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In [[mathematics]], '''Schur polynomials''', named after [[Issai Schur]], are certain [[symmetric polynomial]]s in ''n'' variables, indexed by [[integer partition|partition]]s, that generalize the [[elementary symmetric polynomial]]s and the [[complete homogeneous symmetric polynomial]]s.  In [[representation theory]]  they are the characters of [[irreducible representation]]s of the [[general linear group]]s. The Schur polynomials  form a [[basis (linear algebra)|linear basis]] for the space of all symmetric polynomials.  Any product of Schur functions can be written as a linear combination of Schur polynomials with non-negative integral coefficients; the values of these coefficients is given combinatorially by the [[Littlewood-Richardson rule]]. More generally, '''skew Schur polynomials'''  are associated with pairs of partitions and have similar properties to Schur polynomials.
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==Definition==
 
Schur polynomials correspond to [[integer partition]]s.  Given a partition
 
:<math> d = d_1 + d_2 + \cdots + d_n, \; \; d_1 \geq d_2 \geq \cdots \ge d_n</math>
 
(where each ''d''<sub>''j''</sub> is a non-negative integer), the following functions are [[alternating polynomials]] (in other words they change sign under any [[transposition (mathematics)|transposition]] of the variables):
 
:<math> a_{(d_1+n-1, d_2+n-2, \dots , d_n)} (x_1, x_2, \dots , x_n) =
\det \left[ \begin{matrix} x_1^{d_1+n-1} & x_2^{d_1+n-1} & \dots & x_n^{d_1+n-1} \\
x_1^{d_2+n-2} & x_2^{d_2+n-2} & \dots & x_n^{d_2+n-2} \\
\vdots & \vdots & \ddots & \vdots \\
x_1^{d_n} & x_2^{d_n} & \dots & x_n^{d_n} \end{matrix} \right]
</math>
 
Since they are alternating, they are all divisible by the [[Vandermonde determinant]]:
 
:<math> a_{(n-1, n-2, \dots , 0)} (x_1, x_2, \dots , x_n) = \det \left[ \begin{matrix} x_1^{n-1} & x_2^{n-1} & \dots & x_n^{n-1} \\
x_1^{n-2} & x_2^{n-2} & \dots & x_n^{n-2} \\
\vdots & \vdots & \ddots & \vdots \\
1 & 1 & \dots & 1 \end{matrix} \right] = \prod_{1 \leq j < k \leq n} (x_j-x_k). </math>
The Schur polynomials are defined as the ratio:
:<math>
s_{(d_1, d_2, \dots , d_n)} (x_1, x_2, \dots , x_n) =
\frac{ a_{(d_1+n-1, d_2+n-2, \dots , d_n+0)} (x_1, x_2, \dots , x_n)}
{a_{(n-1, n-2, \dots , 0)} (x_1, x_2, \dots , x_n) }. </math>
 
This is a symmetric function because the numerator and denominator are both alternating, and a polynomial since all alternating polynomials are divisible by the Vandermonde determinant.
 
==Properties==
The degree ''d'' Schur polynomials in ''n'' variables are a linear basis for the space of homogeneous degree ''d'' symmetric polynomials in ''n'' variables.
 
For a partition &lambda;, the Schur polynomial is a sum of monomials:
 
:<math>
S_\lambda(x_1,x_2,\ldots,x_n)=\sum_T x^T = \sum_T x_1^{t_1}\cdots x_n^{t_n}
</math>
 
where the summation is over all semistandard [[Young tableau]]x ''T'' of shape &lambda;; the exponents ''t''<sub>1</sub>, ..., ''t''<sub>''n''</sub> give the weight of ''T'', in other words each ''t''<sub>''i''</sub> counts the occurrences of the number ''i'' in ''T''. This can be shown to be equivalent to the definition from the first Giambelli formula using the [[Lindström–Gessel–Viennot lemma]] (as outlined on that page).
 
