the entire sound wave $v(x)$ can be reconstructed from knowing $f_k(v)$ for all $k$, since that would tell you all the notes in the sound.

And of course, $f_k(v)$ is going to be the $k$th Fourier coefficient of $v$.

Christopher A. Wong
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    +1 The best explanation i have read so far... Thank you. Could you consider explaining what the double dual would then be? Or can you provide me with a good reference for the double dual? – Antoni Parellada Nov 25 '16 at 17:19
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Roughly, a 1-form $f: V \rightarrow K$, is a function that eats a vector and spits out a scalar, and is also linear:

$$f(\alpha \textbf{v} + \beta \textbf{w}) = \alpha f(\textbf{v}) + \beta f(\textbf{w})$$

For a quick introduction, you can check out the wikipedia page. I particularly like the visualization they have of envisioning 1-forms in finite dimensions as stacks of oriented $(n-1)$-dimensional hyperplanes. When a vector is paired with a 1-form, the resulting scalar is simply the number of planes that the vector "pierces". Larger 1-forms are represented by denser stacks, and produce larger scalars for the same vector.

You can show that the collection of all 1-forms over a vector space $V$ forms another vector space (we can meaningfully add 1-forms, multiply them by scalars, write them as linear combinations of other 1-forms in a basis [proof], etc.). This new vector space of 1-forms is called the dual space, $V^*$.


One particularly interesting fact about 1-forms is that they obey covariant transformation laws under a change of basis, whereas traditional vectors obey contravariant transformation rules. [wikipedia link]

Vectors are contravariant because their components transform in the opposite way that the basis does. For example, shrinking the basis vectors makes a vector's components grow larger; also, rotating the basis clockwise makes the components of a vector rotate counter-clockwise.

1-forms are covariant because their components transform in the same ways as the basis. Shrinking the basis vectors makes a 1-form's components shrink as well (the stacks of planes appear farther apart, and the 1-form is therefore smaller).

eigenchris
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I recommend a excellent reading about differential forms with some previous results in linear algebra, in my point-view.

1: Differential Forms, by Henri Cartan. This book is ideal for understand differential forms in various contexts, for example, Cartan develops the theory of forms in space of finite and infinite dimension.

And for differential forms in geometry, you can consult:

2: Differential Forms, by Manfredo do Carmo. This book is ideal to learn the concepts of differential forms to apply in Differential Geometry.

So a quick reading of Manfredo's book will be great for you and your doubts, but I recommend, principally for geometry study, a reading in Cartan's book.

Irddo
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  • Hi Irddo, I was looking at this thread and I was wondering if you know any site where I could download (or buy the printed version) the book: Lições de Equações Diferenciais Ordinárias by Sotomayor (in english or portuguese, I'm a spanish speaker and have been studying mathematical physics with many books written in portuguese). I did download the book, however the quality is very poor since the file contains scanned pages. I'm very thankful if you could provide me – Vladimir Vargas Oct 30 '15 at 04:38
  • some source to download a version of this book in a somewhat good quality. Thanks a lot. – Vladimir Vargas Oct 30 '15 at 04:39
  • Hi @VladimirVargas, I have a version here in pdf, but not in very good quality. I can send to you, by email. How can we do that? – Irddo Oct 30 '15 at 13:58
  • you can send it to [email protected] Thank you! – Vladimir Vargas Oct 30 '15 at 15:03
  • Sent! You're welcome, @VladimirVargas. – Irddo Oct 30 '15 at 17:20