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Log-Concavity of the Genus Polynomials of Ringel Ladders

Jonathan L. Gross Department of Computer Science
Columbia University, New York, NY 10027, USA;
email: gross@cs.columbia.edu
Toufik Mansour Department of Mathematics
University of Haifa, 31905 Haifa, Israel;
email: tmansour@univ.haifa.ac.il
Thomas W. Tucker Department of Mathematics
Colgate University, Hamilton, NY 13346, USA;
email: ttucker@colgate.edu
 and  David G.L. Wang School of Mathematics and Statistics
Beijing Institute of Technology, 102488 Beijing, P. R. China;
email: glw@bit.edu.cn
Abstract.

A Ringel ladder can be formed by a self-bar-amalgamation operation on a symmetric ladder, that is, by joining the root vertices on its end-rungs. The present authors have previously derived criteria under which linear chains of copies of one or more graphs have log-concave genus polynomials. Herein we establish Ringel ladders as the first significant non-linear infinite family of graphs known to have log-concave genus polynomials. We construct an algebraic representation of self-bar-amalgamation as a matrix operation, to be applied to a vector representation of the partitioned genus distribution of a symmetric ladder. Analysis of the resulting genus polynomial involves the use of Chebyshev polynomials. This paper continues our quest to affirm the quarter-century-old conjecture that all graphs have log-concave genus polynomials.

2000 Mathematics Subject Classification:
05A15, 05A20, 05C10

1. Genus Polynomials

Our graphs are implicitly taken to be connected, and our graph embeddings are cellular and orientable. For general background in topological graph theory, see [13, 1]. Prior acquaintance with the concepts of partitioned genus distribution (abbreviated here as pgd) and production (e.g., [10, 17]) are necessary preparation for reading this paper. The exposition here is otherwise intended to be accessible both to graph theorists and to combinatorialists.

The number of combinatorially distinct embeddings of a graph GG in the orientable surface of genus ii is denoted by gi(G)g_{i}(G). The sequence g0(G)g_{0}(G), g1(G)g_{1}(G), g2(G)g_{2}(G), \ldots, is called the genus distribution of GG. A genus distribution contains only finitely many positive numbers, and there are no zeros between the first and last positive numbers. The genus polynomial is the polynomial

ΓG(x)=g0(G)+g1(G)x+g2(G)x2+.\Gamma_{G}(x)\,=\,g_{0}(G)+g_{1}(G)x+g_{2}(G)x^{2}+\ldots\,.

Log-concave sequences

A sequence A=(ak)k=0nA=(a_{k})_{k=0}^{n} is said to be nonnegative, if ak0a_{k}\geq 0 for all kk. An element aka_{k} is said to be an internal zero of AA if ak=0a_{k}=0 and if there exist indices ii and jj with i<k<ji<k<j, such that aiaj0a_{i}a_{j}\neq 0. If ak1ak+1ak2a_{k-1}a_{k+1}\leq a_{k}^{2} for all kk, then AA is said to be log-concave. If there exists an index hh with 0hn0\leq h\leq n such that

a0a1ah1ahah+1an,a_{0}\,\leq\,a_{1}\,\leq\,\cdots\,\leq\,a_{h-1}\,\leq\,a_{h}\,\geq\,a_{h+1}\,\geq\,\cdots\,\geq\,a_{n},

then AA is said to be unimodal. It is well-known that any nonnegative log-concave sequence without internal zeros is unimodal, and that any nonnegative unimodal sequence has no internal zeros. A prior paper [11] by the present authors provides additional contextual information regarding log-concavity and genus distributions.

For convenience, we sometimes abbreviate the phrase “log-concave genus distribution” as LCGD. Proofs that closed-end ladders and doubled paths have LCGDs [4] were based on explicit formulas for their genus distributions. Proof that bouquets have LCGDs [12] was based on a recursion. A conjecture that all graphs have LCGDs was published by [12].

