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Wir betrachten im \(\mathbb{R}^{2}\) die drei Untervektorr盲ume \(U_{1}=\left\langle\left\\{\left(\begin{array}{l}1 \\\ 2\end{array}\right)\right\\}\right\rangle, U_{2}=\left\langle\left\\{\left(\begin{array}{l}1 \\\ 1\end{array}\right),\left(\begin{array}{c}1 \\\ -2\end{array}\right)\right\\}\right)\) und \(U_{3}=\) \(\left\langle\left\\{\left(\begin{array}{c}1 \\\ -3\end{array}\right)\right\\}\right\rangle\). Welche der folgenden Aussagen ist richtig? (a) Es ist \(\left\\{\left(\begin{array}{l}-2 \\\ -4\end{array}\right)\right\\}\) ein Erzeugendensystem von \(U_{1} \cap U_{2}\). (b) Die leere Menge \(\emptyset\) ist eine Basis von \(U_{1} \cap U_{3}\). (c) Es ist \(\left\\{\left(\begin{array}{l}1 \\ 4\end{array}\right)\right\\}\) eine linear unabh盲ngige Teilmenge von \(U_{2}\). (d) Es gilt \(\left\langle U_{1} \cup U_{3}\right\rangle=\mathbb{R}^{2}\).

Short Answer

Expert verified
Given three subspaces of 鈩澛: U鈧, U鈧, and U鈧, we analyzed whether the given statements (a), (b), (c), and (d) are correct. We found the following results: Statement (a): The set {(-2,-4)} is a generating set for the intersection of U鈧 and U鈧. This statement is true. Statement (b): The empty set is a generating set for the intersection of U鈧 and U鈧. This statement is true. Statement (c): The vector (1,4) is linearly independent in subspace U鈧. This statement is false. Statement (d): The span of the union of subspaces U鈧 and U鈧 is 鈩澛. This statement is true.

Step by step solution

01

Statement (a): Intersection of \(U_1\) and \(U_2\)

We are given that \(\left(-2,-4\right)\) is a generating set of \(U_1 \cap U_2\). We have to check whether this vector is in both \(U_1\) and \(U_2\). For \(U_1\), there must exist a scalar \(k_1\) such that: $$\left(-2,-4\right) = k_1 \cdot \left(\begin{array}{l}1 \\\ 2\end{array}\right)$$ Solving for \(k_1\), we find that indeed \(k_1=-2\). So, the vector \(\left(-2,-4\right)\) is in \(U_1\). For \(U_2\), there must exist scalars \(k_2\) and \(k_3\) such that: $$\left(-2,-4\right) = k_2 \cdot \left(\begin{array}{l}1 \\\ 1\end{array}\right) + k_3 \cdot \left(\begin{array}{c}1 \\\ -2\end{array}\right)$$ Solving the system of linear equations, we find that \(k_2 = -\frac{4}{3}\) and \(k_3 = -\frac{10}{3}\). Therefore, the vector \(\left(-2,-4\right)\) is also in \(U_2\). Hence, \(\left\\{\left(\begin{array}{l}-2 \\\ -4\end{array}\right)\right\\}\) is indeed a generating set of \(U_1 \cap U_2\), so statement (a) is correct.
02

Statement (b): Intersection of \(U_1\) and \(U_3\)

We have to check if the empty set is a basis for the intersection \(U_1 \cap U_3\). If the intersection is the zero-vector space, this statement is true. Let's see if there exists some scalar \(k\) to satisfy: $$k \cdot \left(\begin{array}{l}1 \\\ 2\end{array}\right) = k' \cdot \left(\begin{array}{c}1 \\\ -3\end{array}\right)$$ From the first components, we get \(k=k'\). For the second components, we get \(2k = -3k'\). But as \(k=k'\), the only solution is \(k = k' = 0\). So, the intersection of \(U_1\) and \(U_3\) is only the zero-vector space. The empty set is indeed a basis for \(U_1 \cap U_3\), making statement (b) correct.
03

Statement (c): Linear Independence in \(U_2\)

