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Discovery guide 37.1 Discovery guide

Recall that two vectors \(\uvec{u},\uvec{v}\) in \(\R^n\) are called orthogonal if \(\udotprod{u}{v} = 0\text{.}\)
In analogy with this, we will also call two vectors \(\uvec{u},\uvec{v}\) in an inner product space orthogonal if \(\uvecinprod{u}{v} = 0\text{.}\)
Suppose \(V\) in an inner product space, and \(U\) is a subspace of \(V\text{.}\) The collection of all vectors orthogonal to \(U\) is called the orthogonal complement of \(U\text{,}\) and is denoted \(\orthogcmp{U}\text{.}\) That is, \(\orthogcmp{U}\) consists of all vectors that are orthogonal to every vector in \(U\text{.}\)

Discovery 37.1.1.

Suppose \(V = \R^3\) with the usual Euclidean inner product (the dot product). Then orthogonal is the same as perpendicular.
Note. In the first two tasks, keep in mind that if a directed line segment is translated, the vector associated to the translated segment is equal to the vector associated to the original segment.

(a)

Describe \(\orthogcmp{U}\) if \(U\) is a plane through the origin.

(b)

Describe \(\orthogcmp{W}\) if \(W\) is a line through the origin.

(c)

Based on your two answers, make a general conjecture about \(\orthogcmp{(\orthogcmp{U})}\) in an inner product space.

Discovery 37.1.2.

Suppose \(U = \Span \{\uvec{u}_1,\uvec{u}_2,\uvec{u}_3\}\) is a subspace of an inner product space \(V\text{.}\) Convince yourself that a vector \(\uvec{v}\) is in \(\orthogcmp{U}\) if and only if \(\uvec{v}\) is orthogonal to each of \(\uvec{u}_1,\uvec{u}_2,\uvec{u}_3\text{.}\)
Careful. Make sure you are considering the word Span in the definition of \(U\text{.}\)
Since \(\orthogcmp{U}\) is defined by a homogeneous condition (inner product equals \(0\)), we expect it to be a subspace. The orthogonality condition can be used to determine a basis for \(\orthogcmp{U}\text{.}\)

Discovery 37.1.3.

Consider \(V = \matrixring_{2 \times 2}(\R)\) as an inner product space with \(\inprod{A}{B} = \trace(\utrans{B} A)\text{.}\) Let \(U\) represent the subspace of every upper triangular matrix whose upper-right entry is equal to its trace.

(a)

Determine a basis for \(U\text{.}\)
Hint.
Describe a typical element in \(U\) using parameters, then associate a basis vector to each independent parameter.
A set of vectors in an inner product space is called an orthogonal set if each vector in the set is orthogonal to every other vector in the set. A set of vectors is called an orthonormal set if it is an orthogonal set where every member is a unit vector.
Geometrically we think of linearly independent vectors as β€œpointing in different directions,” so it is reasonable to expect an orthogonal set of vectors to be independent.

Discovery 37.1.4.

Suppose \(\{ \uvec{v}_1, \uvec{v}_2, \uvec{v}_3 \}\) is an orthogonal set of nonzero vectors in an inner product space. To test for independence, we start with the homogeneous vector equation
\begin{equation} k_1 \uvec{v}_1 + k_2 \uvec{v}_2 + k_3 \uvec{v}_3 = \zerovec\text{.}\tag{✢} \end{equation}

(a)

From our initial equation (✢), we have
\begin{equation*} \inprod{k_1 \uvec{v}_1 + k_2 \uvec{v}_2 + k_3 \uvec{v}_3}{\uvec{v}_1} = \inprod{\zerovec}{\uvec{v}_1}\text{.} \end{equation*}
Simplify the left-hand side of this equality to discover something about \(k_1\text{.}\)

(b)

Convince yourself that similar reasoning will work for \(k_2,k_3\text{.}\)

(c)

Is \(\{ \uvec{v}_1, \uvec{v}_2, \uvec{v}_3 \}\) an independent set?

Discovery 37.1.5.

Suppose \(\basisfont{B} = \{\uvec{e}_1,\uvec{e}_2,\uvec{e}_3\}\) is both a basis and an orthogonal set in an inner product space \(V\text{.}\) Since \(\basisfont{B}\) is a basis, every vector \(\uvec{v}\) in \(V\) has a unique expression
\begin{equation} \uvec{v} = k_1 \uvec{e}_1 + k_2 \uvec{e}_2 + k_3 \uvec{e}_3\tag{✢✢} \end{equation}
for some scalars \(k_1,k_2,k_3\text{.}\)

(a)

Substitute (✢✢) into \(\inprod{\uvec{v}}{\uvec{e}_1}\) to obtain an expression for \(\inprod{\uvec{v}}{\uvec{e}_1}\) in terms of the \(k_j\) and \(\uvec{e}_j\text{.}\) Then isolate \(k_1\text{.}\)

(b)

Similar to Task (a), use (✢✢) in \(\inprod{\uvec{v}}{\uvec{e}_2}\) to obtain a formula for \(k_2\text{,}\) and in \(\inprod{\uvec{v}}{\uvec{e}_3}\) to obtain a formula for \(k_3\text{.}\)

(c) Identify the pattern.

