Frobenius normal form
   HOME

TheInfoList



OR:

In
linear algebra Linear algebra is the branch of mathematics concerning linear equations such as :a_1x_1+\cdots +a_nx_n=b, linear maps such as :(x_1, \ldots, x_n) \mapsto a_1x_1+\cdots +a_nx_n, and their representations in vector spaces and through matrix (mathemat ...
, the Frobenius normal form or rational canonical form of a
square In geometry, a square is a regular polygon, regular quadrilateral. It has four straight sides of equal length and four equal angles. Squares are special cases of rectangles, which have four equal angles, and of rhombuses, which have four equal si ...
matrix Matrix (: matrices or matrixes) or MATRIX may refer to: Science and mathematics * Matrix (mathematics), a rectangular array of numbers, symbols or expressions * Matrix (logic), part of a formula in prenex normal form * Matrix (biology), the m ...
''A'' with entries in a
field Field may refer to: Expanses of open ground * Field (agriculture), an area of land used for agricultural purposes * Airfield, an aerodrome that lacks the infrastructure of an airport * Battlefield * Lawn, an area of mowed grass * Meadow, a grass ...
''F'' is a
canonical form In mathematics and computer science, a canonical, normal, or standard form of a mathematical object is a standard way of presenting that object as a mathematical expression. Often, it is one which provides the simplest representation of an obje ...
for matrices obtained by conjugation by
invertible matrices In linear algebra, an invertible matrix (''non-singular'', ''non-degenarate'' or ''regular'') is a square matrix that has an inverse. In other words, if some other matrix is multiplied by the invertible matrix, the result can be multiplied by a ...
over ''F''. The form reflects a minimal decomposition of the
vector space In mathematics and physics, a vector space (also called a linear space) is a set (mathematics), set whose elements, often called vector (mathematics and physics), ''vectors'', can be added together and multiplied ("scaled") by numbers called sc ...
into subspaces that are cyclic for ''A'' (i.e., spanned by some vector and its repeated
image An image or picture is a visual representation. An image can be Two-dimensional space, two-dimensional, such as a drawing, painting, or photograph, or Three-dimensional space, three-dimensional, such as a carving or sculpture. Images may be di ...
s under ''A''). Since only one normal form can be reached from a given matrix (whence the "canonical"), a matrix ''B'' is similar to ''A'' if and only if it has the same rational canonical form as ''A''. Since this form can be found without any operations that might change when extending the field ''F'' (whence the "rational"), notably without factoring polynomials, this shows that whether two matrices are similar does not change upon field extensions. The form is named after German mathematician
Ferdinand Georg Frobenius Ferdinand Georg Frobenius (26 October 1849 – 3 August 1917) was a German mathematician, best known for his contributions to the theory of elliptic functions, differential equations, number theory, and to group theory. He is known for the famou ...
. Some authors use the term rational canonical form for a somewhat different form that is more properly called the primary rational canonical form. Instead of decomposing into a minimum number of cyclic subspaces, the primary form decomposes into a maximum number of cyclic subspaces. It is also defined over ''F'', but has somewhat different properties: finding the form requires factorization of polynomials, and as a consequence the primary rational canonical form may change when the same matrix is considered over an extension field of ''F''. This article mainly deals with the form that does not require factorization, and explicitly mentions "primary" when the form using factorization is meant.


