Two poset polytopes

Discrete & Computational Geometry, Mar 1986

Two convex polytopes, called theorder polytope ϑ(P) andchain polytope ℒ(P), are associated with a finite posetP. There is a close interplay between the combinatorial structure ofP and the geometric structure of ϑ(P). For instance, the order polynomial Ω(P, m) ofP and Ehrhart polynomiali(ϑ(P),m) of ϑ(P) are related by Ω(P, m+1)=i(ϑ(P),m). A “transfer map” then allows us to transfer properties of ϑ(P) to ℒ(P). In particular, we transfer known inequalities involving linear extensions ofP to some new inequalities.

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Two poset polytopes

Received Februaty Two Poset Polytopes 0 Richard P. Stanley 0 0 Department of Mathematics, Massachusetts Institute of Technology , Cambridge, MA 02139 , USA Two convex polytopes, called the orderpolytope d)(P) and chain polytope <~(P), are associated with a finite poset P. There is a close interplay between the combinatorial structure of P and the geometric structure of E~(P). For instance, the order polynomial fl(P, m) of P and Ehrhart polynomial i(~9(P),m) of O(P) are related by f~(P,m+l)=i(d)(P),m). A "transfer m a p " then allows us to transfer properties of O(P) to W(P). In particular, we transfer known inequalities involving linear extensions of P to some new inequalities. - Our aim is to investigate two convex polytopes associated with a finite partially ordered set (poset) P. The first of these, which we call the "order polytope" and denote by O(P), has been the subject of considerable scrutiny, both explicit and implicit, Much of what we say about the order polytope will be essentially a review of well-known results, albeit ones scattered throughout the literature, sometimes in a rather obscure form. The second polytope, called the "chain polytope" and denoted i f ( P ) , seems never to have been previously considered per se. It is a special case of the vertex-packing polytope of a graph (see Section 2) but has many special properties not in general valid or meaningful for graphs. There is a surprising connection (Section 3) between (P(P) and (~(P) which will allow us to " t r a n s f e r " properties of O(P) over to r ( ( p ) . Given the poset P = {x 1. . . . . x , } (where by standard abuse of notation we identify p with its set of points), the set R e of all functions f : P---, R is an n-dimensional real vector space with a scalar product defined by ( f , g ) = ~-.~Ej ( x ) g ( x ) , which makes R e a Euclidean space. In particular, we can talk about convex subsets of R p and their volumes, orthogonal projections, etc. *Partiallysupportedby NSF Grant No. 8104855-MCSand by a GuggenheimFellowship. Definition 1.1. The order polytope d)(P) of the poset P is the subset of R p defined by the conditions 0 < f ( x ) < 1, f ( x ) < f ( y ) for all x e P, i f x < y in P. ( 1 ) ( 2 ) (1') (2') (3a) (3b) (3c) N o t e that O ( P ) is a convex polytope since it is defined by linear inequalities and is bounded because of ( 1 ). Clearly, because of ( 2 ), we can replace ( 1 ) by the conditions 0 < f ( x ) , if x is a minimal element of P, f ( x ) < 1, if x is a maximal element of P. f ( x ) < f ( y ) if y covers x in P. By the transitivity of P, we can replace ( 2 ) by the equivalent conditions Let o: P ~ {1..... n } be a linear extension (order-preserving bijection) of P. We identify a with the permutation Yl. . . . . Yn of the elements x 1..... x n of P defined by o(y,) = i. All functions f ~ R e satisfying 0 < f ( Y l ) < "'" < f(Yn) < 1 belong to 0 ( P ) . These functions form an n-dimensional simplex, so we conclude dim t V ( P ) = n. It is easily seen that conditions (1') and (2') are independent, so they define the facets [(n -1)-dimensional faces] of 0 ( P ) . More precisely a facet of O ( P ) consists of those f ~d~(P) satisfying exactly one of the following