I'm trying to think about this problem I'm faced with.
My peer stated that a non-trivial homogeneous system (which is square) has a column/row of zeros, but I'm trying to make sense of that. It's pretty mind-boggling at the moment. Can anyone help?
Do all homogeneous systems with non-trivial solutions have columns of zeros
linear algebra
Related Solutions
1st question: This means that the system $Bx=0$ has non trivial solutions (Why is that so? An explanation would be very much appreciated!).
If one of the rows of the matrix $B$ consists of all zeros then in fact you will have infinitely many solutions to the system $Bx=0$. As a simple case consider the matrix $M=\left(\begin{array}{cc} 1 & 1 \\ 0 & 0 \end{array} \right)$. Then the system $Mx=0$ has infinitely many solutions, namely all points on the line $x+y=0$.
2nd question: This is also true for the equivalent system $Ax=0$ and this means that A is non invertible (An explanation how they make this conclusion would also be much appreciated).
Since the system $Ax=0$ is equivalent to the system $Bx=0$ which has non-trivial solutions, $A$ cannot be invertible. If it were then we could solve for $x$ by multiplying both sides of $Ax=0$ by $A^{-1}$ to get $x=0$, contradicting the fact that the system has non-trivial solutions.
[Math] Can a set of 4 vectors with 3 entries each only span R2 if the third row reduces to all zeros
So the question is to find the span of $v_{1} = \begin{bmatrix} 1 \\ 0 \\ 2 \\ \end{bmatrix}$, $v_{2} = \begin{bmatrix} 3 \\ 1 \\ 1 \\ \end{bmatrix}$, $v_{3} = \begin{bmatrix} 9 \\ 4 \\ -2 \\ \end{bmatrix}$, and $v_{4} = \begin{bmatrix} -7 \\ 3 \\ 1 \\ \end{bmatrix}$.
Before trying to solve this problem, it is important to know what span means. The first thing you need to know is where the vectors live. To figure this out, count the number of components in one of the vectors. In this case, there are 3 components in each vector, so these vectors live in $\mathbb{R}^{3}$. The first component corresponds to the $x$-axis, the second component corresponds to the $y$-axis, and the third component corresponds to the $z$-axis.
Now, if we take two linearly independent vectors, say $v_{1} = \begin{bmatrix} 1 \\ 0 \\ 0 \end{bmatrix}$ and $v_{2} = \begin{bmatrix} 0 \\ 1 \\ 0 \end{bmatrix}$, then these vectors clearly live in $\mathbb{R}^{3}$, since they each have 3 components. Since they are linearly independent, and there are 2 of them, they span a plane in $\mathbb{R}^{3}$. This particular plane is isomorphic to $\mathbb{R}^{2}$, but it is not $\mathbb{R}^{2}$, because vectors in $\mathbb{R}^{2}$ all look like $\begin{bmatrix} x \\ y \\ \end{bmatrix}$ (i.e., they have 2 components only). A plane in $\mathbb{R}^{3}$ is clearly 2-dimensional since that is how we define a plane, but we do not describe it as $\mathbb{R}^{2}$. Instead, we simply say it is a plane in $\mathbb{R}^{3}$.
Here is an example of what I mean: span$\left \{\begin{bmatrix} 1 \\ 0 \\ 0 \end{bmatrix}, \begin{bmatrix} 0 \\ 1 \\ 0 \end{bmatrix} \right \}$ is the $XY$-plane in $\mathbb{R}^{3}$, while span$\left \{\begin{bmatrix} 1 \\ 0 \\ 0 \end{bmatrix}, \begin{bmatrix} 0 \\ 0 \\ 1 \end{bmatrix} \right \}$ is the $XZ$-plane in $\mathbb{R}^{3}$, and span$\left \{\begin{bmatrix} 0 \\ 1 \\ 0 \end{bmatrix}, \begin{bmatrix} 0 \\ 0 \\ 1 \end{bmatrix} \right \}$ is the $YZ$-pane in $\mathbb{R}^{3}$. All three of the spans I just mentioned are isomorphic to $\mathbb{R}^{2}$, but they are distinct planes in $\mathbb{R}^{3}$, which is why we must describe them as planes in $\mathbb{R}^{3}$, rather than just as $\mathbb{R}^{2}$. When described as planes, they can be differentiated from each other, which is good because they are different planes.
Now, on to your question, as you correctly stated, to determine which vectors are linearly independent (in order to determine the dimension of the span), we put the vectors as columns in a matrix and reduce to RREF. So after doing that, we get that
$\begin{bmatrix} 1 & 3 & 9 & -7 \\ 0 & 1 & 4 & 3 \\ 2 & 1 & -2 & 1 \\ \end{bmatrix}$ reduces to $\begin{bmatrix} 1 & 0 & -3 & 0 \\ 0 & 1 & 4 & 0 \\ 0 & 0 & 0 & 1 \\ \end{bmatrix}$
We see that there are three pivots! The number of pivots is the number of linearly independent columns, and the pivots correspond to the linearly independent columns, so the vectors $ \left \{ \begin{bmatrix} 1 \\ 0 \\ 2 \\ \end{bmatrix}, \begin{bmatrix} 3 \\ 1 \\ 1 \\ \end{bmatrix}, \begin{bmatrix} -7 \\ 3 \\ 1 \\ \end{bmatrix} \right \}$ (which are $v_{1}$, $v_{2}$, and $v_{4}$) are the linearly independent ones, and $v_{3}$ is linearly dependent on them. Since there are three linearly independent vectors, the span of all four vectors is equal to the span of the three linearly independent ones. Three linearly independent vectors span a subspace that is 3-dimensional. But these vectors live in $\mathbb{R}^{3}$, which is 3-dimensional itself, so their span must be equal to $\mathbb{R}^{3}$. If these vectors happened to live in $\mathbb{R}^{4}$, then their span would be a 3-dimensional subspace of $\mathbb{R}^{4}$.
So to answer your question, these four vectors could have spanned a 2-dimensional subspace of $\mathbb{R}^{3}$ if only two of the four were linearly independent. But we had three pivots in our matrix, so three linearly independent vectors, which meant the span of the four was equal to the span of the three linearly independent vectors (i.e., span$\{ v_{1}, v_{2}, v_{3}, v_{4} \} = $ span$\{ v_{1}, v_{2}, v_{4} \}$), and they spanned all of $\mathbb{R}^{3}$ in this case because they live in the 3-dimensional space and their span is 3-dimensional.
Best Answer
Suppose we have a homogeneous system with $n$ equations and $n$ unknowns. What this represents is the system $Ax = 0$ for some square matrix $A$. To say that there is a non-trivial solution to this system means that there is a nonzero vector $x$ such that $Ax = 0$. That is, the null space of $A$ has a nonzero vector, and hence it has dimension at least 1. By the rank-nullity theorem, the rank of the matrix is strictly less than the number of columns. But this corresponds to saying that the row-reduced echelon form of the matrix has at most $n - 1$ pivot columns. Hence there is at least one zero row.
However, it is not necessarily the case that we always have a zero column. Consider $\begin{pmatrix}1&1\\ 1&1\end{pmatrix}$ which has RREF of $\begin{pmatrix}1&1\\ 0&0\end{pmatrix}$. This has no zero column, but it has a non-trivial solution, e.g. $(1,-1)$.