Motivation

When trying to find out whether two square matrices ''A'' and ''B'' are similar, one approach is to try, for each of them, to decompose the vector space as far as possible into a
direct sum The direct sum is an operation between structures in abstract algebra, a branch of mathematics. It is defined differently but analogously for different kinds of structures. As an example, the direct sum of two abelian groups A and B is anothe ...
of stable subspaces, and compare the respective actions on these subspaces. For instance if both are
diagonalizable In linear algebra, a square matrix A is called diagonalizable or non-defective if it is similar to a diagonal matrix. That is, if there exists an invertible matrix P and a diagonal matrix D such that . This is equivalent to (Such D are not ...
, then one can take the decomposition into
eigenspace In linear algebra, an eigenvector ( ) or characteristic vector is a Vector (mathematics and physics), vector that has its direction (geometry), direction unchanged (or reversed) by a given linear map, linear transformation. More precisely, an e ...
s (for which the action is as simple as it can get, namely by a scalar), and then similarity can be decided by comparing
eigenvalue In linear algebra, an eigenvector ( ) or characteristic vector is a vector that has its direction unchanged (or reversed) by a given linear transformation. More precisely, an eigenvector \mathbf v of a linear transformation T is scaled by a ...
s and their multiplicities. While in practice this is often a quite insightful approach, there are various drawbacks this has as a general method. First, it requires finding all eigenvalues, say as
roots A root is the part of a plant, generally underground, that anchors the plant body, and absorbs and stores water and nutrients. Root or roots may also refer to: Art, entertainment, and media * ''The Root'' (magazine), an online magazine focusin ...
of the
characteristic polynomial In linear algebra, the characteristic polynomial of a square matrix is a polynomial which is invariant under matrix similarity and has the eigenvalues as roots. It has the determinant and the trace of the matrix among its coefficients. The ...
, but it may not be possible to give an explicit expression for them. Second, a complete set of eigenvalues might exist only in an extension of the field one is working over, and then one does not get a proof of similarity over the original field. Finally ''A'' and ''B'' might not be diagonalizable even over this larger field, in which case one must instead use a decomposition into generalized eigenspaces, and possibly into
Jordan block In the mathematical discipline of matrix theory, a Jordan matrix, named after Camille Jordan, is a block diagonal matrix over a ring (whose identities are the zero 0 and one 1), where each block along the diagonal, called a Jordan block, has th ...
s. But obtaining such a fine decomposition is not necessary to just decide whether two matrices are similar. The rational canonical form is based on instead using a direct sum decomposition into stable subspaces that are as large as possible, while still allowing a very simple description of the action on each of them. These subspaces must be generated by a single nonzero vector ''v'' and all its images by repeated application of the
linear operator In mathematics, and more specifically in linear algebra, a linear map (also called a linear mapping, linear transformation, vector space homomorphism, or in some contexts linear function) is a mapping V \to W between two vector spaces that pr ...
associated to the matrix; such subspaces are called cyclic subspaces (by analogy with cyclic
subgroup In group theory, a branch of mathematics, a subset of a group G is a subgroup of G if the members of that subset form a group with respect to the group operation in G. Formally, given a group (mathematics), group under a binary operation  ...
s) and they are clearly stable under the linear operator. A basis of such a subspace is obtained by taking ''v'' and its successive images as long as they are
linearly independent In the theory of vector spaces, a set of vectors is said to be if there exists no nontrivial linear combination of the vectors that equals the zero vector. If such a linear combination exists, then the vectors are said to be . These concep ...
. The matrix of the linear operator with respect to such a basis is the
companion matrix In linear algebra, the Frobenius companion matrix of the monic polynomial p(x)=c_0 + c_1 x + \cdots + c_x^ + x^n is the square matrix defined as C(p)=\begin 0 & 0 & \dots & 0 & -c_0 \\ 1 & 0 & \dots & 0 & -c_1 \\ 0 & 1 & \dots & 0 & -c_2 \\ \ ...
of a
monic polynomial In algebra, a monic polynomial is a non-zero univariate polynomial (that is, a polynomial in a single variable) in which the leading coefficient (the nonzero coefficient of highest degree) is equal to 1. That is to say, a monic polynomial is one ...
; this polynomial (the minimal polynomial of the operator restricted to the subspace, which notion is analogous to that of the
order Order, ORDER or Orders may refer to: * A socio-political or established or existing order, e.g. World order, Ancien Regime, Pax Britannica * Categorization, the process in which ideas and objects are recognized, differentiated, and understood ...
of a cyclic subgroup) determines the action of the operator on the cyclic subspace up to
isomorphism In mathematics, an isomorphism is a structure-preserving mapping or morphism between two structures of the same type that can be reversed by an inverse mapping. Two mathematical structures are isomorphic if an isomorphism exists between the ...
, and is independent of the choice of the vector ''v'' generating the subspace. A direct sum decomposition into cyclic subspaces always exists, and finding one does not require factoring polynomials. However it is possible that cyclic subspaces do allow a decomposition as direct sum of smaller cyclic subspaces (essentially by the
Chinese remainder theorem In mathematics, the Chinese remainder theorem states that if one knows the remainders of the Euclidean division of an integer ''n'' by several integers, then one can determine uniquely the remainder of the division of ''n'' by the product of thes ...
). Therefore, just having for both matrices some decomposition of the space into cyclic subspaces, and knowing the corresponding minimal polynomials, is not in itself sufficient to decide their similarity. An additional condition is imposed to ensure that for similar matrices one gets decompositions into cyclic subspaces that exactly match: in the list of associated minimal polynomials each one must divide the next (and the constant polynomial 1 is forbidden to exclude trivial cyclic subspaces). The resulting list of polynomials are called the
invariant factor The invariant factors of a module over a principal ideal domain (PID) occur in one form of the structure theorem for finitely generated modules over a principal ideal domain. If R is a PID and M a finitely generated R-module, then :M\cong R^r\ ...
s of (the ''K'' 'X'' module defined by) the matrix, and two matrices are similar if and only if they have identical lists of invariant factors. The rational canonical form of a matrix ''A'' is obtained by expressing it on a basis adapted to a decomposition into cyclic subspaces whose associated minimal polynomials are the invariant factors of ''A''; two matrices are similar if and only if they have the same rational canonical form.


