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mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
, the Littlewood–Richardson rule is a combinatorial description of the coefficients that arise when decomposing a product of two Schur functions as a linear combination of other Schur functions. These coefficients are natural numbers, which the Littlewood–Richardson rule describes as counting certain skew tableaux. They occur in many other mathematical contexts, for instance as multiplicity in the decomposition of
tensor product In mathematics, the tensor product V \otimes W of two vector spaces and (over the same field) is a vector space to which is associated a bilinear map V\times W \to V\otimes W that maps a pair (v,w),\ v\in V, w\in W to an element of V \otime ...
s of finite-dimensional representations of general linear groups, or in the decomposition of certain induced representations in the representation theory of the symmetric group, or in the area of
algebraic combinatorics Algebraic combinatorics is an area of mathematics that employs methods of abstract algebra, notably group theory and representation theory, in various combinatorial contexts and, conversely, applies combinatorial techniques to problems in alg ...
dealing with
Young tableaux In mathematics, a Young tableau (; plural: tableaux) is a combinatorial object useful in representation theory and Schubert calculus. It provides a convenient way to describe the group representations of the symmetric and general linear groups and ...
and
symmetric polynomials In mathematics, a symmetric polynomial is a polynomial in variables, such that if any of the variables are interchanged, one obtains the same polynomial. Formally, is a ''symmetric polynomial'' if for any permutation of the subscripts one h ...
. Littlewood–Richardson coefficients depend on three partitions, say \lambda,\mu,\nu, of which \lambda and \mu describe the Schur functions being multiplied, and \nu gives the Schur function of which this is the coefficient in the linear combination; in other words they are the coefficients c_^\nu such that :s_\lambda s_\mu=\sum_\nu c_^\nu s_\nu. The Littlewood–Richardson rule states that c_^\nu is equal to the number of Littlewood–Richardson tableaux of skew shape \nu/\lambda and of weight \mu.


History

The Littlewood–Richardson rule was first stated by but though they claimed it as a theorem they only proved it in some fairly simple special cases. claimed to complete their proof, but his argument had gaps, though it was so obscurely written that these gaps were not noticed for some time, and his argument is reproduced in the book . Some of the gaps were later filled by . The first rigorous proofs of the rule were given four decades after it was found, by and , after the necessary combinatorial theory was developed by , , and in their work on the Robinson–Schensted correspondence. There are now several short proofs of the rule, such as , and using Bender-Knuth involutions. used the Littelmann path model to generalize the Littlewood–Richardson rule to other semisimple Lie groups. The Littlewood–Richardson rule is notorious for the number of errors that appeared prior to its complete, published proof. Several published attempts to prove it are incomplete, and it is particularly difficult to avoid errors when doing hand calculations with it: even the original example in contains an error.


Littlewood–Richardson tableaux

A Littlewood–Richardson tableau is a skew semistandard tableau with the additional property that the sequence obtained by concatenating its reversed rows is a lattice word (or lattice permutation), which means that in every initial part of the sequence any number i occurs at least as often as the number i+1. Another equivalent (though not quite obviously so) characterization is that the tableau itself, and any tableau obtained from it by removing some number of its leftmost columns, has a weakly decreasing weight. Many other combinatorial notions have been found that turn out to be in bijection with Littlewood–Richardson tableaux, and can therefore also be used to define the Littlewood–Richardson coefficients.


Example

Consider the case that \lambda=(2,1), \mu=(3,2,1) and \nu=(4,3,2). Then the fact that c_^\nu=2 can be deduced from the fact that the two tableaux shown at the right are the only two Littlewood–Richardson tableaux of shape \nu/\lambda and weight \mu. Indeed, since the last box on the first nonempty line of the skew diagram can only contain an entry 1, the entire first line must be filled with entries 1 (this is true for any Littlewood–Richardson tableau); in the last box of the second row we can only place a 2 by column strictness and the fact that our lattice word cannot contain any larger entry before it contains a 2. For the first box of the second row we can now either use a 1 or a 2. Once that entry is chosen, the third row must contain the remaining entries to make the weight (3,2,1), in a weakly increasing order, so we have no choice left any more; in both case it turns out that we do find a Littlewood–Richardson tableau.


A more geometrical description

The condition that the sequence of entries read from the tableau in a somewhat peculiar order form a lattice word can be replaced by a more local and geometrical condition. Since in a semistandard tableau equal entries never occur in the same column, one can number the copies of any value from right to left, which is their order of occurrence in the sequence that should be a lattice word. Call the number so associated to each entry its index, and write an entry ''i'' with index ''j'' as ''i'' 'j'' Now if some Littlewood–Richardson tableau contains an entry i>1 with index ''j'', then that entry ''i'' 'j''should occur in a row strictly below that of (i-1) /math> (which certainly also occurs, since the entry ''i'' − 1 occurs as least as often as the entry ''i'' does). In fact the entry ''i'' 'j''should also occur in a column no further to the right than that same entry (i-1) /math> (which at first sight appears to be a stricter condition). If the weight of the Littlewood–Richardson tableau is fixed beforehand, then one can form a fixed collection of indexed entries, and if these are placed in a way respecting those geometric restrictions, in addition to those of semistandard tableaux and the condition that indexed copies of the same entries should respect right-to-left ordering of the indexes, then the resulting tableaux are guaranteed to be Littlewood–Richardson tableaux.