Stahl’s method [21, 22] of representing what we have elsewhere formulated as simultaneous recurrences [4] or as a transposition of a production system for a surgical operation on graph embeddings as a matrix of polynomials can simplify a proof that a family of graphs has log-concave genus distributions, without having to derive the genus distribution itself.

Newton’s theorem that real-rooted polynomials with non-negative coefficients are log-concave is one way of getting log-concavity. Stahl [22] made the general conjecture (Conjecture 6.4) that all genus polynomials are real-rooted, and he gave a collection of specific test families. Shortly thereafter, Wagner [24] proved that the genus distributions for the related closed-end ladders and various other test families suggested by [22] are real-rooted. However, Liu and Wang [16] answered Stahl’s general conjecture in the negative, by exhibiting a chain of copies of the wheel graph W4W_{4}, one of Stahl’s test families, that is not real-rooted. Our previous paper [11] proves, nonetheless, that the genus distribution of every graph in the W4W_{4}-linear sequence is log-concave. Thus, even though Stahl’s proposed approach to log-concavity via roots of genus polynomials is sometimes infeasible, results in [11] do support Stahl’s expectation that chains of copies of a graph are a relatively accessible aspect of the general LCGD problem. The genus distributions for the family of Ringel ladders, whose log-concavity is proved in this paper, are not real-rooted either.

Log-concavity of genus distributions for directed graph embeddings has been studied by [2] and [3]. Another related area is the continuing study of maximum genus of graphs, of which [15] is an example.

Linear, ringlike, and tree-like families

Stahl used the term“HH-linear” to describe chains of graphs that are constructed by amalgamating copies of a fixed graph HH. Such amalgamations are typically on a pair of vertices, one in each of the amalgamands, or on a pair of edges. It seems reasonable to generalize the usage of linear in several ways, for instance, by allowing graphs in the chain to be selected from a finite set.

We use the term ring-like to describe a graph that results from any of the following topological operations on a doubly rooted linear chain with one root in the first graph of the chain and one in the last graph:

  1. (1)

    a self-amalgamation of two root-vertices;

  2. (2)

    a self-amalgamation of two root-edges;

  3. (3)

    joining one root-vertex to the other root-vertex (which is called a self-bar-amalgamation).

Every graph can be regarded as tree-like in the sense of tree decompositions. However, we use this term only when a graph is not linear or ring-like. For any fixed tree-width ww and fixed maximum degree Δ\Delta, there is a quadratic-time algorithm [8] to calculate the genus polynomial of graphs of parameters ww and Δ\Delta. One plausible approach to the general LCGD conjecture might be to prove it for fixed tree-width and fixed maximum degree. Recurrences have been given for the the genus distributions of cubic outerplanar graphs [6], 4-regular outerplanar graphs [18], and cubic Halin graphs [7], all three of which are tree-like. However, none of these genus distributions have been proved to be log-concave. Nor have any other tree-like graphs been proved to have LCGDs.

This paper is organized as follows. Section 2 describes a representation of partitioning of the genus distribution into ten parts as a pgd-vector. Section 3 describes how productions are used to describe the effect of a graph operation on the pgd-vector. Section 4 analyzes how self-bar amalgamation affects the genus distribution. Section 5 offers a new derivation of the genus distributions of the Ringel ladders and proof that these genus distributions are log-concave.

2. Partitioned Genus Distributions

A fundamental strategy in the calculation of genus distributions, from the outset [4], has been to partition a genus distribution according to the incidence of face-boundary walks on one or more roots. We abbreviate “face-boundary walk” as fb-walk. For a graph (G,u,s)(G,u,s) with two 2-valent root-vertices, we can partition the number gi(G)g_{i}(G) into the following four parts:

ddi(G)dd_{i}(G):

the number of embeddings of (G,u,v)(G,u,v) in the surface SiS_{i} such that two distinct fb-walks are incident on root uu and two on root vv;

dsi(G)ds_{i}(G):

the number of embeddings in SiS_{i} such that two distinct fb-walks are incident on root uu and only one on root vv;

sdi(G)sd_{i}(G):

the number of embeddings in SiS_{i} such that one fb-walk is twice incident on root uu and two distinct fb-walks are incident on root vv;

ssi(G)ss_{i}(G):

the number of embeddings in SiS_{i} such that one fb-walk is twice incident on root uu and one is twice incident on root vv.