Example

Consider the following matrix A, over Q: :\scriptstyle A=\begin -1& 3&-1& 0&-2& 0& 0&-2 \\ -1&-1& 1& 1&-2&-1& 0&-1 \\ -2&-6& 4& 3&-8&-4&-2& 1 \\ -1& 8&-3&-1& 5& 2& 3&-3 \\ 0& 0& 0& 0& 0& 0& 0& 1 \\ 0& 0& 0& 0&-1& 0& 0& 0 \\ 1& 0& 0& 0& 2& 0& 0& 0 \\ 0& 0& 0& 0& 4& 0& 1& 0 \end. ''A'' has minimal polynomial \mu = X^6 - 4X^4 - 2X^3 + 4X^2 + 4X + 1, so that the
dimension In physics and mathematics, the dimension of a mathematical space (or object) is informally defined as the minimum number of coordinates needed to specify any point within it. Thus, a line has a dimension of one (1D) because only one coo ...
of a subspace generated by the repeated images of a single vector is at most 6. The
characteristic polynomial In linear algebra, the characteristic polynomial of a square matrix is a polynomial which is invariant under matrix similarity and has the eigenvalues as roots. It has the determinant and the trace of the matrix among its coefficients. The ...
is \chi = X^8 - X^7 - 5X^6 + 2X^5 + 10X^4 + 2X^3 - 7X^2 - 5X - 1, which is a multiple of the minimal polynomial by a factor X^2 - X - 1. There always exist vectors such that the cyclic subspace that they generate has the same minimal polynomial as the operator has on the whole space; indeed most vectors will have this property, and in this case the first standard basis vector e_1 does so: the vectors A^k(e_1) for k=0,1,\ldots,5 are linearly independent and span a cyclic subspace with minimal polynomial \mu. There exist complementary stable subspaces (of dimension 2) to this cyclic subspace, and the space generated by vectors v=(3,4,8,0,-1,0,2,-1)^\top and w=(5,4,5,9,-1,1,1,-2)^\top is an example. In fact one has A\cdot v=w, so the complementary subspace is a cyclic subspace generated by v; it has minimal polynomial X^2 - X - 1. Since \mu is the minimal polynomial of the whole space, it is clear that X^2 - X - 1 must divide \mu (and it is easily checked that it does), and we have found the invariant factors X^2 - X - 1 and \mu = X^6 - 4X^4 - 2X^3 + 4X^2 + 4X + 1 of ''A''. Then the rational canonical form of ''A'' is the block diagonal matrix with the corresponding companion matrices as diagonal blocks, namely :\scriptstyle C=\left(\begin 0& 1& 0& 0& 0& 0& 0& 0 \\ 1& 1& 0& 0& 0& 0& 0& 0 \\\hline 0& 0& 0& 0& 0& 0& 0&-1 \\ 0& 0& 1& 0& 0& 0& 0&-4 \\ 0& 0& 0& 1& 0& 0& 0&-4 \\ 0& 0& 0& 0& 1& 0& 0& 2 \\ 0& 0& 0& 0& 0& 1& 0& 4 \\ 0& 0& 0& 0& 0& 0& 1& 0 \end\right). A basis on which this form is attained is formed by the vectors v,w above, followed by A^k(e_1) for k=0,1,\ldots,5; explicitly this means that for :\scriptstyle P=\begin 3& 5& 1&-1& 0& 0& -4& 0\\ 4& 4& 0&-1&-1&-2& -3&-5\\ 8& 5& 0&-2&-5&-2&-11&-6\\ 0& 9& 0&-1& 3&-2& 0& 0\\ -1&-1& 0& 0& 0& 1& -1& 4\\ 0& 1& 0& 0& 0& 0& -1& 1\\ 2& 1& 0& 1&-1& 0& 2&-6\\ -1&-2& 0& 0& 1&-1& 4&-2 \end, one has A=PCP^.


