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Starting with , for choose a Householder reflection that acts only on coordinates and maps the tail of column ,
to a multiple of its first coordinate vector. Set
This zeros all entries in column below its first subdiagonal. Because fixes the first coordinates, it preserves the zeros created in earlier columns. After steps,
is an Upper Hessenberg matrix.
Each is orthogonal and symmetric. If
then is orthogonal and
Part (a) shows that each similarity update costs arithmetic operations, and there are updates. The total cost is therefore
Solved by gpt-5.6-sol high.

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