Verifying a linear transformation

In summary, the trace function tr(A) is a linear transformation that maps from the space of matrices to the real numbers. While the "field of real numbers" and the "vector space of real numbers" are technically different, they can be considered as the same thing in the context of vector spaces. This is because the real numbers satisfy the properties of a vector space when defining the set of vectors, scalars, zero vector, and zero scalar as the number zero.
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Mr Davis 97
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I am told that the trace function tr(A) is a linear transformation. But this function maps from the space of matrices to the real numbers. How can this be a linear transformation if the set of real numbers isn't a vector space? Or is it? Can a field also be considered a vector space?
 
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  • #2
Mr Davis 97 said:
Can a field also be considered a vector space?

Yes.

To split hairs , the "field of real numbers" is technically different than "the vector space of real numbers", but, Platonically, we think of the real numbers as being a single "thing" and that thing satisfies the properties of a vector space if we define the set of vectors as being the real numbers, the set of scalars as being the real numbers and the zero vector and the zero scalar, each to be the number zero.
 
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  • #3
Stephen Tashi said:
To split hairs , the "field of real numbers" is technically different than "the vector space of real numbers", but, Platonically, we think of the real numbers as being a single "thing".
I just thought about the mess, if we really distinguished between them: ##\mathbb{R}## as group, ring, algebra, module, field, integral domain, division ring, topological space, manifold, affine space, vector space, Euclidean space, metric space, Hilbert space, Banach space.
 

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another while preserving the basic structure of the vector space. In other words, it is a transformation that preserves addition and scalar multiplication.

2. How do you verify if a transformation is linear?

To verify if a transformation is linear, you can use two methods: the transformation rule and the properties of linearity. The transformation rule states that for a transformation to be linear, it must satisfy T(ax+by) = aT(x) + bT(y). The properties of linearity include preservation of addition and scalar multiplication, and the transformation of the zero vector to the zero vector.

3. Why is it important to verify a linear transformation?

Verifying a linear transformation is important because it ensures that the transformation is valid and can be used in further calculations and applications. It also helps in understanding the properties and behavior of the transformation.

4. What are the consequences of a non-linear transformation?

A non-linear transformation does not preserve the basic structure of a vector space, which can lead to incorrect results and interpretations in mathematical models and applications. It also makes it difficult to perform further calculations and analysis using the transformation.

5. Can a transformation be both linear and non-linear?

No, a transformation cannot be both linear and non-linear. It is either one or the other based on whether it satisfies the properties of linearity or not. However, a transformation can be both affine (preserves parallel lines) and linear at the same time.

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