General case and theory

Fix a base field ''F'' and a finite-dimensional
vector space In mathematics and physics, a vector space (also called a linear space) is a set (mathematics), set whose elements, often called vector (mathematics and physics), ''vectors'', can be added together and multiplied ("scaled") by numbers called sc ...
''V'' over ''F''. Given a polynomial ''P'' ∈ ''F'' 'X'' there is associated to it a
companion matrix In linear algebra, the Frobenius companion matrix of the monic polynomial p(x)=c_0 + c_1 x + \cdots + c_x^ + x^n is the square matrix defined as C(p)=\begin 0 & 0 & \dots & 0 & -c_0 \\ 1 & 0 & \dots & 0 & -c_1 \\ 0 & 1 & \dots & 0 & -c_2 \\ \ ...
''C''''P'' whose characteristic polynomial and minimal polynomial are both equal to ''P''. Theorem: Let ''V'' be a finite-dimensional vector space over a field ''F'', and ''A'' a square matrix over ''F''. Then ''V'' (viewed as an ''F'' 'X'' module with the action of ''X'' given by ''A'') admits a ''F'' 'X''module isomorphism :''V'' ≅ ''F'' 'X''''f''1 ⊕ … ⊕ ''F'' 'X''''fk'' where the ''fi'' ∈ ''F'' 'X''may be taken to be monic polynomials of positive degree (so they are non-
unit Unit may refer to: General measurement * Unit of measurement, a definite magnitude of a physical quantity, defined and adopted by convention or by law **International System of Units (SI), modern form of the metric system **English units, histo ...
s in ''F'' 'X'' that satisfy the relations :''f''1 , ''f''2 , … , ''fk'' (where "a , b" is notation for "''a'' divides ''b''"); with these conditions the list of polynomials ''fi'' is unique. ''Sketch of Proof'': Apply the
structure theorem for finitely generated modules over a principal ideal domain In mathematics, in the field of abstract algebra, the structure theorem for finitely generated modules over a principal ideal domain is a generalization of the fundamental theorem of finitely generated abelian groups and roughly states that finite ...
to ''V'', viewing it as an ''F'' 'X''module. The structure theorem provides a decomposition into cyclic factors, each of which is a
quotient In arithmetic, a quotient (from 'how many times', pronounced ) is a quantity produced by the division of two numbers. The quotient has widespread use throughout mathematics. It has two definitions: either the integer part of a division (in th ...
of ''F'' 'X''by a proper ideal; the zero ideal cannot be present since the resulting
free module In mathematics, a free module is a module that has a ''basis'', that is, a generating set that is linearly independent. Every vector space is a free module, but, if the ring of the coefficients is not a division ring (not a field in the commu ...
would be infinite-dimensional as ''F'' vector space, while ''V'' is finite-dimensional. For the polynomials ''f''''i'' one then takes the unique monic generators of the respective ideals, and since the structure theorem ensures containment of every ideal in the preceding ideal, one obtains the divisibility conditions for the ''f''''i''. See Ffor details. Given an arbitrary square matrix, the elementary divisors used in the construction of the
Jordan normal form \begin \lambda_1 1\hphantom\hphantom\\ \hphantom\lambda_1 1\hphantom\\ \hphantom\lambda_1\hphantom\\ \hphantom\lambda_2 1\hphantom\hphantom\\ \hphantom\hphantom\lambda_2\hphantom\\ \hphantom\lambda_3\hphantom\\ \hphantom\ddots\hphantom\\ ...
do not exist over ''F'' 'X'' so the
invariant factors The invariant factors of a module over a principal ideal domain (PID) occur in one form of the structure theorem for finitely generated modules over a principal ideal domain. If R is a PID and M a finitely generated R-module, then :M\cong R^r\o ...
''f''''i'' as given above must be used instead. The last of these factors ''fk'' is then the minimal polynomial, which all the invariant factors therefore divide, and the product of the invariant factors gives the characteristic polynomial. Note that this implies that the minimal polynomial divides the characteristic polynomial (which is essentially the Cayley-Hamilton theorem), and that every irreducible factor of the characteristic polynomial also divides the minimal polynomial (possibly with lower multiplicity). For each invariant factor ''fi'' one takes its
companion matrix In linear algebra, the Frobenius companion matrix of the monic polynomial p(x)=c_0 + c_1 x + \cdots + c_x^ + x^n is the square matrix defined as C(p)=\begin 0 & 0 & \dots & 0 & -c_0 \\ 1 & 0 & \dots & 0 & -c_1 \\ 0 & 1 & \dots & 0 & -c_2 \\ \ ...
''C''''fi'', and the block diagonal matrix formed from these blocks yields the rational canonical form of ''A''. When the minimal polynomial is identical to the characteristic polynomial (the case ''k'' = 1), the Frobenius normal form is the companion matrix of the characteristic polynomial. As the rational canonical form is uniquely determined by the unique invariant factors associated to ''A'', and these invariant factors are independent of basis, it follows that two square matrices ''A'' and ''B'' are similar if and only if they have the same rational canonical form.