Clearly, gi(G)=ddi(G)+dsi(G)+sdi(G)+ssi(G)g_{i}(G)=dd_{i}(G)+ds_{i}(G)+sd_{i}(G)+ss_{i}(G). Each of the four parts is sub-partitioned:

ddi0(G)dd^{0}_{i}(G):

the number of type-dddd embeddings of (G,u,v)(G,u,v) in SiS_{i} such that neither fb-walk incident at root uu is incident at root vv;

ddi(G)dd^{\prime}_{i}(G):

the number of type-dddd embeddings in SiS_{i} such that one fb-walk incident at root uu is incident at root vv;

ddi′′(G)dd^{\prime\prime}_{i}(G):

the number of type-dddd embeddings in SiS_{i} such that both fb-walks incident at root uu are incident at root vv;

dsi0(G)ds^{0}_{i}(G):

the number of type-dsds embeddings in SiS_{i} such that neither fb-walk incident at root uu is incident at root vv;

dsi(G)ds^{\prime}_{i}(G):

the number of type-dsds embeddings in SiS_{i} such that one fb-walk incident at root uu is incident at root vv;

sdi0(G)sd^{0}_{i}(G):

the number of type-sdsd embeddings in SiS_{i} such that the fb-walk incident at root uu is not incident on root vv;

sdi(G)sd^{\prime}_{i}(G):

the number of type-sdsd embeddings in SiS_{i} such that the fb-walk at root uu is also incident at root vv;

ssi0(G)ss^{0}_{i}(G):

the number of type-ssss embeddings in SiS_{i} such that the fb-walk incident at root uu is not incident on root vv;

ssi1(G)ss^{1}_{i}(G):

the number of type-ssss embeddings in SiS_{i} such that the fb-walk incident at root uu is incident at root vv, and the incident pattern is uuvvuuvv;

ssi2(G)ss^{2}_{i}(G):

the number of type-ssss embeddings in SiS_{i} such that the fb-walk incident at root uu is incident at root vv, and the incident pattern is uvuvuvuv.

We define the pgd-vector of the graph(G,u,v)(G,u,v) to be the vector

(dd′′(G)dd(G)dd0(G)ds0(G)ds(G)sd0(G)sd(G)ss0(G)ss1(G)ss2(G))\begin{matrix}\big{(}dd^{\prime\prime}(G)&dd^{\prime}(G)&dd^{0}(G)&ds^{0}(G)&ds^{\prime}(G)&&&\\[4.0pt] &&&sd^{0}(G)&sd^{\prime}(G)&ss^{0}(G)&ss^{1}(G)&ss^{2}(G)\big{)}\end{matrix}

with ten coordinates, each a polynomial in xx. For instance,

ds(G)=ds0~(G)+ds1(G)x+ds2(G)x2+.ds^{\prime}(G)\;=\;d\tilde{s_{0}}(G)\,+\,ds^{\prime}_{1}(G)x\,+\,ds^{\prime}_{2}(G)x^{2}\,+\,\cdots.

3. Symmetric Ladders

We define the symmetric ladder (L¨n,u,v)(\ddot{L}_{n},u,v) to be the graph obtained from the cartesian product P2Pn+2P_{2}\Box P_{n+2} by contracting the respective edges at both ends that join a pair of 2-valent vertices and designating the remaining two 2-valent vertices at the ends of the ladder as root-vertices. The symmetric ladders (L¨1,u,v)(\ddot{L}_{1},u,v) and (L¨2,u,v)(\ddot{L}_{2},u,v) are illustrated in Figure 3.1. The location of the roots of a symmetric ladder at opposite ends causes it to have a different partitioned genus distribution from other ladders to which it is isomorphic when the roots are disregarded.

