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Compression (functional analysis)
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In [[functional analysis]], the '''compression''' of a [[linear operator]] ''T'' on a [[Hilbert space]] to a [[Linear subspace|subspace]] ''K'' is the operator :<math>P_K T \vert_K : K \rightarrow K </math>, where <math>P_K : H \rightarrow K</math> is the [[orthogonal projection]] onto ''K''. This is a natural way to obtain an operator on ''K'' from an operator on the whole Hilbert space. If ''K'' is an [[invariant subspace]] for ''T'', then the compression of ''T'' to ''K'' is the [[restriction (mathematics)|restricted]] operator ''K→K'' sending ''k'' to ''Tk''. More generally, for a linear operator ''T'' on a Hilbert space <math>H</math> and an [[isometry]] ''V'' on a subspace <math>W</math> of <math>H</math>, define the '''compression''' of ''T'' to <math>W</math> by :<math>T_W = V^*TV : W \rightarrow W</math>, where <math>V^*</math> is the [[hermitian adjoint|adjoint]] of ''V''. If ''T'' is a [[self-adjoint operator]], then the compression <math>T_W</math> is also self-adjoint. When ''V'' is replaced by the [[inclusion map]] <math>I: W \to H</math>, <math>V^* = I^*=P_K : H \to W</math>, and we acquire the special definition above. ==See also== * [[Dilation (operator theory)|Dilation]] ==References== * P. Halmos, A Hilbert Space Problem Book, Second Edition, Springer-Verlag, 1982. [[Category:Functional analysis]] {{mathanalysis-stub}}
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