Is This a Valid Vector Space with Unusual Operations?

In summary, this vector space has a zero vector, additive inverses, associativity, and closure. However, it does not obey the distributive law.
  • #1
karush
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On the set of vectors
$\begin{bmatrix}
x_1 \\ y_1
\end{bmatrix}\in \Bbb{R}^2 $
with $x_1 \in \Bbb{R}$, and $y_1$ in $\Bbb{R}^{+}$ (meaning $y_1 >0$) define an addition by
$$\begin{bmatrix}
x_1 \\ y_1
\end{bmatrix} \oplus
\begin{bmatrix}
x_2 \\ y_2
\end{bmatrix}
=
\begin{bmatrix}
x_1 + x_2 \\ y_1y_2
\end{bmatrix}$$
and a scalar multiplication by
$$ k \odot
\begin{bmatrix}
x \\ y
\end{bmatrix} =
\begin{bmatrix}
k x \\ y^{k}
\end{bmatrix}.
$$
Determine if this is a vector space.
If it is, make sure to explicitly state what the $0$ vector is.
OK the only the only thing I could come up with was $2+2=4$ and $2\cdot 2=4$
and zero vectors are orthogonal with $k=2$
 
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  • #2
karush said:
On the set of vectors
$\begin{bmatrix}
x_1 \\ y_1
\end{bmatrix}\in \Bbb{R}^2 $
with $x_1 \in \Bbb{R}$, and $y_1$ in $\Bbb{R}^{+}$ (meaning $y_1 >0$) define an addition by
$$\begin{bmatrix}
x_1 \\ y_1
\end{bmatrix} \oplus
\begin{bmatrix}
x_2 \\ y_2
\end{bmatrix}
=
\begin{bmatrix}
x_1 + x_2 \\ y_1y_2
\end{bmatrix}$$
and a scalar multiplication by
$$ k \odot
\begin{bmatrix}
x \\ y
\end{bmatrix} =
\begin{bmatrix}
k x \\ y^{k}
\end{bmatrix}.
$$
Determine if this is a vector space.
If it is, make sure to explicitly state what the $0$ vector is.
OK the only the only thing I could come up with was $2+2=4$ and $2\cdot 2=4$
and zero vectors are orthogonal with $k=2$
"zero vectors?" There's only one.

I've got closure, associativity, a zero vector, additive inverses, and it's even commutative. However it doesn't obey the distributive law.

Can you get these?

-Dan
 
  • #3
ok I don't know how you would try the distributive property since the scalar was different
Distributive law: For all real numbers c and all vectors $u, v \in V$, $ c\cdot(u + v) = c\cdot u + c\cdot v$
 
  • #4
karush said:
ok I don't know how you would try the distributive property since the scalar was different
Distributive law: For all real numbers c and all vectors $u, v \in V$, $ c\cdot(u + v) = c\cdot u + c\cdot v$
I had this whole blasted thing written out in LaTeX just to find out I made an error. The distributive law also works.

Here it is anyway.

\(\displaystyle k \odot \left ( \left [ \begin{matrix} x_1 \\ y_1 \end{matrix} \right ] \oplus \left [ \begin{matrix} x_2 \\ y_2 \end{matrix} \right ] \right )
= \left ( k \odot \left [ \begin{matrix} x_1 \\ y_1 \end{matrix} \right ] \right ) \oplus \left ( k \odot \left [ \begin{matrix} x_2 \\ y_2 \end{matrix} \right ] \right ) = \left [ \begin{matrix} kx_1 \\ y_1^k \end{matrix} \right ] \oplus \left [ \begin{matrix} kx_2 \\ y_2^k \end{matrix} \right ] = \left [ \begin{matrix} kx_1 + kx_2 \\ y_1^k y_2^k \end{matrix} \right ]\)

\(\displaystyle k \odot \left ( \left [ \begin{matrix} x_1 \\ y_1 \end{matrix} \right ] \oplus \left [ \begin{matrix} x_2 \\ y_2 \end{matrix} \right ] \right ) = k \odot \left [ \begin{matrix} x_1 + x_2 \\ y_1 y_2 \end{matrix} \right ] = \left [ \begin{matrix} k(x_1 + x_2 ) \\ (y_1 y_2)^k \end{matrix} \right ] \)

So they are the same.

-Dan
 
  • #5
The 0 vector (additive identity) is $\begin{bmatrix}0 \\ 1\end{bmatrix}$: for any vector $v= \begin{bmatrix}a \\ b\end{bmatrix}$, $v+ 0= 0+ v= \begin{bmatrix}a+ 0 \\ b(1)\end{bmatrix}= \begin{bmatrix}a \\ b\end{bmatrix}= v$.

What about the additive inverse of $\begin{bmatrix}a \\ b\end{bmatrix}$? Calling that $\begin{bmatrix}p \\ q\end{bmatrix}$, We must have $\begin{bmatrix}a \\ b\end{bmatrix}+ \begin{bmatrix}p \\ q \end{bmatrix}= \begin{bmatrix}a+ p \\ bq \end{bmatrix}= \begin{bmatrix} 0 \\ 1\end{pmatrix}$ so we have a+ p= 0 and bq= 1 so we must have p= -a and q= 1/b. That is the reason for the condition "y> 0".
 
  • #6
That was a great help ..
Much Mahalo

It hard to find really good help with these
 

FAQ: Is This a Valid Vector Space with Unusual Operations?

What is a vector space?

A vector space is a mathematical structure that consists of a set of vectors and operations that can be performed on those vectors. These operations include addition and scalar multiplication, and they must follow certain properties to be considered a vector space.

How do you determine if a set is a vector space?

To determine if a set is a vector space, you must check if it satisfies the 10 axioms or properties of a vector space. These properties include the existence of a zero vector, closure under addition and scalar multiplication, and the existence of additive and multiplicative inverses for each vector.

What are the properties of a vector space?

The properties of a vector space include the existence of a zero vector, closure under addition and scalar multiplication, associativity and commutativity of addition, distributivity of scalar multiplication over addition, and the existence of additive and multiplicative inverses for each vector.

Can a set be a vector space if it does not have a zero vector?

No, a set cannot be a vector space if it does not have a zero vector. The zero vector is a necessary property of a vector space and without it, the set would not satisfy all of the axioms of a vector space.

Is every set of vectors a vector space?

No, not every set of vectors is a vector space. To be considered a vector space, a set must satisfy all of the axioms or properties of a vector space. If even one of these properties is not satisfied, the set cannot be considered a vector space.

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