Refer to caption
Figure 3.1. The symmetric ladders L¨1\ddot{L}_{1} and L¨2\ddot{L}_{2}.

Productions

A production is an algebraic representation of the set of possible effects of a graph operation on a graph embedding. For instance, adding a rung to an embedded symmetric ladder (L¨n,u,v)(\ddot{L}_{n},u,v) involves inserting a new vertex on each side of the root-vertex vv and then joining the two new vertices. Since both the resulting new vertices are trivalent, the number of embeddings of (L¨n+1,u,v)(\ddot{L}_{n+1},u,v) that can result is 4. Thus, the sum of the coefficients in the consequent of the production (the right side) is 4. Figures 3.2 and 3.3 are topological derivations of the following ten productions used to derive the partitioned genus distribution of (L¨n+1,u,v)(\ddot{L}_{n+1},u,v) from the partitioned genus distribution of (L¨n,u,v)(\ddot{L}_{n},u,v).

ddi0\displaystyle dd^{0}_{i} \displaystyle\longrightarrow 2ddi0+2sdi+10\displaystyle 2dd^{0}_{i}+2sd^{0}_{i+1}
ddi\displaystyle dd^{\prime}_{i} \displaystyle\longrightarrow ddi0+ddi+2sdi+1\displaystyle dd^{0}_{i}+dd^{\prime}_{i}+2sd^{\prime}_{i+1}
ddi′′\displaystyle dd^{\prime\prime}_{i} \displaystyle\longrightarrow 2ddi+2ssi+12\displaystyle 2dd^{\prime}_{i}+2ss^{2}_{i+1}
dsi0\displaystyle ds^{0}_{i} \displaystyle\longrightarrow 2dsi0+2ssi+10\displaystyle 2ds^{0}_{i}+2ss^{0}_{i+1}
dsi\displaystyle ds^{\prime}_{i} \displaystyle\longrightarrow dsi0+dsi+2ssi+11\displaystyle ds^{0}_{i}+ds^{\prime}_{i}+2ss^{1}_{i+1}
sdi0\displaystyle sd^{0}_{i} \displaystyle\longrightarrow 4ddi0\displaystyle 4dd^{0}_{i}
sdi\displaystyle sd^{\prime}_{i} \displaystyle\longrightarrow 4ddi\displaystyle 4dd^{\prime}_{i}
ssi0\displaystyle ss^{0}_{i} \displaystyle\longrightarrow 4dsi0\displaystyle 4ds^{0}_{i}
ssi1\displaystyle ss^{1}_{i} \displaystyle\longrightarrow 4dsi\displaystyle 4ds^{\prime}_{i}
ssi2\displaystyle ss^{2}_{i} \displaystyle\longrightarrow 2dsi+2ddi′′\displaystyle 2ds^{\prime}_{i}+2dd^{\prime\prime}_{i}
Refer to caption
Figure 3.2. Five productions for construction of symmetric ladders.
Refer to caption
Figure 3.3. Five more productions for symmetric ladders.
Theorem 3.1.

The pgd-vector of the symmetric ladder (L¨0,u,v)(\ddot{L}_{0},u,v) is

(3.1) VL0=(0010000000).V_{L_{0}}\,=\,\begin{pmatrix}0&0&1&0&0&0&0&0&0&0\end{pmatrix}.

