Conditions on Matrix Imply Conditions on Elements

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Discussion Overview

The discussion revolves around the properties of a matrix and its reduced row echelon form (RREF). Participants explore the implications of certain conditions on the matrix elements, specifically focusing on the third row of a given matrix, the determination of specific values, and the solutions to a homogeneous system of equations. The scope includes theoretical reasoning and mathematical problem-solving related to linear algebra.

Discussion Character

  • Exploratory
  • Technical explanation
  • Homework-related
  • Mathematical reasoning

Main Points Raised

  • Some participants discuss the implications of having a row of all zeros in the RREF, suggesting that it indicates linear dependence on the other rows.
  • There are multiple suggestions for possible third rows of the matrix that would lead to a row of zeros, with examples provided by participants.
  • Participants propose methods for determining the values of parameters 'a' and 'b' based on the relationships established in the RREF.
  • Some participants emphasize the need to row-reduce the matrix to find the general solution to the homogeneous system of equations.
  • One participant shares an example of a different matrix to illustrate how a third row can quickly become all zeros during row reduction.
  • Another participant describes the process of row reduction and the conditions under which certain entries must equal zero to maintain consistency in the equations.

Areas of Agreement / Disagreement

Participants generally agree on the properties of the RREF and the implications of having a row of zeros, but there are multiple competing views on the specific values of 'a' and 'b' and how to approach the row reduction process. The discussion remains unresolved regarding the complete determination of these values and the final solutions to the system.

Contextual Notes

Participants express uncertainty about how to proceed with the row reduction without knowing the elements of the third row, indicating a dependency on specific values and assumptions that remain unverified.

SiddharthThakur
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Question 1
The reduced row echelon form of










 
3
4 17 22
1 2 5
row
a
b
A is equal to










 
0 0 0 0
0 0 1 2
1 2 0 3
R .
(a) What can you say about row 3 of A? Give an example of a possible third row for A.
(b) Determine the values of a and b.
(c) Determine the solution of the homogeneous system of equations Rx = 0 in parametric vector
form.
(d) What is the dimension of the column space of A? Do the columns of A span R3 ?
 
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Hi SiddharthThakur. Welcome to MHB. :) I can't really read your matrices well so until you fix them I can't comment on your specific problem but I can make a couple of comments in general about how to approach the problem.

(a) If there are any rows with entries of all 0, those rows should be below any non-zero rows.

(c) Make an augmented matrix and place a column of 0s in the last column. Now reduce to reduced row echelon form. From that point you should be able to write the general solution $R \hspace{1 mm} \vec{x}=\vec{0}$ in terms of your free variables.

(d) To find $\text{dim } \text{Col } A$, or simply $\text{rank } A$, find the pivot positions of the RREF matrix or just the echelon form and count the columns which have a pivot position in them. So if some matrix has a pivot position in columns 1,4,5,9 then $\text{dim } \text{Col }$ of that matrix is 4.
 
The reduced row echelon form of A=[1,2,5,b_ 4,a,17,-22_ row3]
is equal to R=[1,2,0,3_ 0,0,1,-2_ 0,0,0,0]
(a) What can you say about row 3 of A? Give an example of a possible third row for A.
(b) Determine the values of a and b.
(c) Determine the solution of the homogeneous system of equations Rx = 0 in parametric vector
form.
(d) What is the dimension of the column space of A? Do the columns of A span

(its 3x4 matrices 3rows 4 columns)
 
SiddharthThakur said:
The reduced row echelon form of A=[1,2,5,b_ 4,a,17,-22_ row3]
is equal to R=[1,2,0,3_ 0,0,1,-2_ 0,0,0,0]

(a) What can you say about row 3 of A? Give an example of a possible third row for A.
(b) Determine the values of a and b.
(c) Determine the solution of the homogeneous system of equations Rx = 0 in parametric vector
form.
(d) What is the dimension of the column space of A? Do the columns of A span

(its 3x4 matrices 3rows 4 columns)

So $$A = \left( \begin{array}{cccc} 1 & 2 & 5 & b \\ 4 & a & 17 & -22 \\ i_{31} & i_{32} & i_{33} & i_{34} \end{array}\right)$$

and the RREF of $$A =\left( \begin{array}{cccc} 1 & 2 & 0 & 3 \\ 0 & 0 & 1 & -2 \\ 0 & 0 & 0 & 0 \end{array}\right)$$?