conditions: f ( x ) = 0, f ( x ) = 1, f ( x ) = f ( y ) , for some minimal x ~ P, for some maximal x ~ P, for some y covering x in P. It is convenient to state the above conditions in a more uniform way. Let be the poset obtained from P by adjoining a minimum element 0 and a maximum element i. Define a polytope ~ ( P ) to be the set of functions g ~ R ~' satisfying g( 0 ) = 0, g ( x ) <_ g ( y ) g ( i ) = 1, if x _< y in ,b. The linear map P: ~ ( P ) -* O ( P ) obtained by restriction to P is clearly a bijection and hence (since P is linear) defines a combinatorial equivalence of polytopes. Thus by ( 3 ) a facet of O ( P ) consists of those g ~ ~ ( P ) satisfying g(x) = g(y) for some fixed pair (x, y)~ for which y covers x in P. In particular, the number of facets of O ( P ) or O ( P ) is the number c ( t ' ) of cover relations in P, or equivalently c(P)+ a+ b, where P has a minimal elements and b maximal elements. We now wish to determine the entire facial structure of t~(P), or equivalently of 0 ( P ) . Since every face is an intersection of facets, it follows that a face F,~ of ~ ( P ) corresponds to certain partitions ~r= {B 1. . . . . Bk} of P into nonempty pairwise disjoint blocks, viz., F,~ = ( g ~ ~ ( P ) : g is constant on the blocks Bi of Ir }. ( 4 ) It r e m a i n s to d e t e r m i n e for which rr F,~ is a face, and which are the distinct faces F., Call i r a face partition if F,, is a face of P. It is clear that if ~r is a face partition, then ~r is connected, i.e., every block B of ~r is connected as an (induced) s u b p o s e t of P. Call a partition ~r = { B 1. . . . . B k } closed if for any i 4= j there is g ~ F~ such that g(Bi) ~ g(Bj). Every partition ~r has a unique coarsening ~ for which ~ is closed and F , = F ~ . Moreover, if ~ r ~ [ B 1. . . . . Bk} is a closed face partition then dim F~ = k - 2 [since if (~~ B, and 1 ~ By then g ~ F~ satisfies g ( B i ) = 0 and g ( B j ) = 1]. H e n c e it remains to describe the closed face partitions. This description was a p p a r e n t l y first explicitly observed by Geissinger [6]. W e will state Geissinger's result below ( T h e o r e m 1.2) but will omit the rather straightforward proof. Define a b i n a r y relation < ~ on ~r by setting B, < Bj if x _< y for some x ~ B i and y ~ By. Call ~r compatible if the transitive closure of < ~ is a partial order (i.e., is antisymmetric). If ~r is c o m p a t i b l e then every block B of sv is convex; i.e., if x, z ~ B a n d x < y < z.. then y ~ B. The converse is false; e.g., let I ' be given by Fig. 1. T h e partition into blocks 0, ad, bc, 1 is connected and convex, but not compatible. T h e o r e m 1.2. A partition of P is a closed face partition if and on~ if it is connected and compatible. (In particular, the partition ~r into a single block P yields the empty set F, = 0 , which we regard as a face.) T h u s the lattice of faces 0 ( P ) [or (~(P)] is isomorphic to the lattice of connected c o m p a t i b l e partitions of P, ordered by reverse refinement. F o r instance, if P = { a, b } is a two-element antichain, then d~(P) is a square and Fig. 2 depicts its face lattice (with (~ and ] written 0 and 1). Define a filter (or dual order ideal, up-set, or increasing subset) of P to be a subset I of P such that if x ~ I and y > x, then y ~ I. Let XI: P ~ R denote the Oo-b-I~ Oob-i O-o-bl ~ Ob-a-! Ob-ol characteristic function of I; i.e., x ~ ( x ) = The following corollary is immediate from Theorem 1.2 and can also be easily proved directly. Corollary 1.3. The vertices of tP(P) are the characteristic functions XI of filters I of P. In particular, the number of vertices of t~(P) is the number of filters of P. The Chain Polytope Let us define a second polytope associated with a poset P = {x 1..... x , }. Definition 2.1. The chain polytope ~ ( P ) of the poset P is the subset of R e defined by the conditions 0 < g ( x ) , for all x ~ P , g ( Y l ) + ' ' ' + g ( Y k ) --<1, for every chain yl < "'" < Yk ° f P " ( 5 ) ( 6 ) Again it is clear that ~ ( P ) is a convex polytope. Since f~(P) contains the n-dimensional simplex { g ~ R P : g(x) >0 for all x ~ P and g ( x l ) + . . . + g ( x , ) < 1}, we have d i m ~ ( P ) = n. In view of ( 5 ) we can replace ( 6 ) by g ( Y l ) + ' ' " + g(Yk) < 1, for every maximal chain Yl < " " " < Yk of P. ( 6 ' ) Conditions ( 5 ) and (6') are easily seen to be independent and thus define the facets of ~ ( P ) . In particular, the number of facets of ~ ( P ) is equal to n + m(P), where re(P) is the number of maximal chains of P. A description of the faces of ~ ( P ) analogous to Theorem 1.2 seems messy and will not be pursued here. However, we do have a simple description of the vertices analogous to Corollary 1.3. Define an antichain of P to be a subset A of pairwise incomparable elements of P. Theorem 2.2. The vertices of ~¢(P) are the characteristic functions XA of antichains of P. In particular, the number of vertices of T ( P ) is equal to the number of antichains of P. Proof. Clearly each XA ~ ~¢(P)" Since 0 < g(x) < 1 for all g ~ ~ ( P ) and x ~ P, it follows that XA is a vertex of i f ( P ) . Conversely, suppose g ~ ~ ( P ) and g ~ XA for any antichain A of P. Let Q = ( x ~ P: 0 < g ( x ) <1}. Let Q1 be the set of minimal elements of Q and Q2 the set of minimal dements of Q - Q r One easily sees that since g ~ XA, Q1 and Q2 are nonempty. Define Define gl, g2: P ~ R by = m i n { g ( x ) , l - g ( x ) : x ~ Q i u Q 2 }. g , ( x ) = ( g ( x ) , x q~Qi u Q2 ~ g ( x ) - e , xEQ2, ( g ( x ) , gz(x) = ( g ( x ) - e , [g(x)+e, xq~PluO2 x~O1 x~Q2. It is clear that gi, g2 E ~g(P). Since gl 4:g2 and g = ½(gi + g2), it follows that g is not a vertex of ~ ( P ) . [] Theorem 2.2 is already known within a graph-theoretical context. Let G be a graph (with no loops and multiple edges) on a vertex set V = ( x 1. . . . . x,,}. Let ~/'(G) _c R v denote the convex hull of the characteristic functions XA of independent (stable) sets A of vertices; i.e., no two vertices in A are adjacent in G. Then U ( G ) is called the vertex-packingpotytope of G. In particular, given a poset P define its comparabilitygraph C o m ( P ) to be the graph whose vertices are the elements of P, with x, y ~ P adjacent if x < y or y < x. Then an independent set of vertices of C o m ( P ) is just an antichain A of P, so by Theorem 2.2 we have U ( C o m ( P ) ) = c~(p). But since comparability graphs are perfect (e.g., [6, Thm. 5.34]) it follows from [2, Thin. 3.1] (or see [7, Thm. 3.14]) that the facets of U ( C o m ( P ) ) are given by ( 5 ) and (6'). There is a well-known bijection between filters I and antichains A of P, viz., I = ( y : y > x f o r s o m e x ~ A } , A = set of minimal dements of I. Thus from Corollary 1.3 and Theorem 2.2 it follows that O ( P ) and ¢g(P) have the same number of vertices. In general, however, O ( P ) and cg(p) need not have the same number of /-dimensional faces for i > 0 (and hence need not be combinatorially equivalent). For instance, if P is given by Fig. 3, then O ( P ) has eight facets and oK(p) has nine facets. There is, however, one class of posets for which O ( P ) and cg(p) are in fact combinatorially equivalent. Theorem 2.3. Suppose P has length at most one (i.e., P has no three-element chains). Then O( P ) and cg( p ) are affinely equivalent and hence combinatorially equivalent. Proof Define a nonsingular affine transformation f: R e ___,R e by ( ~ f ) ( x ) = ( f ( x ) , l - f ( x ) , if x is a minimal element of P otherwise It is routine to check that the image of 0 ( P ) under ~ is ~ ( P ) , and the proof follows. [] In Section 4 we generalize the fact that for any P, O(P) and ~ ( P ) have the same number of vertices. A Connection Between O(P) and ~ ( P ) In this section we construct