An algorithmic form of the rule

The Littlewood–Richardson as stated above gives a combinatorial expression for individual Littlewood–Richardson coefficients, but gives no indication of a practical method to enumerate the Littlewood–Richardson tableaux in order to find the values of these coefficients. Indeed, for given \lambda,\mu,\nu there is no simple criterion to determine whether any Littlewood–Richardson tableaux of shape \nu/\lambda and of weight \mu exist at all (although there are a number of necessary conditions, the simplest of which is , \lambda, +, \mu, =, \nu, ); therefore it seems inevitable that in some cases one has to go through an elaborate search, only to find that no solutions exist. Nevertheless, the rule leads to a quite efficient procedure to determine the full decomposition of a product of Schur functions, in other words to determine all coefficients c_^\nu for fixed λ and μ, but varying ν. This fixes the weight of the Littlewood–Richardson tableaux to be constructed and the "inner part" λ of their shape, but leaves the "outer part" ν free. Since the weight is known, the set of indexed entries in the geometric description is fixed. Now for successive indexed entries, all possible positions allowed by the geometric restrictions can be tried in a
backtracking Backtracking is a class of algorithms for finding solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons a candidate ("backtracks") as soon as it d ...
search. The entries can be tried in increasing order, while among equal entries they can be tried by ''decreasing'' index. The latter point is the key to efficiency of the search procedure: the entry ''i'' 'j''is then restricted to be in a column to the right of i +1/math>, but no further to the right than i-1 /math> (if such entries are present). This strongly restricts the set of possible positions, but ''always leaves at least one valid position for i /math>''; thus every placement of an entry will give rise to at least one complete Littlewood–Richardson tableau, and the
search tree In computer science, a search tree is a tree data structure used for locating specific keys from within a set. In order for a tree to function as a search tree, the key for each node must be greater than any keys in subtrees on the left, and less ...
contains no dead ends. A similar method can be used to find all coefficients c_^\nu for fixed λ and ν, but varying μ.


Littlewood–Richardson coefficients

The Littlewood–Richardson coefficients ''c''   appear in the following interrelated ways: *They are the structure constants for the product in the ring of symmetric functions with respect to the basis of Schur functions ::s_\lambda s_\mu =\sum c_^\nu s_\nu :or equivalently ''c''   is the inner product of ''s''''ν'' and ''s''''λ''''s''''μ''. *They express
skew Schur function In mathematics, Schur polynomials, named after Issai Schur, are certain symmetric polynomials in ''n'' variables, indexed by partitions, that generalize the elementary symmetric polynomials and the complete homogeneous symmetric polynomials. In ...
s in terms of Schur functions ::s_ =\sum _\mu c_^\nu s_\mu. *The ''c''   appear as intersection numbers on a
Grassmannian In mathematics, the Grassmannian is a space that parameterizes all -dimensional linear subspaces of the -dimensional vector space . For example, the Grassmannian is the space of lines through the origin in , so it is the same as the projective ...
: ::\sigma_\lambda \sigma_\mu =\sum c_^\nu \sigma_\nu :where ''σ''''μ'' is the class of the
Schubert variety In algebraic geometry, a Schubert variety is a certain subvariety of a Grassmannian, usually with singular points. Like a Grassmannian, it is a kind of moduli space, whose points correspond to certain kinds of subspaces ''V'', specified using line ...
of a Grassmannian corresponding to ''μ''. *''c''   is the number of times the irreducible representation ''V''''λ'' ⊗ ''V''''μ'' of the product of symmetric groups ''S'', ''λ'', × ''S'', ''μ'', appears in the restriction of the representation ''V''''ν'' of ''S'', ''ν'', to ''S'', ''λ'', × ''S'', ''μ'', . By
Frobenius reciprocity In mathematics, and in particular representation theory, Frobenius reciprocity is a theorem expressing a duality between the process of restricting and inducting. It can be used to leverage knowledge about representations of a subgroup to find ...
this is also the number of times that ''V''''ν'' occurs in the representation of ''S'', ''ν'', induced from ''V''''λ'' ⊗ ''V''''μ''. *The ''c''   appear in the decomposition of the tensor product of two
Schur module Schur is a German or Jewish surname. Notable people with the surname include: * Alexander Schur (born 1971), German footballer * Dina Feitelson-Schur (1926–1992), Israeli educator * Friedrich Schur (1856-1932), German mathematician * Fritz Sch ...
s (irreducible representations of special linear groups) ::E^\lambda \otimes E^\mu =\bigoplus_\nu (E^\nu)^. *''c''   is the number of standard Young tableaux of shape ''ν''/''μ'' that are jeu de taquin equivalent to some fixed standard Young tableau of shape ''λ''. *''c''   is the number of Littlewood–Richardson tableaux of shape ''ν''/''λ'' and of weight ''μ''. *''c''   is the number of
pictures An image is a visual representation of something. It can be two-dimensional, three-dimensional, or somehow otherwise feed into the visual system to convey information. An image can be an artifact, such as a photograph or other two-dimension ...
between μ and ν/λ.


