Can Multilinear Maps Be Represented with Matrices?

  • Thread starter WWGD
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In summary, there are standard ways of representing linear and bilinear maps between vector spaces, but is there a way to represent higher-order p-linear maps? These maps can be represented by matrices with p indices, but this can make reading and writing proofs difficult.
  • #1
WWGD
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Hi, everyone:

There are standard ways of representing linear and bilinear maps.
between (fin. dim) vector spaces, after choosing a basis .Linear maps
are represented by columns T(vi) , for a basis {v1,...,vn} (assume B
defined on VxV ), bilinear maps B(x,y) with the matrix Bij=(B(ei,ej))
Is there a way of representing 3-linear, 4-linear, etc. maps with
matrices?. I have played around with matrices T(ei,ej,ek), but
I cannot see how to get a real number as a product of 3 matrices.
Any ideas?.

P.S: I don't know how to setup the spacing.In this forum I was asked
to not leave spacing. In other forums, people complain when I don't
leave spacing, because the lack of spaces force them to strain their
eyes ( where they also complain about how kids today don't understand
music, and about how Frank Sinatra was the last good singer. They also
talk about Selzer water Melba toast, and that hot new comedian Red Skelton.
. Maybe this last explains it :smile:)
 
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  • #2
Here is the answer, given to me by someone else (Prof. R. Israel), in case anyone
else is interested:

Suppose T is an n-linear map from V^n to W, and B = {b_i: i=1..m} is a basis
of V. Then the m^n vectors T(b_i) = T(b_{i_1},...,b_{i_n}) for n-tuples
i = (i_1,...,i_n) in {1..m}^n determine T, since if each
x_j = sum_{k = 1}^m c_{j,k} b_k,
T(x_1,...,x_n) = sum_{i in {1..m}^n} product_{j=1}^n c_{j, i_j} T(b_i).

A bilinear map from V^2 to the reals R, for example, can be represented by an
m x m matrix of real numbers: each entry has a pair of indices. A trilinear
map from V^3 to the reals would be represented by a triply-indexed array
of real numbers, rather than a matrix.
 
  • #3
A p-linear map can be represented by a matrix (tensor) with p indices. Most of the basic theorems with linear maps and bilinear maps are generalized to the p-linear case. The proofs remain the same too, but reading and writing the proofs is really messy because of all the indices.
 

1. What are multilinear maps?

Multilinear maps are mathematical objects that generalize the concept of a linear map, which maps between vector spaces. They can be defined as maps that take multiple inputs and produce an output, where the output is linear in each of the inputs.

2. What are the applications of multilinear maps?

Multilinear maps have various applications in mathematics, computer science, and cryptography. They are used in algebraic geometry, representation theory, and quantum field theory. In computer science, they are used in image processing, computer vision, and natural language processing. In cryptography, they are used to construct secure cryptographic protocols.

3. How are multilinear maps extended?

Multilinear maps can be extended in various ways, such as extending the domain or codomain, or by adding more inputs or outputs. These extensions can help to generalize the concept of multilinear maps and make them applicable to different mathematical and scientific fields.

4. What are some challenges in studying multilinear maps?

One of the main challenges in studying multilinear maps is finding efficient and secure constructions. Multilinear maps are also prone to various attacks, such as zeroizing attacks and algebraic attacks. Another challenge is understanding the theoretical properties of multilinear maps, as they are still a relatively new area of research.

5. Are there any open problems related to multilinear maps?

Yes, there are several open problems related to multilinear maps that are actively being researched. Some of these include finding more efficient constructions, improving the security of existing constructions, and understanding the theoretical properties of multilinear maps. Additionally, there are open problems related to the applications of multilinear maps, such as using them to construct more secure cryptographic protocols.

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