a map q~: O ( P ) --, g ( P ) with several nice properties. This will allow us to transfer certain properties of 0 ( P ) over to i f ( P ) . Definition 3.1. Let P be a finite poset, and define the transfer map ¢p: ¢ ( P ) --* ~ ( P ) as follows: If f ~ 0 ( P ) and x ~ P then (epf ) ( x ) = rnin{ f ( x ) - f ( y ) : x covers y in P } . ( 7 ) Theorem 3.2. (a) The transfer map qJ is a continuous, piecewise-linear bijection from O ( P ) onto cg(p). (b) Let m be a positive integer and f ~ O( P). Then m f ( x ) ~ 7_ for all x ~ P if and only if m ( q~f)( x ) ~ Z for all x ~ P. Proof. (a) Continuity is immediate from the definition ( 7 ). Moreover, for each linear extension Yl..... yn of P, q~is linear on the simplex defined by 0 < f ( Y l ) <• .. < f ( y , ) < 1 . Since these simplices dearly cover 0 ( P ) , it follows that q~ is piecewise-linear. Now define q~: T ( P ) ---,0 ( P ) by ( ~ g ) ( x ) = m a x { g ( y l ) + - - . + g ( y k ) : Yt < ' ' " < Y* = X } " One checks that ( q ~ f f ) f = f and ( ~ q , ) g = g for all f ~ 0 ( P ) Hence ~ is a bijection (with inverse ~k). (b) This result is immediate from ( 7 ) and ( 8 ). and g ~ ( P ) . ( 8 ) [] The Ehrhart Polynomial Let ~ be a d-dimensional convex polytope in R n with integer vertices. If m is a positive integer then define i ( ~ , m ) = c a r d ( m ~ n Z " ) . In other words, i ( ~ , m) is equal to the number of points a ~ ~ such that mct~ Z ' . It is known that i ( ~ , m) is a polynomial function of m of degree d, called the Ehrhart polynomial of ~ . When d = n the leading coefficient of i ( ~ , m) is the volume V ( ~ ) of ~ . For these and other facts concerning i ( ~ , m), see, e.g., [15]. Now let P be a finite n-element poset and m a positive integer and define f l ( P , m) to be the number of order-preserving maps ,/: P ~ (1 ..... m ) ; i.e., if x _< y in P then 71(x) < */(y). Then f~(P, m) is a polynomial function of m of degree n, called the order polynomial of P. The leading coefficient of ~2(P, m) is e ( P ) / n ! , where e ( P ) is the number of linear extensions of P. For these and other facts concerning ~2(P, m), see, e.g., [12] and [13, Sections 13 and 19]. Theorem 4.1. The Ehrhart polynomials of (9(P ) and ~ ( P ) are given by i ( ( 9 ( P ) , m ) = i ( ~ ( P ) , m ) = ~ ( P , m + l ) . Proof By definition, i(O(P), m) is equal to the number of order-preserving maps f : P ---,R satisfying 0 < f ( x ) < 1 and m f ( x ) ~ Z for all x ~ P. This is equivalent to the condition that mf: P ~ (0,1 . . . . . m} is order-preserving, so i(O(P), m) = ~2(P, m +1). But Theorem 3.2(b) implies that i(O(P), m) = i ( ~ ( P ) , m), and the proof follows. [] Since the leading coefficient of i ( ~ , m ) is V ( ~ ) (when d i m # = n and c R n) and that of ~2(P, m + 1 ) is e ( P ) / n ! , there follows Corollary 4.2. The volumes of O( P ) and cg( p ) are given by V ( O ( P ) ) = V ( ~ ( P ) ) = e(P)/n!. It would be interesting to find other vertex-packing polytopes whose volumes have a simple combinatorial interpretation. Let us also mention that a method similar to the proof of Corollary 4.2 for showing that two convex polytopes have the same volume appears in [14]. Example 4.3. Let F, denote the n-element fence, i.e., the poset with elements x 1. . . . . x , and cover relations x, < Xi+l , i f i i s o d d , x, > xi+l, i f i i s e v e n . A bijection o: F, ~ (1 ..... n } is order-preserving if and only if the permutation o ( x l ) , o ( x 2 ) . . . . . o ( x , ) of (1 . . . . . n} is alternating, i.e., o ( x l ) < o(x2) > o(x3) < • . • . Hence e ( F , ) is the number E , of alternating permutations of (1 ..... n }. E , is an Euler number and is well-known (e.g., [3, pp. 258-259]) to satisfy E n x n Y'. ~ n>_0 = secx + t a n x . T h e chain polytope ff(Fn) may be identified with the set of all vectors (Yl . . . . . Y,) R" satisfying ( 9 ) (10) Yi > 0, 1 < i < n, and