To find the vector in W that is closest to v, we can use the orthogonal projection formula:
proj_w(v) = ((v · u1)/(u1 · u1))u1 + ((v · u2)/(u2 · u2))u2 + ((v · u3)/(u3 · u3))u3
Where u1, u2, and u3 are the basis vectors for W.
First, we need to find the dot products of v with each of the basis vectors:
v · u1 = (1,0,0,-1) · (1,0,-1,0) = 1
v · u2 = (1,0,0,-1) · (0,-1,0,1) = -1
v · u3 = (1,0,0,-1) · (2,1,-3,0) = 2
Next, we need to find the dot products of each basis vector with itself:
u1 · u1 = (1,0,-1,0) · (1,0,-1,0) = 2
u2 · u2 = (0,-1,0,1) · (0,-1,0,1) = 2
u3 · u3 = (2,1,-3,0) · (2,1,-3,0) = 14
Now we can plug these values into the projection formula:
proj_w(v) = (1/2)(1,0,-1,0) + (-1/2)(0,-1,0,1) + (2/14)(2,1,-3,0)
= (1/2, 0, -1/2, 0) + (0, 1/2, 0, -1/2) + (4/14, 2/14, -6/14, 0)
= (7/14, 1/2, -7/14, -1/2)
Therefore, the vector in W that is closest to v is (7/14, 1/2, -7/14, -1/2).
This can also be verified by finding the distance between v and each vector in W and choosing the vector with the smallest distance. The distance formula is given by:
d(v, w) = ||v - w|| =