Question

Suppose that \(\left\\{\alpha_{i}\right\\}_{i=1}^{n}\) spans an \(R\) -module \(M\) and that \(\rho: M \rightarrow\) \(M^{\prime}\) is an \(R\) -linear map. Show that: (a) \(\rho\) is surjective if and only if \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) spans \(M^{\prime} ;\) (b) if \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) is linearly independent, then \(\rho\) is injective.

Short answer

Question: Prove the following statements for a given set of elements \(\left\\{\alpha_{i}\right\\}_{i=1}^{n}\) that span an \(R\)-module \(M\) and an \(R\)-linear map \(\rho: M \rightarrow M^{\prime}\): (a) \(\rho\) is surjective if and only if \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) spans \(M^{\prime}\). (b) If \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) is linearly independent, then \(\rho\) is injective. Answer: (a) For \(\rho\) to be surjective, it must cover all elements in \(M^{\prime}\), and if \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) spans \(M^{\prime}\), then every element in \(M^{\prime}\) can be expressed as a linear combination of the images of the \(\alpha_i\) elements under \(\rho\). We've shown that both implications hold, proving that \(\rho\) is surjective if and only if \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) spans \(M^{\prime}\). (b) If \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) is linearly independent, we can show that \(\rho\) is injective. This is demonstrated by considering the case when \(\rho(m) = \rho(m^{\prime})\), which implies \(m = m^{\prime}\). Thus, we've proved that if \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) is linearly independent, \(\rho\) is injective.

Step-by-step solution

Part (a): Assumption of surjectivity

Assume that \(\rho\) is surjective. This means that for any \(m^{\prime} \in M^{\prime}\), there exists an \(m \in M\) such that \(\rho(m) = m^{\prime}\). Since \(\left\\{\alpha_{i}\right\\}_{i=1}^{n}\) spans \(M\), any element of \(M\) can be written as a linear combination of the \(\alpha_{i}\)'s, i.e. \(m = r_1 \alpha_1 + r_2 \alpha_2 + \cdots + r_n \alpha_n\) for some \(r_i \in R\). Then, we can find such a linear combination to obtain \(\rho(m)\): $$\rho(m) = \rho(r_1 \alpha_1 + r_2 \alpha_2 + \cdots + r_n \alpha_n).$$

Part (a): Application of linearity

Using the linearity of \(\rho\), we can rewrite the expression above as a linear combination of the images of the \(\alpha_i\)'s under \(\rho\): $$\rho(r_1 \alpha_1 + r_2 \alpha_2 + \cdots + r_n \alpha_n) = r_1 \rho(\alpha_1) + r_2 \rho(\alpha_2) + \cdots + r_n \rho(\alpha_n).$$ Now \(m^{\prime}\) can be written as a linear combination of \(\left\\{\rho(\alpha_{i})\right\\}_{i=1}^{n}\), which implies that \(\left\\{\rho(\alpha_{i})\right\\}_{i=1}^{n}\) spans \(M^{\prime}\).

Part (a): Assumption of spanning

Now, let's assume that \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) spans \(M^{\prime}\). So, every \(m^{\prime} \in M^{\prime}\) can be expressed as a linear combination of the images of the \(\alpha_i\)'s under \(\rho\): $$m^{\prime} = r_1 \rho(\alpha_1) + r_2 \rho(\alpha_2) + \cdots + r_n \rho(\alpha_n).$$

Part (a): Surjective \(\rho\)

Since \(\left\\{\alpha_{i}\right\\}_{i=1}^{n}\) spans \(M\), there exists \(m \in M\) such that \(m = r_1 \alpha_1 + r_2 \alpha_2 + \cdots + r_n \alpha_n\). Then, we have: $$\rho(m) = \rho(r_1 \alpha_1 + r_2 \alpha_2 + \cdots + r_n \alpha_n) = r_1 \rho(\alpha_1) + r_2 \rho(\alpha_2) + \cdots + r_n \rho(\alpha_n) = m^{\prime}.$$ Since every \(m^{\prime} \in M^{\prime}\) has a pre-image in \(M\), \(\rho\) is surjective. Thus, we've shown both implications, and Part (a) is proven.