y~ + y~+x < 1, l < i < n - 1 . V,x" = secx + tan x. It follows from Corollary 4.2 that the volume Vn of the set ( 9 ) satisfies Equation (10) was first given in [10] (see also [4]). With almost no effort we obtain the following interesting corollary of T h e o r e m 4.1. Corollary 4.4. The order polynomial f~(P, m) of a finite poset P depends only on the comparability graph C o m ( P ) of P. Proof. By Theorem 4.1 we have f ~ ( P , m + l ) = i ( ~ ( P ) , m ) , and by definition ~ ( P ) depends only on C o m ( P ) . [] In particular, the leading coefficient of f~(P, m) depends only on C o m ( P ) , and we obtain Corollary 4.5. The number e ( P ) of finear extension of P depends only on C o m ( P ) . Corollary 4.5 was first stated in [7, p. 139]. Its proof was based on a condition as to when C o m ( P ) = Com(Q). This condition appears to be implicit in the work of Gallai and others, but was apparently first explicitly stated in [5], and is given as follows: Suppose P contains a poset P ' such that for all x ~ P - P', either (a) x < y for all y ~ P', (b) x > y for all y ~ P', or (c) x and y are incomparable for all y ~ P'. Define P: to be the poset obtained from P by dualizing P'; i.e., x < y in P1 if and only if either (a) not both x ~ P ' and y ~ P ' , and x < y in P, or (b) x and y ~ P ' and x > y in P. Call P1 a simple transform of P. Then C o m ( P ) = C o m ( Q ) if and only if there is a sequence P = P0, P1 . . . . . Pk = Q of posets such that each P~+I is a simple transform of Pg. It is then easy to check that simple transforms have the same number of linear extensions, so Corollary 4.5 follows. In fact, it is just as easy to check that simple transforms have the same order polynomials, so Corollary 4.4 also follows. For another proof of Corollary 4.5 and additional references, see [8]. N o t e that the proof we gave of Corollary 4.4 really has nothing to do with convex polytopes. To see this, define for m > 1 the chain polynomial F ( P , m) to be the number of maps g: P -o {0,1,2 .... } such that g ( y l ) + . - . + g(Yk) < m -- 1 for all chains y: < . . . < Yk of P. Then ( 7 ) defines a bijection between order-preserving maps f : P ~ {0. . . . . m - 1 } and maps q~f: P - o {0,1 .... } enumerated by F ( P , m). Hence f~(P, m) = r ( P , m). But F ( P , m) depends only on C o m ( P ) , so the same is true for f~(P, m). Two PosetPolytopes Of course Corollary 4.4 may be extended to the statement that any invariant of P which can be computed in terms of cg(p) depends only on Com(P). In Corollary 6.3 we will see another example of such an invariant. Corollary 4.4 and its proof suggest that the combinatorial type of 0 ( P ) itself may depend only on Com(P). However, if P is given by Fig. 3 then there is easily seen to be a poset Q satisfying C o m ( P ) = Corn(Q) such that O(Q) has nine facets, while ¢9(P) has eight facets. 5. T r i a n g u l a t i o n s The polytope ¢ ( P ) has a canonical triangulation which can be transferred to i f ( P ) . We describe this procedure in this section and give an application in the next. An order ideal of P is a subset I of P such that if x ~ I and y _<x, then y ~ I. Let J ( P ) denote the poset (actually a distributive lattice) of order ideals of P, ordered by inclusion. Let K : I ~ c I 2 c . " c l k be a chain in J ( P ) (where/,-1 c I i means t h a t / i - t is strictly contained in //). Define a set FK ~ R e by FK = ( f ~ R e: (a) f is constant on the subsets I1, 12 - I1. . . . . Ik -- Ik--1' P -- Ik of P, and (b) 0 = f ( I 1 ) <-f(12-11)-< " " <-f(P-Ik) = 1 ) . Then F~: is a (k - 1)-dimensional simplex contained in 0 ( P ) , and the set { FK: K is a chain of J ( P ) } is a triangulation A ( P ) of O(P). [The empty chain K corresponds to the empty face of A(P).] In particular, the facets (maximal faces) of A ( P ) are given by 0 < f ( y , ) < . . . < f ( y , ) ~ 1, ( 11 ) where y~.... , y, is a linear extension of P. The number of facets is e ( P ) and each has volume 1 / n !, giving another proof that V( O( P )) = e ( P )/ n !. For any poset Q define the order complex A(Q) [1, Section 3] to be the abstract simplicial complex on Q whose faces are the chains of Q. Hence, as an abstract simplicial complex, A ( P ) is isomorphic to A ( J ( p ) ) . In particular, the geometric realization [A(J(p))[ of A ( J ( p ) ) is an n-cell, a result which also follows from very general considerations [11, Corollary 3.4.3] but here is explained more concretely. It follows from the definition ( 7 ) of the transfer map ~ that q~ is linear on each face Fx of A ( P ) . Hence q~(FK) is a simplex, and (since q~ is continuous) the set {q~(FK): Fx ~ A(P)} is a triangulation q~F(e) of oK(p). By applying q~to the facet ( 11 ) of A ( P ) , an explicit description of the facets of q,A(P) can be deduced. Namely, given a linear extension o: P--* {1. . . . . n} with o ( y i ) = i and given I Kv, = Kk: zj < zj_ 1 < . . . < z o = Yk ( 12 ) inductively by the conditions that (a) z o = Yk; (b) among all z covered by z,, a ( z ) is maximized when z = z~+l; and (c) zj is a minimal element of P. Let F~ be the facet ( 11 ) of A ( P ) ; i.e., Fo= FK, where K is the maximal chain q~c (Yl} c { Y l , Y2} c . . . c P of J ( P ) . Then the equations defining the facet q~(Fo) of 4~A(P) are given by 0 <_ f ( Y l ) , Y'~ f ( x ) x E K I <_ ~., f ( x ) , X E~ Kt+ I E f ( x ) <_1. x ~ K,, l < i < n - 1 , For instance, let P and o be given by Fig. 4, where the element y, of P is labeled i. Then, writing f~ for f(Yi), the equations for q,(Fo) are given by 0 < f t < f z < f 2 + f 3 < f z + f 3 + f , < f z + f 5 _<A+A+A_<I, which may also be written as o-<A-<A, A + A - < A , o-<A, A + A + A - < I . o-<A, o-<A, In [16] the Alexandrov-Fenchel inequalities from the theory of mixed volumes were used to prove the logarithmic concavity of certain integer sequences associated with O ( P ) . After reviewing this result we "'transfer" it to o f ( p ) and obtain new log-concave sequences involving linear extensions of P. We state the Alexandrov-Fenchel inequalities in a form most convenient for our purposes. For references to their proofs, see [16]. Let (Ha: 0 < h _<1} be a collection of parallel (affine) hyperplanes in R " such that the distance between H x and H~, is 1~-/~1. Let ~ 0 C H o and ~ l c H 1 be convex bodies (i.e., nonempty compact convex sets), and let ~ = c x ( ~ 0 W~1), the convex hull of ~ 0 and :~1- Set ~ x = :~ n H x and let V " - I ( ~ x ) denote the ( n - 1 ) - d i m e n s i o n a l volume of ~ x - Then there exist real numbers V~(~0' ~ l ) > 0, 0 < i < n - 1, such that V . _ ~ ( ~ x ) = n 1 V(bao, ~1)~,(1 - )k) " - 1 - / , 0 _< X _< 1. ( 13 ) The number V, = V,(~o, ~ t ) is called the ith m i x e d volume of ~ o and ~ l [in particular, Vo(~o, ~al) = v " - l ( ~ o ) , V.-l(~O, ~ 1 ) = v " - l ( ~ a l ) ] , and the Alexandrov-Fenchel inequalities assert that i=0 1~,2 > Vi_IV/+ 1, Then the Oxs satisfy the conditions for ( 13 ). Moreover, if o is a linear extension of P and F o the corresponding facet ( 11 ) of A ( P ) with x = y,, then Ox ~ Fo is given by all f ~ R v satisfying 0 < f ( y , ) <_ . . . <_ f ( Y i ) = ~ < f ( Y i + l ) <-<-"'" <-- f ( Y , ) ( 14 ) ( 15 ) ( 16 ) It follows that and hence vn-l(¢ ~ i - , ( 1 _ X) " - i n F°) = ( i - 1 ) ! ( n - i ) ! " 1 . , g n - l ( ~ ) h ) = ( n - - 1 ) ! ( : ) E Na+l H . 1 ~ i ( 1 - ) k ) n - l - i , i=O N,+ 1 = (n -1)lV,(tV0, ~1), where Nj is the number of linear extensions o of P satisfying o ( x ) = j . Therefore and we conclude from ( 13 ) that Ni 2 > Ni_INt+I, 2 < i < n - 1. More details are given in [16, Section 3] in a somewhat more general setting. We n o w wish to "transfer" ( 15 ) and ( 16 ) to the chain polytope @ = @(P). We cannot simply define cgx = ~tVx, since ~O x need not lie in a hyperplane. Rather, we define @x in analogy to o u r definition of • x and compute V(gx) by examining each tpq~xN Fo, where ff is given by ( 8 ). Thus fix x ~ P, and for 0 < ) ~ < 1 set % = f ( x ) = x ) . L e m m a 6.1. ~ ( P ) = c x ( ~ o U ~¢1). Proof. By Theorem 2.2 every vertex of ~ ( P ) lies in ~0 u ~i, and the proof follows. [] It follows that there are numbers Mo, M I. . . . . 