For n>0n>0, the pgd-vector of the symmetric ladder (L¨n,u,v)(\ddot{L}_{n},u,v) is the product of the row-vector VLn1V_{L_{n-1}} with the 10×1010\times 10 production matrix

(3.2) 𝐌=(200002x00001100002x0000200000002x00020002x00000110002x040000000000400000000000400000000004000000020200000){\bf M}\;=\;\begin{pmatrix}2&0&0&0&0&2x&0&0&0&0\\ 1&1&0&0&0&0&2x&0&0&0\\ 0&2&0&0&0&0&0&0&0&2x\\ 0&0&0&2&0&0&0&2x&0&0\\ 0&0&0&1&1&0&0&0&2x&0\\ 4&0&0&0&0&0&0&0&0&0\\ 0&4&0&0&0&0&0&0&0&0\\ 0&0&0&4&0&0&0&0&0&0\\ 0&0&0&0&4&0&0&0&0&0\\ 0&0&2&0&2&0&0&0&0&0\end{pmatrix}
Proof.

Each of the ten rows of the matrix MM represents one of the ten productions. For instance, the first two rows represent the productions

ddi0\displaystyle dd^{0}_{i} \displaystyle\longrightarrow 2ddi0+2sdi+10\displaystyle 2dd^{0}_{i}+2sd^{0}_{i+1}
ddi\displaystyle dd^{\prime}_{i} \displaystyle\longrightarrow ddi0+ddi+2sdi+1\displaystyle dd^{0}_{i}+dd^{\prime}_{i}+2sd^{\prime}_{i+1}\qed
Example 3.1.

We iteratively calculate pgd-vectors of the symmetric ladders LnL_{n} for n4n\leq 4

VL0=(0010000000)VL1=(0200000002x)VL2=(224x04x04x000)VL3=(62+24x04x4x4x4x08x28x2)VL4=(14+40x2+40x16x212x4x+48x212x4x+48x28x28x20)\setcounter{MaxMatrixCols}{12}\begin{matrix}V_{L_{0}}&=&(0&0&1&0&0&0&0&0&0&0)\\ V_{L_{1}}&=&(0&2&0&0&0&0&0&0&0&2x)\\ V_{L_{2}}&=&(2&2&4x&0&4x&0&4x&0&0&0)\\ V_{L_{3}}&=&(6&2+24x&0&4x&4x&4x&4x&0&8x^{2}&8x^{2})\\ V_{L_{4}}&=&(14+40x&2+40x&16x^{2}&12x&4x+48x^{2}&12x&4x+48x^{2}&8x^{2}&8x^{2}&0)\end{matrix}

4. Self-Bar-Amalgamations

We recall from Section 1 that the self-bar-amalgamation of any doubly vertex-rooted graph (G,u,v)(G,u,v), which is denoted ¯uv(G,u,v)\overline{*}_{uv}(G,u,v), is formed by joining the roots uu and vv. The present case of interest is when the two roots are 2-valent and non-adjacent. We observe that if GG is a cubic 2-connected graph and if each of the two roots is created by placing a new vertex in the interior of an edge of GG, then the result of the self-bar amalgamation is again a 2-connected cubic graph.

Theorem 4.1.

Let (G,u,v)(G,u,v) be a graph with two non-adjacent 2-valent vertex roots. The (non-partitioned) genus distribution of the graph ¯uv(G,u,v)\overline{*}_{uv}(G,u,v), obtained by self-bar-amalgamation, can be calculated as the dot-product of the pgd-vector VGV_{G} with the following row-vector:

(4.1) B=(4x1+3x2+2x4x2+2x4x2+2x4x44).B\;=\;\begin{pmatrix}4x&1+3x&2+2x&4x&2+2x&4x&2+2x&4x&4&4\end{pmatrix}.
Proof.