We are given the vector \(\left(\begin{array}{l}1 \\\ 4\end{array}\right)\) and we need to check whether it is linearly independent in \(U_2\). Let's first write this vector as a linear combination of the basis vectors of \(U_2\): $$\left(\begin{array}{l}1 \\\ 4\end{array}\right) = k_4 \cdot \left(\begin{array}{l}1 \\\ 1\end{array}\right) + k_5 \cdot \left(\begin{array}{c}1 \\\ -2\end{array}\right)$$ Solving the system of linear equations, we get \(k_4=\frac{9}{3}, k_5=\frac{2}{3}\). As this vector can be written as a linear combination of the basis vectors, it is not linearly independent in \(U_2\). Therefore, the statement (c) is false.
04

Statement (d): Span of the union of \(U_1\) and \(U_3\)

We are given the union of \(U_1\) and \(U_3\), and we need to check whether their span is \(\mathbb{R}^{2}\). To do this, let's check if the basis vectors for \(U_1\) and \(U_3\) generate \(\mathbb{R}^{2}\). We can start by creating a matrix with the basis vectors as columns: $$\left(\begin{array}{cc}1 & 1 \\ 2 & -3\end{array}\right)$$ Taking the determinant of this matrix, we find that it is nonzero. This means that the column vectors are linearly independent, indicating that their span is \(\mathbb{R}^2\). So, the statement (d) is true. In conclusion, statements (a), (b), and (d) are true while statement (c) is false.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Linear Independence
Linear independence is a fundamental concept in vector spaces. When we say a set of vectors is linearly independent, we mean that no vector in this set can be written as a linear combination of the others. For example, in the vector subspace \(U_2\) given by \(\left\{ \left( \begin{array}{c} 1 \ 1 \end{array} \right), \left( \begin{array}{c} 1 \ -2 \end{array} \right) \right\}\), a vector \(\left( \begin{array}{c} 1 \ 4 \end{array} \right)\) is not linearly independent because it can be expressed as \(k_4 \cdot \left( \begin{array}{c} 1 \ 1 \end{array} \right) + k_5 \cdot \left( \begin{array}{c} 1 \ -2 \end{array} \right)\) with non-zero coefficients \(k_4\) and \(k_5\).
The test for linear independence involves setting the linear combination to zero and ensuring the only solution is for all coefficients to be zero. If this condition does not hold, the vectors are dependent.
Basis of a Vector Space
A basis of a vector space is a set of vectors that are both linearly independent and span the entire vector space. For example, if you have vectors \(\left( \begin{array}{c} 1 \ 2 \end{array} \right)\) and \(\left( \begin{array}{c} 1 \ -3 \end{array} \right)\), they form a basis if they span the space and are not scalar multiples of one another. For the intersection \(U_1 \cap U_3\), the zero vector space (only containing the zero vector), the empty set is a basis. This is an easy case where no vectors are needed to span the space, as long as the only vector is the zero vector.
Bases help us to uniquely describe every other vector in the space, as each vector can be expressed as a linear combination of the basis vectors.
Intersection of Vector Spaces
The intersection of vector spaces involves finding common vectors that are present in multiple vector spaces. In our exercise, we checked the intersection \(U_1 \cap U_2\) where \(\left( \begin{array}{c} -2 \ -4 \end{array} \right)\) serves as a generating set. This means that this vector is common to both \(U_1\) and \(U_2\), and accurately generates the intersecting space.
To determine the intersection, solve for scalars such that the vector in question can be expressed using the basis of each space. If they are expressible in each space, it confirms their presence in the intersection.
Generating Set
A generating set, or spanning set, is a collection of vectors whose linear combinations fill up the entire vector space. For instance, in the given spaces \(U_1\) and \(U_3\) whose union spans \(\mathbb{R}^2\), the vectors furnish a generating set for the entire plane. This occurs when the set's vectors can form a linearly independent set that covers the space by spanning the dimension needed, such as in \(\mathbb{R}^2\).
A generating set is useful because it provides a complete "alphabet" of vectors that can be combined to describe any position within the space. It essentially outlines all possible vectors that can be formed in that setup.

