Is a Shifted Solution Still Valid?

In summary, a solution to a homogenous system of equations is when $A\mathbf x=\mathbf 0$. When x+1 is the trivial solution, then A=0.
  • #1
Yankel
395
0
Hello all

A simple question.

It is known that

\[\left ( \begin{matrix} x_{1}\\ x_{2}\\ x_{3} \end{matrix} \right )\]

is a solution of a homogenous system of equations.

I need to determine if

\[\left ( \begin{matrix} x_{1}+1\\ x_{2}+1\\ x_{3}+1 \end{matrix} \right )\]

is also a solution, and why ?

thank you !
 
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  • #2
Yankel said:
Hello all

A simple question.

It is known that

\[\left ( \begin{matrix} x_{1}\\ x_{2}\\ x_{3} \end{matrix} \right )\]

is a solution of a homogenous system of equations.

I need to determine if

\[\left ( \begin{matrix} x_{1}+1\\ x_{2}+1\\ x_{3}+1 \end{matrix} \right )\]

is also a solution, and why ?

thank you !

Hi Yankel,

That depends.

A homogenous system means that $A\mathbf x=\mathbf 0$.

So when would $A(\mathbf x + \mathbf 1)=\mathbf 0$ also be a solution? (Wondering)
 
  • #3
I am not sure. I will guess. Maybe when the solution is (-1,-1,-1) and then x+1 is the trivial solution ?
 
  • #4
Yankel said:
I am not sure. I will guess. Maybe when the solution is (-1,-1,-1) and then x+1 is the trivial solution ?

Can you simplify:
$$\mathbf A(\mathbf x + \mathbf 1) = \mathbf 0$$
using $\mathbf A \mathbf x = \mathbf 0$ and the properties of linear transformations, which are:
$$\begin{cases}\mathbf A(\mathbf a + \mathbf b) = \mathbf A \mathbf a + \mathbf A \mathbf b \\ \mathbf A (\lambda \mathbf a) = \lambda (\mathbf A \mathbf a)\end{cases}$$
 
  • #5
Oh...

A=0 ?
 
  • #6
Yankel said:
Oh...

A=0 ?

Huh? No, I'm afraid not. At least not necessarily. :confused:

What I mean is if you can get rid of the parentheses in $\mathbf A(\mathbf x+ \mathbf 1) = \mathbf 0$? Then we'll see what we can deduce from that...
 
  • #7
you get:

Ax+A=0

but isn't Ax=0 ?
 
  • #8
Yankel said:
you get:

Ax+A=0

but isn't Ax=0 ?

$A \mathbf x$ is indeed $\mathbf 0$, but your equation should be:
$$A \mathbf x + A \mathbf 1 = \mathbf 0$$
Note that $A \mathbf 1$ actually means:
$$A \mathbf 1 = A \begin{bmatrix}1\\1\\1\end{bmatrix}$$
which is different from A.
 
  • #9
this is the answer ? it's a solution only if

A1=0 ? if (1,1,1) is a solution ?
 
  • #10
Yankel said:
this is the answer ? it's a solution only if

A1=0 ? if (1,1,1) is a solution ?

Yep! (Nod)

So we can say that $\mathbf x + \mathbf 1$ will generally not be a solution, unless (1,1,1) is a solution.

I guess that should suffice to answer the question, although we can say a little more.

It means that (1,1,1) must be an eigenvector with eigenvalue 0.
And we know that $\mathbf x$ is also an eigenvector with eigenvalue 0.
However, the one does not have to be a multiple of the other, since a 3-dimensional matrix can have more than 1 eigenvector with eigenvalue 0. (Nerd)
 
  • #11
Thanks !
 

FAQ: Is a Shifted Solution Still Valid?

What is a linear combination of solutions?

A linear combination of solutions refers to the process of adding two or more solutions together to form a new solution. This is commonly used in mathematical equations, where the sum of two or more solutions can help to find the solution to a larger problem.

How is a linear combination of solutions calculated?

To calculate a linear combination of solutions, you simply add the coefficients of each solution together. For example, if you have two solutions, x and y, the linear combination would be ax + by, where a and b are the coefficients. The values of a and b can vary depending on the specific problem.

Why is a linear combination of solutions important?

Linear combinations of solutions are important because they allow us to simplify complex problems by breaking them down into smaller, more manageable solutions. They also help us to find a general solution to a problem, rather than just a specific solution for a given set of parameters.

Can a linear combination of solutions have an infinite number of solutions?

Yes, a linear combination of solutions can have an infinite number of solutions. This is because there are infinitely many ways to combine two or more solutions, and the coefficients used can also vary infinitely.

How is a linear combination of solutions used in real-world applications?

Linear combinations of solutions are used in many real-world applications, such as in engineering and physics. They can be used to model and solve problems involving multiple variables, such as in systems of equations. They are also used in data analysis, where multiple factors are combined to find a solution or pattern.

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