If \(V\) has dimension \(n\) (instead of dimension \(3\)), then the coordinates of a vector \(\uvec{v}\) relative to an orthogonal basis \(\basisfont{B} = \{\uvec{e}_1,\uvec{e}_2,\dotsc,\uvec{e}_n\}\) are .
A basic problem in an inner product space is how to come up with an orthogonal basis. So let’s invent a procedure for doing so.

Discovery 37.1.6.

To keep it simple, let’s suppose \(V\) has dimension \(3\text{.}\) The beginning ingredient for our procedure is some (probably nonorthogonal) basis \(\basisfont{B}_0 = \{\uvec{v}_1,\uvec{v}_2,\uvec{v}_3\}\text{,}\) and the end result should be some definitely orthogonal basis \(\basisfont{B} = \{\uvec{e}_1,\uvec{e}_2,\uvec{e}_3\}\text{.}\)
To get the process started, we might as well first choose \(\uvec{e}_1 = \uvec{v}_1\text{,}\) since we don’t yet have any other \(\uvec{e}_j\) vectors chosen yet to which \(\uvec{e}_1\) needs to be orthogonal.
The rest of the activity requires us to choose \(\uvec{e}_2,\uvec{e}_3\) to complete the orthogonal basis.

(a)

If we already knew the answer \(\basisfont{B} = \{\uvec{e}_1,\uvec{e}_2,\uvec{e}_3\}\text{,}\) and we expanded \(\uvec{v}_2 = k_1\uvec{e}_1 + k_2 \uvec{e}_2 + k_3 \uvec{e}_3\) relative to \(\basisfont{B}\text{,}\) what would the coefficient \(k_1\) be?
Hint.
We already considered this sort of question in DiscoveryΒ 37.1.5 above.

(b)

Draw a diagram of \(\uvec{v}_2\text{,}\) \(\uvec{e}_1\text{,}\) and \(k_1 \uvec{e}_1\) as if these were vectors in \(\R^n\text{,}\) keeping in mind that \(k_1 \uvec{e}_1\) should be exactly that part of \(\uvec{v}_2\) that is parallel to \(\uvec{e}_1\text{.}\) (Does this diagram remind you of some previous concept?)
Use your diagram to propose a choice of vector \(\uvec{e}_2\) that is orthogonal to \(\uvec{e}_1\text{.}\)

(c)

Carry out a similar exploration process as in TaskΒ (a) and TaskΒ (b), but for \(\uvec{v}_3\text{.}\)

(i)

For expansion \(\uvec{v}_3 = k_1\uvec{e}_1 + k_2\uvec{e}_2 + k_3\uvec{e}_3\) relative to \(\basisfont{B}\text{,}\) what would be the coordinates \(k_1\) and \(k_2\text{?}\)

(ii)

Draw a diagram of \(\uvec{v}_3\text{,}\) \(\uvec{e}_1\text{,}\) \(\uvec{e}_2\text{,}\) and \(k_1 \uvec{e}_1 + k_2\uvec{e}_2\text{,}\) keeping in mind that \(k_1 \uvec{e}_1 + k_2\uvec{e}_2\) should be exactly that part of \(\uvec{v}_3\) that is β€œparallel” to \(\Span\{\uvec{e}_1,\uvec{e}_2\}\text{.}\)
Use your diagram to propose a choice of vector \(\uvec{e}_3\) that is orthogonal to both \(\uvec{e}_1\) and \(\uvec{e}_2\text{.}\)

(d) Identify the pattern.

If \(V\) has dimension \(n\) (instead of dimension \(3\)), then the next step in the procedure would be
\begin{equation*} \uvec{e}_4 = \fillinmath{XXXXXXXXXXXXXXXXXXXX} \text{.} \end{equation*}
And then
\begin{equation*} \uvec{e}_5 = \fillinmath{XXXXXXXXXXXXXXXXXXXX} \text{.} \end{equation*}
And so on.

(e)

At the end of all this, what would you do if you wanted an orthonormal basis for \(V\text{?}\)

Discovery 37.1.7.

What do you think the result would be if you unknowingly applied the procedure of DiscoveryΒ 37.1.6 to a starting basis \(\basisfont{B}_0\) that was already orthogonal?

Discovery 37.1.8.

Suppose \(U\) is a subspace of an inner product space \(V\text{.}\)

(b)

Every basis for \(U\) can be enlarged to a basis for \(V\) (StatementΒ 1 of PropositionΒ 20.5.8).
Suppose
\begin{equation*} \basisfont{B}_0 = \{ \uvec{u}_1, \dotsc, \uvec{u}_m, \uvec{v}_1, \dotsc, \uvec{v}_\ell \} \end{equation*}
is such an enlarged basis for \(V\text{,}\) so that the \(\uvec{u}_j\) form a basis for \(U\text{.}\) If we apply the procedure of DiscoveryΒ 37.1.6 to \(\basisfont{B}_0\) to obtain orthgonal basis
\begin{equation*} \basisfont{B} = \{ \uvec{e}_1, \dotsc, \uvec{e}_m, \uvec{f}_1, \dotsc, \uvec{f}_\ell \} \end{equation*}
for \(V\text{,}\) what subspace do the \(\uvec{f}_j\) span?