canonical basis

{{Short description|Basis of a type of algebraic structure}}

In mathematics, a canonical basis is a basis of an algebraic structure that is canonical in a sense that depends on the precise context:

Representation theory

The canonical basis for the irreducible representations of a quantized enveloping algebra of

type ADE and also for the plus part of that algebra was introduced by Lusztig {{harvtxt|Lusztig|1990}} by

two methods: an algebraic one (using a braid group action and PBW bases) and a topological one

(using intersection cohomology). Specializing the parameter q to q=1 yields a canonical basis for the irreducible representations of the corresponding simple Lie algebra, which was

not known earlier. Specializing the parameter q to q=0 yields something like a shadow of a basis. This shadow (but not the basis itself) for the case of irreducible representations

was considered independently by Kashiwara;{{harvtxt|Kashiwara|1990}} it is sometimes called the crystal basis.

The definition of the canonical basis was extended to the Kac-Moody setting by Kashiwara {{harvtxt|Kashiwara|1991}} (by an algebraic method) and by Lusztig {{harvtxt|Lusztig|1991}} (by a topological method).

There is a general concept underlying these bases:

Consider the ring of integral Laurent polynomials \mathcal{Z}:=\mathbb{Z}\left[v,v^{-1}\right] with its two subrings \mathcal{Z}^{\pm}:=\mathbb{Z}\left[v^{\pm 1}\right] and the automorphism \overline{\cdot} defined by \overline{v}:=v^{-1}.

A precanonical structure on a free \mathcal{Z}-module F consists of

  • A standard basis (t_i)_{i\in I} of F,
  • An interval finite partial order on I, that is, (-\infty,i] := \{j\in I \mid j\leq i\} is finite for all i\in I,
  • A dualization operation, that is, a bijection F\to F of order two that is \overline{\cdot}-semilinear and will be denoted by \overline{\cdot} as well.

If a precanonical structure is given, then one can define the \mathcal{Z}^{\pm} submodule F^{\pm} := \sum \mathcal{Z}^{\pm} t_j of F.

A canonical basis of the precanonical structure is then a \mathcal{Z}-basis (c_i)_{i\in I} of F that satisfies:

  • \overline{c_i}=c_i and
  • c_i \in \sum_{j\leq i} \mathcal{Z}^+ t_j \text{ and } c_i \equiv t_i \mod vF^+

for all i\in I.

One can show that there exists at most one canonical basis for each precanonical structure.{{harvtxt|Lusztig|1993|p=194}} A sufficient condition for existence is that the polynomials r_{ij}\in\mathcal{Z} defined by \overline{t_j}=\sum_i r_{ij} t_i satisfy r_{ii}=1 and r_{ij}\neq 0 \implies i\leq j.

A canonical basis induces an isomorphism from \textstyle F^+\cap \overline{F^+} = \sum_i \mathbb{Z}c_i to F^+/vF^+.

= Hecke algebras =

Let (W,S) be a Coxeter group. The corresponding Iwahori-Hecke algebra H has the standard basis (T_w)_{w\in W}, the group is partially ordered by the Bruhat order which is interval finite and has a dualization operation defined by \overline{T_w}:=T_{w^{-1}}^{-1}. This is a precanonical structure on H that satisfies the sufficient condition above and the corresponding canonical basis of H is the Kazhdan–Lusztig basis

: C_w' = \sum_{y\leq w} P_{y,w}(v^2) T_w

with P_{y,w} being the Kazhdan–Lusztig polynomials.

Linear algebra

If we are given an n × n matrix A and wish to find a matrix J in Jordan normal form, similar to A, we are interested only in sets of linearly independent generalized eigenvectors. A matrix in Jordan normal form is an "almost diagonal matrix," that is, as close to diagonal as possible. A diagonal matrix D is a special case of a matrix in Jordan normal form. An ordinary eigenvector is a special case of a generalized eigenvector.

Every n × n matrix A possesses n linearly independent generalized eigenvectors. Generalized eigenvectors corresponding to distinct eigenvalues are linearly independent. If \lambda is an eigenvalue of A of algebraic multiplicity \mu, then A will have \mu linearly independent generalized eigenvectors corresponding to \lambda.

For any given n × n matrix A, there are infinitely many ways to pick the n linearly independent generalized eigenvectors. If they are chosen in a particularly judicious manner, we can use these vectors to show that A is similar to a matrix in Jordan normal form. In particular,

Definition: A set of n linearly independent generalized eigenvectors is a canonical basis if it is composed entirely of Jordan chains.

Thus, once we have determined that a generalized eigenvector of rank m is in a canonical basis, it follows that the m − 1 vectors \mathbf x_{m-1}, \mathbf x_{m-2}, \ldots , \mathbf x_1 that are in the Jordan chain generated by \mathbf x_m are also in the canonical basis.{{harvtxt|Bronson|1970|pp=196,197}}

=Computation=

Let \lambda_i be an eigenvalue of A of algebraic multiplicity \mu_i . First, find the ranks (matrix ranks) of the matrices (A - \lambda_i I), (A - \lambda_i I)^2, \ldots , (A - \lambda_i I)^{m_i} . The integer m_i is determined to be the first integer for which (A - \lambda_i I)^{m_i} has rank n - \mu_i (n being the number of rows or columns of A, that is, A is n × n).

Now define

: \rho_k = \operatorname{rank}(A - \lambda_i I)^{k-1} - \operatorname{rank}(A - \lambda_i I)^k \qquad (k = 1, 2, \ldots , m_i).

The variable \rho_k designates the number of linearly independent generalized eigenvectors of rank k (generalized eigenvector rank; see generalized eigenvector) corresponding to the eigenvalue \lambda_i that will appear in a canonical basis for A. Note that

: \operatorname{rank}(A - \lambda_i I)^0 = \operatorname{rank}(I) = n .