Figures 4.1 and 4.2 derive the ten corresponding productions.

ddi0\displaystyle dd^{0}_{i} 4gi+1\displaystyle\longrightarrow 4g_{i+1}
ddi\displaystyle dd^{\prime}_{i} gi+3gi+1\displaystyle\longrightarrow g_{i}+3g_{i+1}
dd′′\displaystyle dd^{\prime\prime} 2gi+2gi+1\displaystyle\longrightarrow 2g_{i}+2g_{i+1}
dsi0\displaystyle ds^{0}_{i} 4gi+1\displaystyle\longrightarrow 4g_{i+1}
dsi\displaystyle ds^{\prime}_{i} 2gi+2gi+1\displaystyle\longrightarrow 2g_{i}+2g_{i+1}
sdi0\displaystyle sd^{0}_{i} 4gi+1\displaystyle\longrightarrow 4g_{i+1}
sdi\displaystyle sd^{\prime}_{i} 2gi+2gi+1\displaystyle\longrightarrow 2g_{i}+2g_{i+1}
ssi0\displaystyle ss^{0}_{i} 4gi+1\displaystyle\longrightarrow 4g_{i+1}
ssi1\displaystyle ss^{1}_{i} 4gi\displaystyle\longrightarrow 4g_{i}
ssi2\displaystyle ss^{2}_{i} 4gi\displaystyle\longrightarrow 4g_{i}\qed
Refer to caption
Figure 4.1. Five productions for self-bar-amalgamation.
Refer to caption
Figure 4.2. Five more productions for self-bar-amalgamation.

5. Ringel Ladders

We define a Ringel ladder RLnRL_{n} to be the result of a self-bar-amalgamation on the symmetric ladder (L¨n,u,v)(\ddot{L}_{n},u,v). Such ladders were introduced by Gustin [14] and used extensively by Ringel [19] in his solution with Youngs [20] of the Heawood map-coloring problem. The Ringel ladder RL4RL_{4} is illustrated in Figure 5.1. The genus distributions of Ringel ladders were first calculated by Tesar [23]. Our rederivation here is to facilitate our proof of their log-concavity.

Refer to caption
Figure 5.1. The Ringel ladder RL4RL_{4}.
Example 5.1.

We take dot products of the pgd-vectors calculated in Example 3.1

VL0=(0010000000)VL1=(0200000002x)VL2=(224x04x04x000)VL3=(62+24x04x4x4x4x08x28x2)VL4=(14+40x2+40x16x212x4x+48x212x4x+48x28x28x20)\setcounter{MaxMatrixCols}{12}\begin{matrix}V_{L_{0}}&=&(0&0&1&0&0&0&0&0&0&0)\\ V_{L_{1}}&=&(0&2&0&0&0&0&0&0&0&2x)\\ V_{L_{2}}&=&(2&2&4x&0&4x&0&4x&0&0&0)\\ V_{L_{3}}&=&(6&2+24x&0&4x&4x&4x&4x&0&8x^{2}&8x^{2})\\ V_{L_{4}}&=&(14+40x&2+40x&16x^{2}&12x&4x+48x^{2}&12x&4x+48x^{2}&8x^{2}&8x^{2}&0)\end{matrix}

with the vector (4.1)

B=(4x1+3x2+2x4x2+2x4x2+2x4x44)B\;=\;\begin{pmatrix}4x&1+3x&2+2x&4x&2+2x&4x&2+2x&4x&4&4\end{pmatrix}

to obtain the genus polynomials of the corresponding Ringel ladders.

ΓRL0(x)\displaystyle\Gamma_{RL_{0}}(x) = 2+2x\displaystyle\;=\,2+2x
ΓRL1(x)\displaystyle\Gamma_{RL_{1}}(x) = 2+14x\displaystyle\;=\,2+14x
ΓRL2(x)\displaystyle\Gamma_{RL_{2}}(x) = 2+38x+24x2\displaystyle\;=\,2+38x+24x^{2}
ΓRL3(x)\displaystyle\Gamma_{RL_{3}}(x) = 2+70x+184x2\displaystyle\;=\,2+70x+184x^{2}
ΓRL4(x)\displaystyle\Gamma_{RL_{4}}(x) = 2+118x+648x2+256x3\displaystyle\;=\,2+118x+648x^{2}+256x^{3}
Theorem 5.1.

