Self-adjoint operator: Difference between revisions

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In [[mathematics]], a '''self-adjoint operator''' is a [[denseness|densely]] defined [[linear operator]] mapping a complex Hilbert space onto itself and which is invariant under the unary operation of taking the [[adjoint (operator)|adjoint]]. That is, if <math>A</math> is an operator with a domain <math>H_0</math> which is a dense subspace of a complex Hilbert space <math>H</math> then it is self-adjoint if <math>A=A^*</math>, where <math>^*</math> denotes the adjoint. Note that the adjoint of any densely defined linear operator is always well-defined and two operators ''A'' and ''B'' are said to be equal if they have a common domain and their values coincide on that domain.
In [[mathematics]], a '''self-adjoint operator''' is a [[denseness|densely]] defined [[linear operator]] mapping a complex Hilbert space onto itself and which is invariant under the unary operation of taking the [[adjoint (operator)|adjoint]]. That is, if <math>A</math> is an operator with a domain <math>H_0</math> which is a dense subspace of a complex Hilbert space <math>H</math> then it is self-adjoint if <math>A=A^*</math>, where <math>^*</math> denotes the adjoint. Note that the adjoint of any densely defined linear operator is always well-defined and two operators ''A'' and ''B'' are said to be equal if they have a common domain and their values coincide on that domain.
   
   

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In mathematics, a self-adjoint operator is a densely defined linear operator mapping a complex Hilbert space onto itself and which is invariant under the unary operation of taking the adjoint. That is, if is an operator with a domain which is a dense subspace of a complex Hilbert space then it is self-adjoint if , where denotes the adjoint. Note that the adjoint of any densely defined linear operator is always well-defined and two operators A and B are said to be equal if they have a common domain and their values coincide on that domain.

On an infinite dimensional Hilbert space, a self-adjoint operator can be thought of as the analogy of a real symmetric matrix (i.e., a matrix which is its own transpose) or a Hermitian matrix in (i.e., a matrix which is its own Hermitian transpose) when these matrices are viewed as (bounded) linear operators on and , respectively.

References

  1. K. Yosida, Functional Analysis (6 ed.), ser. Classics in Mathematics, Berlin, Heidelberg, New York: Springer-Verlag, 1980