In linear algebra, the transpose of a linear map between two vector spaces, defined over the same field, is an induced map between the dual spaces of the two vector spaces.  The transpose or algebraic adjoint of a linear map is often used to study the original linear map. This concept is generalised by adjoint functors. 
  Definition
  Let  denote the algebraic dual space of a vector space 
 denote the algebraic dual space of a vector space  .  Let
.  Let  and
 and  be vector spaces over the same field 
 be vector spaces over the same field  .  If
.  If  is a linear map, then its algebraic adjoint or dual, is the map
 is a linear map, then its algebraic adjoint or dual, is the map  defined by 
 defined by  .  The resulting functional
.  The resulting functional  is called the pullback of
 is called the pullback of  by 
 by  .
. 
The continuous dual space of a topological vector space (TVS)  is denoted by 
 is denoted by  .  If
.  If  and
 and  are TVSs then a linear map
 are TVSs then a linear map  is weakly continuous if and only if 
 is weakly continuous if and only if  , in which case we let
, in which case we let  denote the restriction of
 denote the restriction of  to 
 to  .  The map
.  The map  is called the transpose or algebraic adjoint of 
 is called the transpose or algebraic adjoint of  .  The following identity characterizes the transpose of 
.  The following identity characterizes the transpose of  :[3]
:[3]   where
 where  is the natural pairing defined by 
 is the natural pairing defined by  .
. 
 Properties
 The assignment  produces an injective linear map between the space of linear operators from
 produces an injective linear map between the space of linear operators from  to
 to  and the space of linear operators from
 and the space of linear operators from  to 
 to  .  If
.  If  then the space of linear maps is an algebra under composition of maps, and the assignment is then an antihomomorphism of algebras, meaning that 
 then the space of linear maps is an algebra under composition of maps, and the assignment is then an antihomomorphism of algebras, meaning that  .  In the language of category theory, taking the dual of vector spaces and the transpose of linear maps is therefore a contravariant functor from the category of vector spaces over
.  In the language of category theory, taking the dual of vector spaces and the transpose of linear maps is therefore a contravariant functor from the category of vector spaces over  to itself.  One can identify
 to itself.  One can identify  with
 with  using the natural injection into the double dual.
 using the natural injection into the double dual. 
 - If  and and are linear maps then are linear maps then [4] [4]
- If  is a (surjective) vector space isomorphism then so is the transpose  is a (surjective) vector space isomorphism then so is the transpose  . .
- If  and and are normed spaces then are normed spaces then
 and if the linear operator
 and if the linear operator  is bounded then the operator norm of
 is bounded then the operator norm of  is equal to the norm of
 is equal to the norm of  ; that is
; that is  and moreover,
 and moreover,  
 
 Polars
 Suppose now that  is a weakly continuous linear operator between topological vector spaces
 is a weakly continuous linear operator between topological vector spaces  and
 and  with continuous dual spaces
 with continuous dual spaces  and 
 and  , respectively.  Let
, respectively.  Let  denote the canonical dual system, defined by
 denote the canonical dual system, defined by  where
 where  and
 and  are said to be orthogonal if 
 are said to be orthogonal if  .  For any subsets
.  For any subsets  and 
 and  , let
, let   denote the (absolute) polar of
  denote the (absolute) polar of  in
 in  (resp. of
 (resp. of  in
 in  ).
).  
 - If  and and are convex, weakly closed sets containing the origin then are convex, weakly closed sets containing the origin then implies  implies  . .
- If  and and then[4] then[4]
![{\displaystyle [u(A)]^{\circ }=\left({}^{\text{t}}\!u\right)^{-1}\left(A^{\circ }\right)}](./_assets_/1db150d9d7f27bbe512c9481394a982da016aa11.svg) and
 and  
 
 - If  and and are locally convex then are locally convex then
 
 
 Annihilators
 Suppose  and
 and  are topological vector spaces and
 are topological vector spaces and  is a weakly continuous linear operator (so 
 is a weakly continuous linear operator (so  ). Given subsets
). Given subsets  and 
 and  , define their annihilators (with respect to the canonical dual system) by
, define their annihilators (with respect to the canonical dual system) by 
  
and 
  
- The kernel of  is the subspace of is the subspace of orthogonal to the image of  orthogonal to the image of  : :
 
 
 - The linear map  is injective if and only if its image is a weakly dense subset of is injective if and only if its image is a weakly dense subset of (that is, the image of (that is, the image of is dense in is dense in when when is given the weak topology induced by  is given the weak topology induced by  ). ).
- The transpose  is continuous when both is continuous when both and and are endowed with the weak-* topology (resp. both endowed with the strong dual topology, both endowed with the topology of uniform convergence on compact convex subsets, both endowed with the topology of uniform convergence on compact subsets). are endowed with the weak-* topology (resp. both endowed with the strong dual topology, both endowed with the topology of uniform convergence on compact convex subsets, both endowed with the topology of uniform convergence on compact subsets).
- (Surjection of Fréchet spaces): If  and and are Fréchet spaces then the continuous linear operator are Fréchet spaces then the continuous linear operator is surjective if and only if (1) the transpose is surjective if and only if (1) the transpose is injective, and (2) the image of the transpose of is injective, and (2) the image of the transpose of is a weakly closed (i.e. weak-* closed) subset of  is a weakly closed (i.e. weak-* closed) subset of  . .
Duals of quotient spaces
 Let  be a closed vector subspace of a Hausdorff locally convex space
 be a closed vector subspace of a Hausdorff locally convex space  and denote the canonical quotient map by
 and denote the canonical quotient map by   Assume
 Assume  is endowed with the quotient topology induced by the quotient map 
 is endowed with the quotient topology induced by the quotient map  .  Then the transpose of the quotient map is valued in
.  Then the transpose of the quotient map is valued in  and
 and  is a TVS-isomorphism onto 
 is a TVS-isomorphism onto  .  If
.  If  is a Banach space then
 is a Banach space then  is also an isometry.  Using this transpose, every continuous linear functional on the quotient space
 is also an isometry.  Using this transpose, every continuous linear functional on the quotient space  is canonically identified with a continuous linear functional in the annihilator
 is canonically identified with a continuous linear functional in the annihilator  of 
 of  .
. 
 Duals of vector subspaces
 Let  be a closed vector subspace of a Hausdorff locally convex space 
 be a closed vector subspace of a Hausdorff locally convex space  .  If
.  If  and if
 and if  is a continuous linear extension of
 is a continuous linear extension of  to
 to  then the assignment
 then the assignment  induces a vector space isomorphism
 induces a vector space isomorphism   which is an isometry if
 which is an isometry if  is a Banach space.
 is a Banach space.  
Denote the inclusion map by  The transpose of the inclusion map is
 The transpose of the inclusion map is   whose kernel is the annihilator
 whose kernel is the annihilator  and which is surjective by the Hahn–Banach theorem. This map induces an isomorphism of vector spaces
 and which is surjective by the Hahn–Banach theorem. This map induces an isomorphism of vector spaces  
 