(a) When a row cancels out to all 0s that means it carries the same information as an above row. So if you have a row that is $x+y+z=2$ and another row that is $2x+2y+2z=4$, then the last row can be reduced to all 0s because it's just the same thing. How can you use that fact to give a possible row 3?

(b) What have you tried? Basically start trying to reduce A into RREF A and you should find some equalities to use. If you post what you've done I can help you continue. :)

(c), (d) We need to complete (b) to get a full answer for these.
 
I'm not able to do this question.How can I reduced it into RREF without knowing the elements of row3...?
Its confusing me a lot.
 
I'll use another matrix as an example.

$$A =\left( \begin{array}{cccc} 1 & 1 & 1 & 1 \\ 2 & 0 & 3 & 5 \\ 2 & 2 & 2 & 2 \end{array}\right)$$.

The third row becomes all 0s very quickly when trying to find the RREF of this matrix. Why?
 
Since the deadline for the assignment in question has passed, I will make some more comments on solving the problem so others can use the information in the future.

We are given a matrix $A$:

$\displaystyle A = \left( \begin{array}{cccc} 1 & 2 & 5 & b \\ 4 & a & 17 & -22 \\ i_{31} & i_{32} & i_{33} & i_{34} \end{array}\right)$ and we know that it is row-equivalent to: $\displaystyle A =\left( \begin{array}{cccc} 1 & 2 & 0 & 3 \\ 0 & 0 & 1 & -2 \\ 0 & 0 & 0 & 0 \end{array}\right)$.

(a) Since the third row contains entries which are all 0, that means the third row is a linear combination of the first two. There are infinite possible third rows for matrix $A$ that reduce to all 0's, but here is one:

$\displaystyle A = \left( \begin{array}{cccc} 1 & 2 & 5 & b \\ 4 & a & 17 & -22 \\ 2 & 4 & 10 & 2b \end{array}\right)$

We can easily see that $R_3=2R_1$ in this example and we can easily reduce $R_3$ to all 0's.

(b) Let's start row-reducing $A$, letting the third row start with all 0's because we know it is a linear combination of the first two rows.

$\displaystyle A = \left( \begin{array}{cccc} 1 & 2 & 5 & b \\ 4 & a & 17 & -22 \\ 0 & 0 & 0 & 0 \end{array}\right) \sim \left( \begin{array}{cccc} 1 & 2 & 5 & b \\ 0 & a-8 & -3 & -22-4b \\ 0 & 0 & 0 & 0 \end{array}\right) \sim \left( \begin{array}{cccc} 1 & 2 & 5 & b \\ 0 & \frac{a-8}{-3} & 1 & \frac{-22-4b}{-3} \\ 0 & 0 & 0 & 0 \end{array}\right)$

Now we want to eliminate the term $i_{13}$ by multiplying using the replacement equation $R_1=-5R_2+R_1$. However we want the term $i_{12}$ to remain as 2, so the only way that's possible is if:

$$\frac{a-8}{-3}=0 \implies a=8$$

Using the same replacement of $R_1=-5R_2+R_1$ we get the relation that:

$$-5 \left( \frac{-22-4b}{-3} \right)+b=3 \implies b=-7$$

We can check this on Wolfram by reducing the matrix: $\left( \begin{array}{cccc} 1 & 2 & 5 & -7 \\ 4 & 8 & 17 & -22 \\ 0 & 0 & 0 & 0 \end{array}\right)$ and we see that we have correctly found $a$ and $b$.

I will answer the other parts in a later post.
 

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