The genus distribution of the Ringel ladder RLnRL_{n} is given by taking the dot product of the vector BB with the product of the vector VL0V_{L_{0}} and the matrix MnM^{n}, where BB is given by (4.1), and MM is given by (3.2).

Proof.

This follows immediately from Theorem 4.1. ∎

To deduce an explicit expression of ΓRLn(x)\Gamma_{RL_{n}}(x), we shall use Chebyshev polynomials. Chebyshev polynomials of the second kind are defined by the recurrence relation

Up(x)= 2xUp1(x)Up2(x),U_{p}(x)\;=\;2xU_{p-1}(x)-U_{p-2}(x),

with U0(x)=1U_{0}(x)=1 and U1(x)=2xU_{1}(x)=2x. It can be equivalently defined by the generating function

(5.1) p0Up(x)tp=112xt+t2.\sum_{p\geq 0}U_{p}(x){t^{p}}={1\over 1-2xt+t^{2}}.

• The pthp^{\rm th} Chebyshev polynomial Up(x)U_{p}(x) can be expressed by

Up(x)=j0(1)j(pjj)(2x)p2j.U_{p}(x)=\sum_{j\geq 0}(-1)^{j}\binom{p-j}{j}(2x)^{p-2j}.
Theorem 5.2.

The genus distribution of the Ringel ladder RLnRL_{n} is given by

ΓRLn(x)\displaystyle\Gamma_{RL_{n}}(x) =(1x)j0((njj)+(nj+1j))(8x)j\displaystyle\;=\;(1-x)\sum_{j\geq 0}\left(\binom{n-j}{j}+\binom{n-j+1}{j}\right)(8x)^{j}
+x2n+1j0((njj)+(nj+1j))(2x)j.\displaystyle\qquad+x2^{n+1}\sum_{j\geq 0}\left(\binom{n-j}{j}+\binom{n-j+1}{j}\right)(2x)^{j}.
Proof.

Using Theorem 5.1 and mathematical software such as Maple, we calculate the generating function

n0VL0Mntn=(a,b,c,2xta,2xtb,2xta,2xtb,4x2t2a,4x2t2b,2xtc),\displaystyle\sum_{n\geq 0}V_{L_{0}}M^{n}t^{n}=(a,b,c,2xta,2xtb,2xta,2xtb,4x^{2}t^{2}a,4x^{2}t^{2}b,2xtc),

where

a\displaystyle a =2t2(12t8xt2)(1t8xt2)(14xt2),\displaystyle=\frac{2t^{2}}{(1-2t-8xt^{2})(1-t-8xt^{2})(1-4xt^{2})},
b\displaystyle b =2t(1t8xt2)(14xt2),\displaystyle=\frac{2t}{(1-t-8xt^{2})(1-4xt^{2})},
c\displaystyle c =114xt2.\displaystyle=\frac{1}{1-4xt^{2}}.

This implies

n0ΓRLn(x)tn\displaystyle\sum_{n\geq 0}\Gamma_{RL_{n}}(x)t^{n} =n0VL0MnBTtn\displaystyle=\sum_{n\geq 0}V_{L_{0}}M^{n}B^{T}t^{n}
=VL0(1tM)1BT\displaystyle=V_{L_{0}}(1-tM)^{-1}B^{T}
=2(1x)(1+4xt)1t8xt2+4x(1+2xt)12t8xt2.\displaystyle=\frac{2(1-x)(1+4xt)}{1-t-8xt^{2}}+\frac{4x(1+2xt)}{1-2t-8xt^{2}}.

From Definition (5.1), we can denote the coefficient ΓRLn(x)\Gamma_{RL_{n}}(x) of tnt^{n} in the above generating function in the following form.