Part (b): Linear independence of \(\rho(\alpha_i)\)

Assume that \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\) is linearly independent. We want to show that \(\rho\) is injective, that is, if \(m, m^{\prime} \in M\) and \(\rho(m) = \rho(m^{\prime})\), then \(m = m^{\prime}\). Consider the difference \(m - m^{\prime} \in M\). Then, \(\rho(m - m^{\prime}) = \rho(m) - \rho(m^{\prime}) = 0\), where \(0\) is the zero vector in \(M^{\prime}\).

Part (b): Showing Injectivity

Since \(\rho(m - m^{\prime}) = 0\), consider the linear combination: \(0 = r_1 \rho(\alpha_1) + r_2 \rho(\alpha_2) + \cdots + r_n \rho(\alpha_n)\), where \(r_i \in R\) and \(\rho(\alpha_i) = \rho(m - m^{\prime})\). By the linear independence of \(\left\\{\rho\left(\alpha_{i}\right)\right\\}_{i=1}^{n}\), it must be that all \(r_i = 0\) for \(i = 1,2,...,n\). Therefore, we have \(\rho(m - m^{\prime}) = 0 = r_1 \rho(\alpha_1) + r_2 \rho(\alpha_2) + \cdots + r_n \rho(\alpha_n) = \rho(r_1 \alpha_1 + r_2 \alpha_2 + \cdots + r_n \alpha_n)\), which implies that \(m - m^{\prime} = r_1 \alpha_1 + r_2 \alpha_2 + \cdots + r_n \alpha_n\). Since all \(r_i = 0\), it follows that \(m - m^{\prime} = 0\), and therefore \(m = m^{\prime}\). Hence, \(\rho\) is injective, and Part (b) is proven.

Key concepts

R-module

An R-module is to ring theory what a vector space is to linear algebra but with a few key differences. In essence, an R-module is a mathematical structure constructed over a ring R where elements can be scaled, but unlike vector spaces, the ring R doesn't necessarily have to be a field.

In our exercise, we looked at an R-module M spanned by a set \(\{\alpha_i\}_{i=1}^n\). To say a set spans an R-module means that any element within the module can be represented as a combination, specifically a linear combination using elements from the ring, of the spanning set members. Modules generalize vector spaces by allowing the 'scalars' to come from a ring, which might lack multiplicative inverses or even commutativity.

Understanding modules is crucial when we start talking about module homomorphisms, particularly those that are surjective.

Surjective map

A surjective map, or onto function, is a concept in mathematics where every element of the function's codomain is mapped to by at least one element of its domain. In the context of R-modules, when we say a homomorphism \(\rho: M \rightarrow M'\) is surjective, we mean that for every element m' in the codomain module M', we can find at least one element m in the domain module M such that \(\rho(m) = m'\).

In the exercise, we proved surjectivity by leveraging the fact that the span of the transformation of the generating set under \(\rho\) could produce every element in M', indicating that \(\rho\) is indeed surjective. The interplay between the original spanning set of M and its image under \(\rho\) was key to establishing the surjective nature of this map.

Linear independence

The concept of linear independence is fundamental to the study of linear algebra and module theory. A set of elements in a module (or a vector space) is said to be linearly independent if no element can be expressed as a linear combination of the others. In simpler terms, in our set \(\{\rho(\alpha_i)\}_{i=1}^{n}\), the elements are linearly independent if the only linear combination that yields the zero element 0 in M' is the one where all coefficients are zero.

It's a concept tightly related to the notion of dimension and basis in vector spaces, and it plays an equivalent role in modules. In the exercise, the key improvement to understanding is recognizing that the linear independence of the images under \(\rho\) directly implies injectivity—the uniqueness of pre-images in M for each element in M'—which is highly significant when considering the structure of modules and their homomorphisms.

Injective map

An injective map, known as a one-to-one function, is a type of function where distinct elements in the domain map to distinct elements in the codomain. For our module homomorphism \(\rho: M \rightarrow M'\), this means that if \(\rho(m) = \rho(m')\), then necessarily m = m'. In essence, there aren't two different elements in M that would be 'squished' into a single element via \(\rho\) in M'.

In the solution to our exercise, we demonstrated that if a set of transformed elements \(\{\rho(\alpha_i)\}_{i=1}^{n}\) is linearly independent, then \(\rho\) must be injective. Injectivity is a reassuring property in many settings; it ensures that information is not 'lost' during the transformation process, which is particularly beneficial when studying structure-preserving maps like module homomorphisms.