3//._ 1 (depending on the choice of x ~ P ) uniquely defined by M i ( n s t l ) h i ( 1 - h ) ~ - i - ' , 0 < ~ < _ _ 1, (17) and that then Mi2 >__Mi_xM~+ 1, 1 < i < n - 2 . It remains to interpret M~ combinatorially. Theorem 6.2. M i is equal to the number of linear extensions o: P --->{1,..., n ) such that if o ( x ) = s, then i is the largest integer (necessarily less than s) for which o - l( s - 1), o - l( s - 2 ) . . . . . o - l( s - i) are all incomparable with x. (In particular, i = 0 i f s = 1 or if o - l ( s - 1 ) < o - l ( s ) in P. I f x is a minimal element of P then i = s - 1 . ) Proof. Since the simplices ~Fo are the facets of the triangulation ~ A ( P ) of ~ ( P ) , we have V " - l ( f f x ) = Z V"-X(ffx n epFo), o (18) summed over all linear extensions o of P. Define a map p: RP---,R p-',x) by restricting f ~ R e to P - ( x }. Since p is a projection orthogonal to ~x, we have V " - l(cgx n ePFo) = V( P(ffx n ~Fo)), where Vdenotes ordinary (n - 1)-dimensional volume (Lebesgue measure) in R e - ( x ) --- R " - i . Let ~: i f ( P ) --, 0 ( P ) be the bijection defined by ( 8 ). Consider the composition p + : ~x --->R e - ( x ) . From ( 8 ) it follows that for any y ~ P - {x } and any g ~ fix n epFo, we have ( p ~ G ) ( y ) = ~_, g ( z ) , z E K~v where K v is the chain ( 12 ) defined in Section 5 (and where g ( x ) = ~ by the definition of ~x). Hence the map pff, when restricted to ~x n epFo, is an affine transformation whose linear part can be put in triangular form with ls on the diagonal. In particular, ptk is volume-preserving, so v " - i ( p ~ ( ~ x N t k F o ) ) = V n - i ( p ( ~ x n F o ) ) = V n - i ( ~ x n + F o ) . (19) T h e first equality holds because ~ke~= identity. Let y be that d e m e n t of P covered by x which maximizes o ( y ) . Then the condition g ( x ) = A for g ~ ~¢xn ~F, is by ( 7 ) equivalent to f ( x ) - f ( y ) = ~ in ff(~Cxn~Fo). [If x is minimal then the condition becomes f ( x ) = k.] Define Yi = o - 1 ( 0 and suppose y = y,, x = x,. Set f~ = f ( Y i ) . Then the set P f f ( ~ x n fiFo) t~-i ( r - l ) ! X,-~-I ( s - r - l ) ! ( l _ X _ t ) . - ~ (n -s)! v , , - l ( p ~ ( ~ n , r o ) ) = ( r - 1 ) ! ( s r - 1 ) ! ( n s)! × £ 1 - x t ~ _ l ( 1 _ ~ _ t ) " - ' d t . Hence Hence Let t = u(1 - X) to obtain This latter integral is just the beta function B ( r , n - s + l ) = ( r - 1 ) ! ( n - s ) ! ( n + r - s ) ! is defined by the conditions O < f l < . " <_L_I<_L+x<_L+I<_ . . . _< f , _ < l . For fixed fr = t (where 0 _<t < 1 - X) the projection of (20) orthogonal to the plane £ = t has (n -2)-dimensional volume f o l - X t ' - l ( l - - ~ - t ) " - S d t = ( 1 - ) ~ ) " + r - ~ f o l u ~ - l ( 1 - u)n-Sdu. Xs-r--l(l__X)"+r--' V"--l(p+ ( % n , r o ) ) = ( s - r - 1 ) ! ( n + r - s ) ! " Set s - r - 1 = h(o) = h(o, x). Comparing (18), (19), and (21) yields (n - 1)!V"-1(%ax) = ~ (nh(_o )1) -)~h(o)(1 X)n-l--h(o). But clearly h ( o ) is just the largest integer i for which o - l ( s - 1 ) , o - l ( s 2)..... o - l ( s - i) are all incomparable with x, and the proof follows by comparing (17) and (22). [] Example 6.3. Let P be given by Fig. 5, with x, labeled i. Choose x = x 4. We list the linear extensions of P, with the elements o - l ( s - 1 ) ..... o - l ( s - i) incom(20) (21) (22) parable with x underlined: 1 2 3 4 5 2 1 3 4 5 1 2 4 3 5 2 1 4 3 5 2 4 1 3 5 1 2 4 5 3 2 1 4 5 3 2 4 1 5 3 2 4 5 1 3 Hence M0 = 4 , M 1 = 3 , M 2 = l , M 3 = M 4 = 0 . Since ~ ( P ) depends only