Special cases


Pieri's formula

Pieri's formula, which is the special case of the Littlewood–Richardson rule in the case when one of the partitions has only one part, states that : S_\mu S_n=\sum_\lambda S_\lambda where ''S''''n'' is the Schur function of a partition with one row and the sum is over all partitions λ obtained from μ by adding ''n'' elements to its
Ferrers diagram In number theory and combinatorics, a partition of a positive integer , also called an integer partition, is a way of writing as a sum of positive integers. Two sums that differ only in the order of their summands are considered the same part ...
, no two in the same column.


Rectangular partitions

If both partitions are rectangular in shape, the sum is also multiplicity free . Fix ''a'', ''b'', ''p'', and ''q'' positive integers with ''p'' \geq ''q''. Denote by (a^p) the partition with ''p'' parts of length ''a''. The partitions indexing nontrivial components of s_s_ are those partitions \lambda with length \leq p+q such that *\lambda_ = \lambda_ = \cdots = \lambda_p = a, *\lambda_q \geq \mathrm(a,b) *\lambda_i + \lambda_ = a+b, \quad . For example, .


Generalizations


Reduced Kronecker coefficients of the symmetric group

The reduced Kronecker coefficient of the symmetric group \bar_ is a generalization of c_^\nu to three arbitrary Young diagrams \lambda,\mu,\nu, which is symmetric under permutations of the three diagrams.


Skew Schur functions

extended the Littlewood–Richardson rule to skew Schur functions as follows: :s_\lambda s_ = \sum_s_ where the sum is over all tableaux ''T'' on μ/ν such that for all ''j'', the sequence of integers λ+ω(''T''≥''j'') is non-increasing, and ω is the weight.


Newell-Littlewood numbers

Newell-Littlewood numbers are defined from Littlewood–Richardson coefficients by the cubic expression : N_ = \sum_ c_^\mu c_^\nu c_^\lambda Newell-Littlewood numbers give some of the tensor product multiplicities of finite-dimensional representations of classical Lie groups of the types B, C, D. The non-vanishing condition on Young diagram sizes c_^\nu\neq 0 \implies , \lambda, +, \mu, =, \nu, leads to : N_\neq 0 \implies \left\{\begin{array}{l}, , \lambda, -, \mu, , \leq , \nu, \leq , \lambda, +, \mu, \\ , \lambda, +, \mu, +, \nu, \in 2\mathbb{Z} \end{array}\right. Newell-Littlewood numbers are generalizations of Littlewood–Richardson coefficients in the sense that : , \mu, +, \nu, =, \lambda, \implies N_{\mu,\nu,\lambda} = c_{\mu,\nu}^\lambda Newell-Littlewood numbers that involve a Young diagram with only one row obey a Pieri-type rule: N_{(k),\mu,\nu} is the number of ways to remove \frac{k+, \mu, -, \nu{2} boxes from \mu (from different columns), then add \frac{k-, \mu, +, \nu{2} boxes (to different columns) to make \nu. Newell-Littlewood numbers are the structure constants of an associative and commutative algebra whose basis elements are partitions, with the product \mu\times \nu = \sum_\lambda N_{\mu,\nu,\lambda}\lambda. For example, : (1)\times (k) = (k-1) + (k+1) + (k,1) \quad \text{(Newell–Littlewood)} : (1)\times (k) = (k+1) + (k,1) \quad \text{(Littlewood–Richardson)}