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Most popular questions from this chapter

Geben Sie zu folgenden Teilmengen des \(\mathbb{R}\)-Vektorraums \(\mathbb{R}^{3}\) an, ob sie Untervektorr盲ume sind, und begr眉nden Sie dies: (a) \(U_{1}:=\left\\{\left(\begin{array}{l}v_{1} \\ v_{2} \\\ v_{3}\end{array}\right) \in \mathbb{R}^{3} \mid v_{1}+v_{2}=2\right\\}\) (b) \(U_{2}:=\left\\{\left(\begin{array}{l}v_{1} \\ v_{2} \\\ v_{3}\end{array}\right) \in \mathbb{R}^{3} \mid v_{1}+v_{2}=v_{3}\right\\}\) (c) \(U_{3}:=\left\\{\left(\begin{array}{l}v_{1} \\ v_{2} \\\ v_{3}\end{array}\right) \in \mathbb{R}^{3} \mid v_{1} v_{2}=v_{3}\right\\}\) (d) \(U_{4}:=\left\\{\left(\begin{array}{l}v_{1} \\ v_{2} \\\ v_{3}\end{array}\right) \in \mathbb{R}^{3} \mid v_{1}=v_{2}\right.\) oder \(\left.v_{1}=v_{3}\right\\}\)

Gegeben sind ein Untervektorraum \(U\) eines \(\mathbb{K}-\) Vektorraums \(V\) und Elemente \(\boldsymbol{u}, \boldsymbol{w} \in V\). Welche der folgenden Aussagen sind richtig? (a) Sind \(u\) und \(w\) nicht in \(U\), so ist auch \(u+w\) nicht in \(U\). (b) Sind \(u\) und \(w\) nicht in \(U\), so ist \(u+w\) in \(U\). (c) Ist \(u\) in \(U\), nicht aber \(\boldsymbol{w}\), so ist \(\boldsymbol{u}+\boldsymbol{w}\) nicht in \(U\).

Bestimmen Sie eine Basis des von der Menge $$ X=\left\\{\left(\begin{array}{c} 0 \\ 1 \\ 0 \\ -1 \end{array}\right),\left(\begin{array}{c} 1 \\ 0 \\ 1 \\ -2 \end{array}\right),\left(\begin{array}{c} -1 \\ -2 \\ 0 \\ 1 \end{array}\right)\left(\begin{array}{c} -1 \\ 0 \\ 1 \\ 0 \end{array}\right),\left(\begin{array}{c} 1 \\ 0 \\ -1 \\ -1 \end{array}\right),\left(\begin{array}{c} 2 \\ 0 \\ -1 \\ 0 \end{array}\right)\right\\} $$ erzeugten Untervektorraums \(U:=\langle X\rangle\) des \(\mathbb{R}^{4}\).

F眉r einen K枚rper \(\mathbb{K}\) und eine nichtleere Menge \(M\) definieren wir \(V:=\left\\{f \in \mathbb{K}^{M} \mid\right.\) nur f眉r endlich viele \(x \in M\) ist \(\left.f(x) \neq 0\right\\}\) Es ist \(V\) also eine Teilmenge von \(\mathbb{K}^{M}\), dem Vektorraum aller Abbildungen von \(M\) nach \(\mathbb{K}\) (siehe S. 540). (a) Begr眉nden Sie, dass \(V\) ein \(\mathrm{K}\)-Vektorraum ist. (b) F眉r jedes \(y \in M\) definieren wir eine Abbildung \(\delta_{y}: M \rightarrow \mathbb{K}\) durch: $$ \delta_{y}(x):= \begin{cases}1, & \text { falls } x=y \\ 0, & \text { sonst }\end{cases} $$ Begr眉nden Sie, dass \(B:=\left\\{\delta_{y} \mid y \in M\right\\}\) eine Basis von \(V\) ist.

Gelten in einem Vektorraum \(V\) die folgenden Aussagen? (a) Ist eine Basis von \(V\) unendlich, so sind alle Basen von \(V\) unendlich. (b) Ist eine Basis von \(V\) endlich, so sind alle Basen von \(V\) endlich. (c) Hat \(V\) ein unendliches Erzeugendensystem, so sind alle Basen von \(V\) unendlich. (d) Ist eine linear unabh盲ngige Menge von \(V\) endlich, so ist es jede.

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