The first [[Jacobi]]-Trudi formula expresses the Schur polynomial as a determinant
in terms of the  [[complete homogeneous symmetric polynomial]]s:
 
:<math> S_{\lambda} = \det_{ij} h_{\lambda_{i} + j - i}. </math>
where
:<math> h_i := S_{(i)} </math>.
The second Jacobi-Trudi formula expresses the Schur polynomial as
a determinant in terms of the [[elementary symmetric polynomial]]s:
 
:<math> S_{\lambda} = \det_{ij} e_{\lambda'_{i} + j - i} </math>,
where
:<math> e_i := S_{(1)^j} </math>
 
where <math>\lambda'</math> is the dual partition to <math>\lambda</math>.
 
These two formulae are known as “determinantal identities". Another such identity is
the [[Giambelli]] formula, which expresses the Schur function for an arbitrary partition
in terms of those for  the “hook partitions“ contained within the Young diagram.
In Frobenius notation, the partition is denoted
:<math> (a_{1}, ... a_{r}| b_{1}, ... b_{r})</math>
 
where,  for each diagonal element in position <math> ii  </math>,  <math> a_{i} </math> denotes
the number of boxes to the right in the same row  and <math> b_{i} </math> denotes the number of boxes beneath it
in the same column (the “arm“ and “leg“ lengths, respectively).
 
The [[Giambelli]] identity expresses the partition as the determinant
:<math> S_{ (a_{1}, ... a_{r}| b_{1}, ... b_{r})} = \det ( S_{(a_{i} | b_{j})}) </math>.
 
Schur polynomials can be expressed as  linear combinations of [[Symmetric polynomial#Monomial symmetric polynomials|monomial symmetric functions]] ''m''<sub>&mu;</sub> with non-negative integer coefficients ''K''<sub>&lambda;&mu;</sub> called [[Kostka number]]s:
 
: <math>S_\lambda= \sum_\mu K_{\lambda\mu}m_\mu.\ </math>
 
Evaluating the Schur polynomial ''S''<sub>&lambda;</sub> in (1,1,...,1) gives the number of semi-standard Young tableaux of shape &lambda; with entries in 1,2,...n.
One can show, by using the Weyl character formula for example, that
 
: <math>S_\lambda(1,1,\dots,1) = \prod_{1\leq i < j \leq n} \frac{\lambda_i - \lambda_j + j-i}{j-i}.</math>
 
In this formula, &lambda;, the tuple indicating the width of each row of the Young diagram, is implicitly extended with zeros until it has length <math>n</math>. The sum of the elements <math>\lambda_i</math> is <math>d</math>.
 
==Example==
The following extended example should help clarify these ideas.  Consider the case ''n'' = 3, ''d'' = 4.  Using Ferrers diagrams or some other method, we find that there are just four partitions of 4 into at most three parts.  We have
 
:<math> S_{(2,1,1)} (x_1, x_2, x_3) = \frac{1}{\Delta} \;
\det \left[ \begin{matrix} x_1^4 & x_2^4 & x_3^4 \\ x_1^2 & x_2^2 & x_3^2 \\ x_1 & x_2 & x_3 \end{matrix}
\right] = x_1 \, x_2 \, x_3 \, (x_1 + x_2 + x_3) </math>
 
:<math> S_{(2,2,0)} (x_1, x_2, x_3) = \frac{1}{\Delta} \;
\det \left[ \begin{matrix} x_1^4 & x_2^4 & x_3^4 \\ x_1^3 & x_2^3 & x_3^3 \\ 1 & 1 & 1 \end{matrix}
\right]= x_1^2 \, x_2^2 + x_1^2 \, x_3^2 + x_2^2 \, x_3^2
+ x_1^2 \, x_2 \, x_3 + x_1 \, x_2^2 \, x_3 + x_1 \, x_2 \, x_3^2 </math>
 
and so on.  Summarizing:
 
#<math> S_{(2,1,1)} = e_1 \, e_3</math>
#<math> S_{(2,2,0)} = e_2^2 - e_1 \, e_3</math>
#<math> S_{(3,1,0)} = e_1^2 \, e_2 - e_2^2 - e_1 \, e_3</math>
#<math> S_{(4,0,0)} = e_1^4 - 3 \, e_1^2 \, e_2 + 2 \, e_1 \, e_3 + e_2^2.</math>
 