Examples

The examples of Littlewood–Richardson coefficients below are given in terms of products of Schur polynomials ''S''π, indexed by partitions π, using the formula :S_\lambda S_\mu =\sum c_{\lambda\mu}^\nu S_\nu. All coefficients with ν at most 4 are given by: *''S''0''S''π = ''S''π for any π. where ''S''0=1 is the Schur polynomial of the empty partition *''S''1''S''1 = ''S''2 + ''S''11 *''S''2''S''1 = ''S''3 + ''S''21 *''S''11''S''1 = ''S''111 + ''S''21 *''S''3''S''1 = ''S''4 + ''S''31 *''S''21''S''1 = ''S''31 + ''S''22 + ''S''211 *''S''2''S''2 = ''S''4 + ''S''31 + ''S''22 *''S''2''S''11 = ''S''31 + ''S''211 *''S''111''S''1 = ''S''1111 + ''S''211 *''S''11''S''11 = ''S''1111 + ''S''211 + ''S''22 Most of the coefficients for small partitions are 0 or 1, which happens in particular whenever one of the factors is of the form ''Sn'' or ''S''11...1, because of Pieri's formula and its transposed counterpart. The simplest example with a coefficient larger than 1 happens when neither of the factors has this form: *''S''21''S''21 = ''S''42 + ''S''411 + ''S''33 + 2''S''321 + ''S''3111 + ''S''222 + ''S''2211. For larger partitions the coefficients become more complicated. For example, *''S''321''S''321 = ''S''642 +''S''6411 +''S''633 +2''S''6321 +''S''63111 +''S''6222 +''S''62211 +''S''552 +''S''5511 +2''S''543 +4''S''5421 +2''S''54111 +3''S''5331 +3''S''5322 +4''S''53211 +''S''531111 +2''S''52221 +''S''522111 +''S''444 +3''S''4431 +2''S''4422 +3''S''44211 +''S''441111 +3''S''4332 +3''S''43311 +4''S''43221 +2''S''432111 +''S''42222 +''S''422211 +''S''3333 +2''S''33321 +''S''333111 +''S''33222 +''S''332211 with 34 terms and total multiplicity 62, and the largest coefficient is 4 *''S''4321''S''4321 is a sum of 206 terms with total multiplicity is 930, and the largest coefficient is 18. *''S''54321''S''54321 is a sum of 1433 terms with total multiplicity 26704, and the largest coefficient (that of ''S''86543211) is 176. *''S''654321''S''654321 is a sum of 10873 terms with total multiplicity is 1458444 (so the average value of the coefficients is more than 100, and they can be as large as 2064). The original example given by was (after correcting for 3 tableaux they found but forgot to include in the final sum) *''S''431''S''221 = ''S''652 + ''S''6511 + ''S''643 + 2''S''6421 + ''S''64111 + ''S''6331 + ''S''6322 + ''S''63211 + ''S''553 + 2''S''5521 + ''S''55111 + 2''S''5431 + 2''S''5422 + 3''S''54211 + ''S''541111 + ''S''5332 + ''S''53311 + 2''S''53221 + ''S''532111 + ''S''4432 + ''S''44311 + 2''S''44221 + ''S''442111 + ''S''43321 + ''S''43222 + ''S''432211 with 26 terms coming from the following 34 tableaux:
....11 ....11 ....11 ....11 ....11 ....11 ....11 ....11 ....11    
...22  ...22  ...2   ...2   ...2   ...2   ...    ...    ...
.3     .      .23    .2     .3     .      .22    .2     .2     
       3             3      2      2      3      23     2      
                                   3                    3

....1  ....1  ....1  ....1  ....1  ....1  ....1  ....1  ....1   
...12  ...12  ...12  ...12  ...2   ...1   ...1   ...2   ...1
.23    .2     .3     .      .13    .22    .2     .1     .2      
       3      2      2      2      3      23     23     2
                     3                                  3

....1  ....1  ....1  ....1  ....1  ....1  ....1  ....1   
...2   ...2   ...2   ...    ...    ...    ...    ...    
.1     .3     .      .12    .12    .1     .2     .2      
2      1      1      23     2      22     13     1
3      2      2             3      3      2      2
              3                                  3

....   ....   ....   ....   ....   ....   ....   ....   
...1   ...1   ...1   ...1   ...1   ...    ...    ...    
.12    .12    .1     .2     .2     .11    .1     .1      
23     2      22     13     1      22     12     12
       3      3      2      2      3      23     2
                            3                    3
Calculating skew Schur functions is similar. For example, the 15 Littlewood–Richardson tableaux for ν=5432 and λ=331 are
...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11 ...11
...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2  ...2
.11   .11   .11   .12   .11   .12   .13   .13   .23   .13   .13   .12   .12   .23   .23
12    13    22    12    23    13    12    24    14    14    22    23    33    13    34
so ''S''5432/331 = Σ''c''  ''S''μ = ''S''52 + ''S''511 + ''S''4111 + ''S''2221 + 2''S''43 + 2''S''3211 + 2''S''322 + 2''S''331 + 3''S''421 .


Notes


References

* * * * * * * * * * Zentralblatt MATH, Zbl
0019.25102
* * * * * * *


External links


An online program
decomposing products of Schur functions using the Littlewood–Richardson rule {{DEFAULTSORT:Littlewood-Richardson rule Algebraic combinatorics Invariant theory Representation theory Symmetric functions