A real square matrix is orthogonal when , equivalently . For and ,
Thus is orthogonal for every allowed angle, and indeed for every real angle.
Using orthogonality,
Both norms are nonnegative, so taking square roots proves
Thus an orthogonal matrix is a Euclidean isometry fixing the origin.
The columns outside indices are unchanged coordinate vectors. The remaining two columns have nonzero entries only in rows , with the block . They have squared norm and mutual inner product zero; they are also orthogonal to all the unchanged columns. Hence .
Let . If , choose with and . Then
Every other coordinate is unchanged. If , choose ; the same conclusions hold. Therefore the procedure can be fixed with the nonnegative pivot convention
This is a Givens rotation.
Write for the actual successive rotations , , and , each selected using the currently transformed matrix. The first eliminates position ; the second eliminates while leaving row two unchanged. After these, the first column is . The final rotation of rows two and three preserves both zeros in that column and eliminates . Hence
A lower-triangular starting matrix does not force any further zeros above the diagonal. For example, the lower-triangular matrix with all entries on and below its diagonal equal to one gives, with the nonnegative pivot convention,
which has all upper-triangular entries nonzero.
Inverting the product of rotations yields the QR factorization
The order reverses when taking the transpose. If is orthogonal, then is both orthogonal and upper triangular. Its first column forces and orthogonality with the other columns forces . Applying the same argument to the remaining block makes diagonal with entries of modulus one.
Our elimination rule makes and positive when nonzero, so they are both one. Every rotation has determinant one; thus and
Without a fixed pivot-sign convention one could only specify a diagonal sign matrix. The convention chosen in part (c) determines the precise signs above.

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