Linear optical quantum computing

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In mathematics, in linear algebra, a cyclic subspace is a certain special subspace of a finite-dimensional vector space associated with a vector in the vector space and a linear transformation of the vector space. The cyclic subspace associated with a vector v in a vector space V and a linear transformation T of V is called the T-cyclic subspace generated by v. The concept of a cyclic subspace is a basic component in the formulation of the cyclic decomposition theorem in linear algebra.

Definition

Let T:VV be a linear transformation of a vector space V and let v be a vector in V. The T-cyclic subspace of V generated by v is the subspace W of V generated by the set of vectors {v,T(v),T2(v),,Tr(v),}. This subspace is denoted by Z(v;T). If V=Z(v;T), then v is called a cyclic vector for T.[1]

There is another equivalent definition of cyclic spaces. Let T:VV be a linear transformation of a finite dimensional vector space over a field F and v be a vector in V. The set of all vectors of the form g(T)v, where g(x) is a polynomial in the ring F[x] of all polynomials in x over F, is the T-cyclic subspace generated by v.[1]

Examples

  1. For any vector space V and any linear operator T on V, the T-cyclic subspace generated by the zero vector is the zero-subspace of V.
  2. If I is the identity operator then every I-cyclic subspace is one-dimensional.
  3. Z(v;T) is one-dimensional if and only if v is a characteristic vector of T.
  4. Let V be the two-dimensional vector space and let T be the linear operator on V represented by the matrix [0100] relative to the standard ordered basis of V. Let v=[01]. Then Tv=[10],T2v=0,,Trv=0,. Therefore {v,T(v),T2(v),,Tr(v),}={[01],[10]} and so Z(v;T)=V. Thus v is a cyclic vector for T.

Companion matrix

Let T:VV be a linear transformation of a ndimensional vector space V over a field F and v be a cyclic vector for T. Then the vectors

B={v1=v,v2=Tv,v3=T2v,vn=Tn1v}

form an ordered basis for V. Let the characteristic polynomial for T be

p(x)=c0+c1x+c2x2++cn1xn1+xn.

Then

Tv1=v2Tv2=v3Tv3=v4Tvn1=vnTvn=c0v1c1v2cn1vn

Therefore, relative to the ordered basis B, the operator T is represented by the matrix

[0000c01000c10100c20001cn1]

This matrix is called the companion matrix of the polynomial p(x).[1]

See also

External links

References

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