Undergrad Finding a linear combination to enter a sphere

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The discussion revolves around finding a linear combination of n vectors in ℝ3 that results in a sum lying within a defined sphere of radius r centered at a point P. The least squares method is suggested as a potential approach, assuming the use of the standard 2-norm metric. The conversation highlights the importance of orthogonality and orthonormality, defining mutually orthonormal vectors as those that are both at right angles and of unit length. It is established that to ensure the sum of the selected vectors remains within the sphere, the condition involving their coefficients must satisfy the inequality related to the radius. Additionally, it is noted that in ℝ3, the maximum number of mutually orthonormal vectors is limited to three due to linear independence constraints.
johann1301h
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Let's say we have n vectors in ℝ3. And say we have defined a subspace inside ℝ3 in the form of a sphere with radius r, and the center of the spheare is at P, where P is a vector in ℝ3.

What methods exists to find any linear combination of the n vectors, so that the sum of all of them, lies within the sphere?

F. ex i have hear of something called least squares. Can that be used for this?
 
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assuming we are using the standard metric / 2norm here, then yes there are nice ways to do this.

First, for now, assume p is the zero vector. Do you know what orthogonality is? And in particular, do you know the term 'orthonormal'?
 
orthogonality: 90 degrees, orthonormal: 90 degrees and length = 1unit ?
 
johann1301h said:
orthogonality: 90 degrees, orthonormal: 90 degrees and length = 1unit ?
yes. and the standard case here is we select two vector in ##\{\mathbf x_1, \mathbf x_2, \mathbf x_3\}## and take the dot product (which is the standard inner product in reals). These vectors are mutually orthonormal iff
##\mathbf x_j^T \mathbf x_k= 1## if ##j = k## and ##=0## if ##j \neq k##

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what does this have to do with your problem? still with ##\mathbf p =\mathbf 0##, you want to select say ##m## of these mutually orthonormal vectors where

##\big \Vert \sum_{i=1}^m \alpha_i \mathbf x\big \Vert_2 \leq r##
or
##\big \Vert \sum_{i=1}^m \alpha_i \mathbf x\big \Vert_2^2 \leq r^2##

this is equivalent to
## \sum_{i=1}^m \alpha_i^2 \leq r^2##

Confirm that this makes sense
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edit:
for avoidance of doubt, mutually orthonormal implies mutually linearly independent, so in ##\mathbb R^3## it must be the case that ##m\leq 3##, because you cannot have more than 3 linearly independent vectors when your dimension is 3.
 
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