A rational normal form generalizing the Jordan normal form

The Frobenius normal form does not reflect any form of factorization of the characteristic polynomial, even if it does exist over the ground field ''F''. This implies that it is invariant when ''F'' is replaced by a different field (as long as it contains the entries of the original matrix ''A''). On the other hand, this makes the Frobenius normal form rather different from other normal forms that do depend on factoring the characteristic polynomial, notably the
diagonal form In mathematics, a diagonal form is an algebraic form (homogeneous polynomial) without cross-terms involving different indeterminates. That is, it is of the form :\sum_^n a_i ^m\ for some degree ''m''. Such forms ''F'', and the hypersurfaces ...
(if ''A'' is diagonalizable) or more generally the
Jordan normal form \begin \lambda_1 1\hphantom\hphantom\\ \hphantom\lambda_1 1\hphantom\\ \hphantom\lambda_1\hphantom\\ \hphantom\lambda_2 1\hphantom\hphantom\\ \hphantom\hphantom\lambda_2\hphantom\\ \hphantom\lambda_3\hphantom\\ \hphantom\ddots\hphantom\\ ...
(if the characteristic polynomial splits into linear factors). For instance, the Frobenius normal form of a diagonal matrix with distinct diagonal entries is just the companion matrix of its characteristic polynomial. There is another way to define a normal form, that, like the Frobenius normal form, is always defined over the same field ''F'' as ''A'', but that does reflect a possible factorization of the characteristic polynomial (or equivalently the minimal polynomial) into irreducible factors over ''F'', and which reduces to the Jordan normal form when this factorization only contains linear factors (corresponding to eigenvalues). This form is sometimes called the generalized Jordan normal form, or primary rational canonical form. It is based on the fact that the vector space can be canonically decomposed into a direct sum of stable subspaces corresponding to the ''distinct'' irreducible factors ''P'' of the characteristic polynomial (as stated by the Xavier Gourdon, ''Les maths en tête, Mathématiques pour M', Algèbre'', 1998, Ellipses, Th. 1 p. 173), where the characteristic polynomial of each summand is a power of the corresponding ''P''. These summands can be further decomposed, non-canonically, as a direct sum of cyclic ''F'' 'x''modules (like is done for the Frobenius normal form above), where the characteristic polynomial of each summand is still a (generally smaller) power of ''P''. The primary rational canonical form is a block diagonal matrix corresponding to such a decomposition into cyclic modules, with a particular form called ''generalized Jordan block'' in the diagonal blocks, corresponding to a particular choice of a basis for the cyclic modules. This generalized Jordan block is itself a
block matrix In mathematics, a block matrix or a partitioned matrix is a matrix that is interpreted as having been broken into sections called blocks or submatrices. Intuitively, a matrix interpreted as a block matrix can be visualized as the original matrix w ...
of the form :\scriptstyle\beginC&0&\cdots&0\\U&C&\cdots&0\\\vdots&\ddots&\ddots&\vdots\\0&\cdots&U&C\end where ''C'' is the companion matrix of the irreducible polynomial , and is a matrix whose sole nonzero entry is a 1 in the upper right-hand corner. For the case of a linear irreducible factor , these blocks are reduced to single entries and and, one finds a (
transpose In linear algebra, the transpose of a Matrix (mathematics), matrix is an operator which flips a matrix over its diagonal; that is, it switches the row and column indices of the matrix by producing another matrix, often denoted by (among other ...
d) Jordan block. In any generalized Jordan block, all entries immediately below the main diagonal are 1. A basis of the cyclic module giving rise to this form is obtained by choosing a generating vector (one that is not annihilated by where the minimal polynomial of the cyclic module is ), and taking as basis : v,A(v),A^2(v),\ldots,A^(v), ~ P(A)(v), A(P(A)(v)),\ldots,A^(P(A)(v)), ~ P^2(A)(v),\ldots, ~ P^(A)(v),\ldots,A^(P^(A)(v)) where .


See also

*
Smith normal form In mathematics, the Smith normal form (sometimes abbreviated SNF) is a normal form that can be defined for any matrix (not necessarily square) with entries in a principal ideal domain (PID). The Smith normal form of a matrix is diagonal, and can ...


References

* FDavid S. Dummit and Richard M. Foote. ''Abstract Algebra''. 2nd Edition, John Wiley & Sons. pp. 442, 446, 452-458. . {{Reflist


External links


Rational Canonical Form (Mathworld)


Algorithms




An Algorithm for the Frobenius Normal Form (pdf)

A rational canonical form Algorithm (pdf)
Linear algebra Matrix normal forms