on Corn(P) we obtain, just as for Corollary 4.4, the following corollary. Corollary 6.4. For any n-element poset P a n d any x ~ P, the numbers M o , M 1. . . . , M ~ _ 1defined in Theorem 6.2 depend only on Corn(P) with the vertex x specified. It is not even a priori obvious that the Mrs are unaffected by replacing P with its dual P* (and leaving the choice of x unaltered), but a simple combinatorial proof which we omit can be given. More generally, Corollary 6.4 can also be proved using the result of Gallai et al. discussed after Corollary 4.5. Just as Theorem 6.2 is the " ~ ( P ) analogue" of ( 16 ), so Theorem 6.2 and its consequence M i 2 > M i _ l M i + l can be straightforwardly generalized to give a ~ ( P ) analogue of the generalization of ( 16 ) given in [16, Thin. 3.2]. Moreover, a variation of ( 15 ) given in [9, (2.14)] can also be given a c~(p) analogue. We will n o t enter into details here. A general property of the mixed volumes V/of ( 13 ) asserts that if V, = 0 then either Vo = V 1 . . . . . V; = 0 or Vi = V~+x. . . . . IT,_ 1 = O. This property, together with ( 14 ) and the fact that V, > 0, implies that the sequence V0, V1,..., V,_ 1 is unimodal; i.e., for some j we have Vo < V 1 < . . . < Vj > Vj+ 1 > . . . > V , _ p In the case of the numbers Mi of Theorem 6.2, an even stronger result can be proved b y direct combinatorial reasoning. Theorem 6.5. The numbers M i = Mi( x ) o f Theorem 6.2 are weakly decreasing; i.e., M o > M I > . . . > Mn_ 1. Proof L e t f~i b e the set o f linear extensions o o f P satisfying h ( a ) = i, where h ( o ) is as i n (22). I f i > 0 a n d o ~ fli,then define o ' : P --, {1 . . . . . n } b y ~i i n t o f~i-1. Since If~,l = M i, the p r o o f [] 1. A. Bj~Srner , A. Garsia , and R. Stanley , An introduction to the theory of Cohen-Macaulay partially ordered sets, in Ordered Sets (I . Rival, ed.), Reidel, Dordrecht-Boston-London, 1982 , 583 - 616 . 2. V. Chv~tal, On certain pdytopes associated with graphs , J. Combin. Theory Ser B 18 ( 1975 ), 138 - 154 . 3. L. Comtet , Advanced Combinatorics, Reidel, Dordrecht-Boston, 1974 . 4. E.E. Doberkat , Problem 84 -20, SIAM Review 26 ( 1984 ), 580 . 5. B. Dreesen , W. Poguntke , and P. Winkler , Comparability invariance of the fixed point property, preprint . 6. U Geissinger , A polytope associated to a finite ordered set, preprint . 7. M . C . Golumbic , Algorithmic Graph Theory and Perfect Graphs , Academic Press, New York, 1980 . 8. M. Habib , Comparability invariants, Ann. Discrete Math. 23 ( 1984 ), 371 - 386 . 9. J. Kahn and M. Saks , Balancing poset extensions, Order 1 ( 1984 ), 113 - 126 . t0. I.G. Macdonald and R. B. Nelsen (independently), Solution to E2701, Amer. Math. Monthly 86 ( 1979 ), 396 . 11. J. S. Provan and U J. Billera , Simplicial Complexes Associated with Convex Polyhedra, I: Constructions and Combinatorial Examples , Technical Rept. no. 402 , School of Operations Research and Industrial Engineering, Comell University, Ithaca, New York, January 1979 . 12. R. Stanley , A chromatic-like polynomial for ordered sets ., in Proc. Second Chapel Hill conference on Combinatorial Mathematics and Its Applications (May , 1970 ), Univ. of North Carolina, Chapel Hill, 421 - 427 . 13. R. Stanley , Ordered structures and partitions , Mem. Amer. Math. Society, no. 119 , 1972 . 14. R. Stanley , Eulerian partitions of a unit hypercube, in Higher Combinatorics (M. Aigner , ed.), Reidel, Dordrecht-Boston, 1977 , p. 49 . 15. R. Stanley , Decompositions of rational convex polytopes , Ann. Discrete Math. 6 ( 1980 ), 333 - 342 . 16. R. Stanley , Two combinatorial applications of the Aleksandrov-Fenchel inequalities , J. Combin. Theory Ser A 31 ( 1981 ), 56 - 65 .


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Richard P. Stanley. Two poset polytopes, Discrete & Computational Geometry, 1986, 9-23, DOI: 10.1007/BF02187680