Every homogeneous degree-four symmetric polynomial in three variables can be expressed as a unique ''linear combination'' of these four Schur polynomials, and this combination can again be found using a Gröbner basis for an appropriate elimination order.  For example,
 
:<math>\phi(x_1, x_2, x_3) = x_1^4 + x_2^4 + x_3^4</math>
 
is obviously a symmetric polynomial which is homogeneous of degree four, and we have
 
:<math>\phi = S_{(2,1,1)} - S_{(3,1,0)} + S_{(4,0,0)}.\,\!</math>
 
==Relation to representation theory==
 
The Schur polynomials occur in the [[representation theory of the symmetric group]]s, [[general linear group]]s, and [[unitary group]]s.  The [[Weyl character formula]] implies that the Schur polynomials are the characters of finite dimensional irreducible representations of the general linear groups, and  helps to generalize Schur's work to other compact and semisimple [[Lie group]]s.
 
Several expressions arise for this relation, one of the most important being the expansion of the Schur functions ''s''<sub>&lambda;</sub> in terms of the symmetric power functions <math>p_k=\sum_i x_i^k</math>. If we write &chi;{{su|p=&lambda;|b=&rho;}} for the character of the representation of the symmetric group indexed by the partition &lambda; evaluated at elements of cycle type indexed by the partition &rho;, then
:<math>s_\lambda=\sum_{\rho=(1^{r_1},2^{r_2},3^{r_3},\dots)}\chi^\lambda_\rho \prod_k \frac{p^{r_k}_k}{r_k!},</math>
where &rho; = (1<sup>''r''<sub>1</sub></sup>, 2<sup>''r''<sub>2</sub></sup>, 3<sup>''r''<sub>3</sub></sup>, ...) means that the partition &rho; has ''r''<sub>''k''</sub> parts of length ''k''.
 
==Skew Schur functions==
Skew Schur functions ''s''<sub>&lambda;/&mu;</sub> depend on two partitions &lambda; and &mu;, and can be defined by the property
:<math>\langle s_{\lambda/\mu},s_\nu\rangle = \langle s_{\lambda},s_\mu  s_\nu\rangle. </math>
 
 
Similar to the ordinary Schur polynomials, there are numerous ways to compute these. The corresponding Jacobi-Trudi identities are
:<math>S_{\lambda/\mu} = (h_{\lambda_i - \mu_j -i + j}), 1\leq i,j \leq l(\lambda)</math>,
:<math>S_{\lambda'/\mu'} = (e_{\lambda_i - \mu_j -i + j}), 1\leq i,j \leq l(\lambda)</math>.
 
There is also a combinatorial interpretation of the skew Schur polynomials,
namely it is a sum over all semi-standard Young tableaux (or column-strict tableaux) of the skew shape <math>\lambda/\mu</math>.
 
==See also==
 
*[[Littlewood-Richardson rule]], where one finds some identities involving Schur polynomials.
*[[Schubert polynomials]], a generalization of Schur polynomials.
 
==References==
*{{Cite book | last1=Macdonald | first1=I. G. | author1-link=Ian G. Macdonald | title=Symmetric functions and Hall polynomials | url=http://www.oup.com/uk/catalogue/?ci=9780198504504 | publisher=The Clarendon Press Oxford University Press | edition=2nd | series=Oxford Mathematical Monographs | isbn=978-0-19-853489-1 | id={{MathSciNet | id = 1354144}} | year=1995 | postscript=<!--None-->}}
*{{springer|id=s/s120040|title=Schur functions in algebraic combinatorics|first=Bruce E. |last=Sagan | authorlink=Bruce Sagan}}
*{{cite book | author=[[Bernd Sturmfels|Sturmfels, Bernd]] | title=Algorithms in Invariant Theory | location=New York | publisher=Springer | year=1993 | isbn=0-387-82445-6}}
 
[[Category:Homogeneous polynomials]]
[[Category:Invariant theory]]
[[Category:Representation theory of finite groups]]
[[Category:Symmetric functions]]
[[Category:Orthogonal polynomials]]

Latest revision as of 09:40, 16 May 2014

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