Understanding LA: Linear Transformation of Matrix A

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LA, or L_A, is defined as a mapping from F^m to F^n, where L_A(x) = Ax for an m*n matrix A. This mapping demonstrates linearity through two key properties: it preserves vector addition, meaning L_A(x_1 + x_2) = L_A(x_1) + L_A(x_2), and it preserves scalar multiplication, as L_A(cx) = cL_A(x). The discussion references Theorem 2.12, which formalizes these properties and confirms that L_A is indeed a linear transformation. The transformation is not merely a notation but is grounded in these mathematical principles. Understanding these properties is essential for grasping the concept of linear transformations in linear algebra.
jeff1evesque
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How is LA a linear function? What kind of operation is action on A? I thought L denotes a linear transformation. So if we have a matrix A, how is the LA a transformation? Is it just a definition (notation wise) or is there more to it?


Thanks,

JL
 
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jeff1evesque said:
How is LA a linear function? What kind of operation is action on A? I thought L denotes a linear transformation. So if we have a matrix A, how is the LA a transformation? Is it just a definition (notation wise) or is there more to it?


Thanks,

JL
I have no idea what you mean by "LA". How is it defined?
 
If A is an m*n matrix, then the mapping L_A is from F^m to F^n and is defined by L_A(x) = Ax. If x_1 and x_2 ] are vectors in F^n, then L_A (x_1 + x_2) = A(x_1 + x_2) = Ax_1 + Ax_2 = L_A(x_1) + L_A(x_2). Also, for any vector x in F^n and any scalar c, we have L_A(cx) = A(cx) = cAx = cL_A(x). Thus L_A is a linear transformation.
 
JG89 said:
If A is an m*n matrix, then the mapping L_A is from F^m to F^n and is defined by L_A(x) = Ax. If x_1 and x_2 ] are vectors in F^n, then L_A (x_1 + x_2) = A(x_1 + x_2) = Ax_1 + Ax_2 = L_A(x_1) + L_A(x_2). Also, for any vector x in F^n and any scalar c, we have L_A(cx) = A(cx) = cAx = cL_A(x). Thus L_A is a linear transformation.

THanks, that's exactly what I thought. However, in the text I am reading, it says L_A is linear immediately from theorem 2.12:

Theorem 2.12:
Let A be an mxn matrix, B and C be nxp matrices, and D and E be qxm matrices. Then,
(a) A(B + C) = AB + AC and (D + E)A = DA + EA.
(b) a(AB) = (aA)B = A(aB) for any scalar a.
(c) I_mA = A = AI_n
(d) If V is an n-dimensional vector space with an ordered basis J, then [I_V]_J = I_n

THanks again.
 
I am studying the mathematical formalism behind non-commutative geometry approach to quantum gravity. I was reading about Hopf algebras and their Drinfeld twist with a specific example of the Moyal-Weyl twist defined as F=exp(-iλ/2θ^(μν)∂_μ⊗∂_ν) where λ is a constant parametar and θ antisymmetric constant tensor. {∂_μ} is the basis of the tangent vector space over the underlying spacetime Now, from my understanding the enveloping algebra which appears in the definition of the Hopf algebra...

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