Once we have determined the number of generalized eigenvectors of each rank that a canonical basis has, we can obtain the vectors explicitly (see generalized eigenvector).{{harvtxt|Bronson|1970|pp=197,198}}

=Example=

This example illustrates a canonical basis with two Jordan chains. Unfortunately, it is a little difficult to construct an interesting example of low order.{{harvtxt|Nering|1970|pp=122,123}}

The matrix

:A = \begin{pmatrix}

4 & 1 & 1 & 0 & 0 & -1 \\

0 & 4 & 2 & 0 & 0 & 1 \\

0 & 0 & 4 & 1 & 0 & 0 \\

0 & 0 & 0 & 5 & 1 & 0 \\

0 & 0 & 0 & 0 & 5 & 2 \\

0 & 0 & 0 & 0 & 0 & 4

\end{pmatrix}

has eigenvalues \lambda_1 = 4 and \lambda_2 = 5 with algebraic multiplicities \mu_1 = 4 and \mu_2 = 2 , but geometric multiplicities \gamma_1 = 1 and \gamma_2 = 1 .

For \lambda_1 = 4, we have n - \mu_1 = 6 - 4 = 2,

: (A - 4I) has rank 5,

: (A - 4I)^2 has rank 4,

: (A - 4I)^3 has rank 3,

: (A - 4I)^4 has rank 2.

Therefore m_1 = 4.

: \rho_4 = \operatorname{rank}(A - 4I)^3 - \operatorname{rank}(A - 4I)^4 = 3 - 2 = 1,

: \rho_3 = \operatorname{rank}(A - 4I)^2 - \operatorname{rank}(A - 4I)^3 = 4 - 3 = 1,

: \rho_2 = \operatorname{rank}(A - 4I)^1 - \operatorname{rank}(A - 4I)^2 = 5 - 4 = 1,

: \rho_1 = \operatorname{rank}(A - 4I)^0 - \operatorname{rank}(A - 4I)^1 = 6 - 5 = 1.

Thus, a canonical basis for A will have, corresponding to \lambda_1 = 4, one generalized eigenvector each of ranks 4, 3, 2 and 1.

For \lambda_2 = 5, we have n - \mu_2 = 6 - 2 = 4,

: (A - 5I) has rank 5,

: (A - 5I)^2 has rank 4.

Therefore m_2 = 2.

: \rho_2 = \operatorname{rank}(A - 5I)^1 - \operatorname{rank}(A - 5I)^2 = 5 - 4 = 1,

: \rho_1 = \operatorname{rank}(A - 5I)^0 - \operatorname{rank}(A - 5I)^1 = 6 - 5 = 1.

Thus, a canonical basis for A will have, corresponding to \lambda_2 = 5, one generalized eigenvector each of ranks 2 and 1.

A canonical basis for A is

:

\left\{ \mathbf x_1, \mathbf x_2, \mathbf x_3, \mathbf x_4, \mathbf y_1, \mathbf y_2 \right\} =

\left\{

\begin{pmatrix} -4 \\ 0 \\ 0 \\ 0 \\ 0 \\ 0 \end{pmatrix},

\begin{pmatrix} -27 \\ -4 \\ 0 \\ 0 \\ 0 \\ 0 \end{pmatrix},

\begin{pmatrix} 25 \\ -25 \\ -2 \\ 0 \\ 0 \\ 0 \end{pmatrix},

\begin{pmatrix} 0 \\ 36 \\ -12 \\ -2 \\ 2 \\ -1 \end{pmatrix},

\begin{pmatrix} 3 \\ 2 \\ 1 \\ 1 \\ 0 \\ 0 \end{pmatrix},

\begin{pmatrix} -8 \\ -4 \\ -1 \\ 0 \\ 1 \\ 0 \end{pmatrix}

\right\}.

\mathbf x_1 is the ordinary eigenvector associated with \lambda_1 .

\mathbf x_2, \mathbf x_3 and \mathbf x_4 are generalized eigenvectors associated with \lambda_1 .

\mathbf y_1 is the ordinary eigenvector associated with \lambda_2 .

\mathbf y_2 is a generalized eigenvector associated with \lambda_2 .

A matrix J in Jordan normal form, similar to A is obtained as follows:

:

M =

\begin{pmatrix} \mathbf x_1 & \mathbf x_2 & \mathbf x_3 & \mathbf x_4 & \mathbf y_1 & \mathbf y_2 \end{pmatrix} =

\begin{pmatrix}

-4 & -27 & 25 & 0 & 3 & -8 \\

0 & -4 & -25 & 36 & 2 & -4 \\

0 & 0 & -2 & -12 & 1 & -1 \\

0 & 0 & 0 & -2 & 1 & 0 \\

0 & 0 & 0 & 2 & 0 & 1 \\

0 & 0 & 0 & -1 & 0 & 0

\end{pmatrix},

: J = \begin{pmatrix}

4 & 1 & 0 & 0 & 0 & 0 \\

0 & 4 & 1 & 0 & 0 & 0 \\

0 & 0 & 4 & 1 & 0 & 0 \\

0 & 0 & 0 & 4 & 0 & 0 \\

0 & 0 & 0 & 0 & 5 & 1 \\

0 & 0 & 0 & 0 & 0 & 5

\end{pmatrix},

where the matrix M is a generalized modal matrix for A and AM = MJ.{{harvtxt|Bronson|1970|p=203}}

See also

Notes

References

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Category:Linear algebra

Category:Abstract algebra

Category:Lie algebras

Category:Representation theory

Category:Quantum groups