Finding Orthogonal Vectors in R4 with Norm 1

In summary, Homework Equations The Attempt at a Solution found three equations in four unknowns that yielded the ratios x_2/x1, x_3/x1, and x_4/x1.
  • #1
sevag00
80
1

Homework Statement



Find two vectors in R4 of norm 1 that are orthogonal to the vectors u = (2, 1, −4, 0),
v = (−1, −1, 2, 2) and w = (3, 2, 5, 4).

Homework Equations





The Attempt at a Solution



What i did was, i let a vector x = (x1, x2, x3, x4) that has a norm of 1 and orthogonal to u,v and w
i.e. x.u = 0; x.v = 0 and x.w = 0.
This where I'm stuck. Some help would be appreciated. Thanks.
 
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  • #2
hi sevag00! :smile:

(try using the X2 button just above the Reply box :wink:)

hint: how would you find a vector (x1,x2,x3) orthogonal to (a,b,c) and (d,e,f) ? :wink:
 
  • #3
Using dot product. x1.a + x2.b + x3.c = 0. Same for (d, e, f).
 
  • #5
Yeah, but the chapter only explains the dot product. So, i think the problem should be solved using dot product.
 
Last edited:
  • #6
ok, in that case you have three simultaneous equations (from the dot products) …

solve them the usual way :smile:
 
  • #7
3 equations with 4 unknowns. Will this yield a solution?
 
  • #8
3 equations with 3 unknown ratios :wink:

so yes, you can find the ratios :smile:
 
  • #9
Ah yes. 4 equations with 4 unknowns.
 
  • #10
tiny-tim said:
how about the cross product ? :wink:

sevag00 said:
Yeah, but the chapter only explains the dot product. So, i think the problem should be solved using dot product.
Further, the cross product is defined only in three dimensions while this problem is in four dimensions.
 
  • #11
Wait a minute. You got me confused. There are 3 equations with 4 unknown. The equation of the norm cannot be included with the other three.
 
  • #12
HallsofIvy said:
Further, the cross product is defined only in three dimensions …

i was talking about three dimensions
sevag00 said:
There are 3 equations with 4 unknown. The equation of the norm cannot be included with the other three.

there are only three unknown ratios

so you can find the ratios
 
  • #13
What ratios? I want to find the components of x.
 
  • #14
x2/x1, x3/x1, x4/x1
 
  • #15
Not getting your approach.
 
  • #16
divide your three dot-product=0 equations by x1

that gives you three equations in x2/x1, x3/x1, and x4/x1

then solve them :smile:
 
  • #17
I think i did it right. I replaced x2/x1 with X x3/x1 with Y and x4/x1 with Z. Then solved 3 equations with 3 unknowns.
 
  • #18
sevag00 said:

Homework Statement



Find two vectors in R4 of norm 1 that are orthogonal to the vectors u = (2, 1, −4, 0),
v = (−1, −1, 2, 2) and w = (3, 2, 5, 4).

Homework Equations





The Attempt at a Solution



What i did was, i let a vector x = (x1, x2, x3, x4) that has a norm of 1 and orthogonal to u,v and w
i.e. x.u = 0; x.v = 0 and x.w = 0.
This where I'm stuck. Some help would be appreciated. Thanks.

You can write the three equations in four unknowns as three equations in three unknowns but with the fourth unknown on the right-hand-side. In other words, you can express three of the x_i as functions of the fourth. For example, you can write the second equation ##-1 x_1 - 1 x_2 + 2 x_3 + 2 x_4 = 0## as ##-1 x_1 - 1 x_2 + 2 x_3 = -2 x_4##, or ##x_1 + x_2 - 2x_3 = 2x_4##. Do the same thing for the third equation; the first already has the right form. Now you can solve for ##x_1, x_2, x_3##; this will give them as formulas involving ##x_4##.

BTW: the method above is a standard way of dealing with such problems; it is used all the time in such fields as linear optimization (linear programming).
 
  • #19
I know that method. But then those equations will become parameters. They will depend on the value of x4 which has infinite solutions.
 
  • #20
sevag00 said:
I know that method. But then those equations will become parameters. They will depend on the value of x4 which has infinite solutions.

Of course; that is the whole point. So, if you want to find two different solutions, just give two different values for ##x_4##---any two values you like, except 0. (Putting ##x_4 = 0## gives the zero vector, which cannot be normalized to length = 1!)
 
  • #21
I want direct solution for the x-es. I'm not going to plug in millions of values to see if the norm is 1.
 
  • #22
put x4 = 1, then normalise it
 
  • #23
sevag00 said:
I want direct solution for the x-es. I'm not going to plug in millions of values to see if the norm is 1.

You have completely misunderstood what some of us have been saying. First find two vectors that satisfy the perpendicularity conditions. THEN normalize them.

For example, if I start with a vector like ##v = (1,2,3,4)## I can get a normalized version as
[tex]u = \frac{v}{\text{norm of }v}[/tex]
If v was perpendicular to some vector w then so is u, and u has norm 1. That's all there is to it.
 

1. What is the definition of orthogonal vectors in R4?

Orthogonal vectors in R4 are four-dimensional vectors that are perpendicular to each other, meaning they form a 90-degree angle at their intersection.

2. How can I find orthogonal vectors in R4?

To find orthogonal vectors in R4, you can use the Gram-Schmidt process, which involves taking a set of linearly independent vectors and creating a new set of orthogonal vectors through a series of calculations.

3. What is the importance of norm 1 in finding orthogonal vectors in R4?

Norm 1, also known as the L1 norm, is used in finding orthogonal vectors in R4 because it helps to determine the magnitude or length of a vector. In this case, we are looking for orthogonal vectors with a norm of 1, which means they have a length of 1 unit.

4. Can I find orthogonal vectors in R4 with a norm other than 1?

Yes, it is possible to find orthogonal vectors in R4 with a norm other than 1. However, the process for finding them will be different as it will involve scaling the vectors to achieve the desired norm.

5. What are the real-world applications of finding orthogonal vectors in R4 with norm 1?

Finding orthogonal vectors in R4 with norm 1 has various applications in fields such as computer graphics, signal processing, and data analysis. It can be used to create 3D images, filter signals, and reduce data dimensionality, among other things.

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