 Representation as a matrix
 If the linear map  is represented by the matrix
 is represented by the matrix  with respect to two bases of
 with respect to two bases of  and 
 and  , then
, then  is represented by the transpose matrix
 is represented by the transpose matrix  with respect to the dual bases of
 with respect to the dual bases of  and 
 and  , hence the name.  Alternatively, as
, hence the name.  Alternatively, as  is represented by
 is represented by  acting to the right on column vectors,
 acting to the right on column vectors,  is represented by the same matrix acting to the left on row vectors.  These points of view are related by the canonical inner product on 
 is represented by the same matrix acting to the left on row vectors.  These points of view are related by the canonical inner product on  , which identifies the space of column vectors with the dual space of row vectors.
, which identifies the space of column vectors with the dual space of row vectors. 
 Relation to the Hermitian adjoint
   The identity that characterizes the transpose, that is,  , is formally similar to the definition of the Hermitian adjoint, however, the transpose and the Hermitian adjoint are not the same map.  The transpose is a map
, is formally similar to the definition of the Hermitian adjoint, however, the transpose and the Hermitian adjoint are not the same map.  The transpose is a map  and is defined for linear maps between any vector spaces
 and is defined for linear maps between any vector spaces  and 
 and  , without requiring any additional structure.  The Hermitian adjoint maps
, without requiring any additional structure.  The Hermitian adjoint maps  and is only defined for linear maps between Hilbert spaces, as it is defined in terms of the inner product on the Hilbert space.  The Hermitian adjoint therefore requires more mathematical structure than the transpose.
 and is only defined for linear maps between Hilbert spaces, as it is defined in terms of the inner product on the Hilbert space.  The Hermitian adjoint therefore requires more mathematical structure than the transpose. 
However, the transpose is often used in contexts where the vector spaces are both equipped with a nondegenerate bilinear form such as the Euclidean dot product or another real inner product.  In this case, the nondegenerate bilinear form is often used implicitly to map between the vector spaces and their duals, to express the transposed map as a map  .  For a complex Hilbert space, the inner product is sesquilinear and not bilinear, and these conversions change the transpose into the adjoint map.
.  For a complex Hilbert space, the inner product is sesquilinear and not bilinear, and these conversions change the transpose into the adjoint map. 
More precisely: if  and
 and  are Hilbert spaces and
 are Hilbert spaces and  is a linear map then the transpose of
 is a linear map then the transpose of  and the Hermitian adjoint of 
 and the Hermitian adjoint of  , which we will denote respectively by
, which we will denote respectively by  and 
 and  , are related.  Denote by
, are related.  Denote by  and
 and  the canonical antilinear isometries of the Hilbert spaces
 the canonical antilinear isometries of the Hilbert spaces  and
 and  onto their duals.  Then
 onto their duals.  Then  is the following composition of maps:
 is the following composition of maps: 
  
Applications to functional analysis
 Suppose that  and
 and  are topological vector spaces and that
 are topological vector spaces and that  is a linear map, then many of
 is a linear map, then many of  's properties are reflected in 
's properties are reflected in  .
. 
 - If  and and are weakly closed, convex sets containing the origin, then are weakly closed, convex sets containing the origin, then implies  implies  .[4] .[4]
- The null space of  is the subspace of is the subspace of orthogonal to the range orthogonal to the range of  of  .[4] .[4]
 is injective if and only if the range is injective if and only if the range of of is weakly closed.[4] is weakly closed.[4]
See also
  References
  
  Bibliography
 - Halmos, Paul (1974), Finite-dimensional Vector Spaces, Springer, ISBN 0-387-90093-4
- Rudin, Walter (1991). Functional Analysis. International Series in Pure and Applied Mathematics. Vol. 8 (Second ed.). New York, NY: McGraw-Hill Science/Engineering/Math. ISBN 978-0-07-054236-5. OCLC 21163277.
- Schaefer, Helmut H.; Wolff, Manfred P. (1999). Topological Vector Spaces. GTM. Vol. 8 (Second ed.). New York, NY: Springer New York Imprint Springer. ISBN 978-1-4612-7155-0. OCLC 840278135.
- Trèves, François (2006) [1967]. Topological Vector Spaces, Distributions and Kernels. Mineola, N.Y.: Dover Publications. ISBN 978-0-486-45352-1. OCLC 853623322.
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