ΓRLn(x)\displaystyle\Gamma_{RL_{n}}(x) =(1x)8xn+1(28xUn(128x)Un1(128x))\displaystyle=(1-x)\sqrt{-8x}^{n+1}\biggl{(}\frac{2}{\sqrt{-8x}}U_{n}\left(\frac{1}{2\sqrt{-8x}}\right)-U_{n-1}\left(\frac{1}{2\sqrt{-8x}}\right)\biggr{)}
+x8xn+1(48xUn(18x)Un1(18x))\displaystyle\qquad+x\sqrt{-8x}^{n+1}\biggl{(}\frac{4}{\sqrt{-8x}}U_{n}\left(\frac{1}{\sqrt{-8x}}\right)-U_{n-1}\left(\frac{1}{\sqrt{-8x}}\right)\biggr{)}
=(1x)j0(2(njj)+(njj1))(8x)j\displaystyle=(1-x)\sum_{j\geq 0}\left(2\binom{n-j}{j}+\binom{n-j}{j-1}\right)(8x)^{j}
+xj0(2(njj)+(njj1))2n+1+jxj.\displaystyle\qquad+x\sum_{j\geq 0}\left(2\binom{n-j}{j}+\binom{n-j}{j-1}\right)2^{n+1+j}x^{j}.

Using the Pascal recursion (nk)+(nk1)=(n+1k){n\choose k}+{n\choose k-1}={n+1\choose k}, we get the desired expression. ∎

Theorem 5.3.

The Ringel ladders RLnRL_{n} have log-concave genus distributions.

Proof.

Let an,ja_{n,j} be the coefficient of xjx^{j} of ΓRLn(x/2)\Gamma_{RL_{n}}(x/2). By Theorem 5.2, we have

an,j\displaystyle a_{n,j} =[(njj)+(nj+1j)18(nj+1j1)18(nj+2j1)]4j\displaystyle=\left[\binom{n-j}{j}+\binom{n-j+1}{j}-{1\over 8}\binom{n-j+1}{j-1}-{1\over 8}\binom{n-j+2}{j-1}\right]4^{j}
+2n[(nj+1j1)+(nj+2j1)].\displaystyle\qquad+2^{n}\left[\binom{n-j+1}{j-1}+\binom{n-j+2}{j-1}\right].

Note that an,j=0a_{n,j}=0 for jn/2+2j\geq\lfloor n/2\rfloor+2. We define fn(j)=an,j2an,j1an,j+1f_{n}(j)=a_{n,j}^{2}-a_{n,j-1}a_{n,j+1}. When j=n/2+1j=\lfloor n/2\rfloor+1, we have an,j+1=0a_{n,j+1}=0 and thus fn(j)=an,j20f_{n}(j)=a_{n,j}^{2}\geq 0. So it suffices to show that

(5.2) fn(j)0for all n2 and 1jn/2.f_{n}(j)\geq 0\qquad\text{for all $n\geq 2$ and $1\leq j\leq n/2$.}

Using Maple, it is routine to verify that Inequality (5.2) holds true for n<100n<100. We now suppose that n100n\geq 100, and we define

(5.3) gn(j)=fn(j)64j!(j+1)!(n2j+5)!(n2j+3)!(nj)!(nj1)!.g_{n}(j)\;=\;f_{n}(j)\cdotp\frac{64\,j!\,(j+1)!\,(n-2j+5)!\,(n-2j+3)!}{(n-j)!\,(n-j-1)!}.

We employ the expression (5.3) because it can be written, if one replaces jj by xx, in the form

(5.4) gn(x)= 16xs2+2n+2x+1x(nx+1)(s1+2n2xs0),g_{n}(x)\;=\;16^{x}s_{2}+2^{n+2x+1}x(n-x+1)\bigl{(}s_{1}+2^{n-2x}s_{0}\bigr{)},

where s2s_{2}, s1s_{1} and s0s_{0} are polynomials in nn and xx as follows:

s2= 256n(n+5)(n+4)(n+3)2(n+2)2(n+1)24(n+3)(n+2)(n+1)(848n5+10503n4+46749n3+88974n2+64168n+7680)x+(19140n7+303416n6+1959723n5+6630515n4+12527817n3+12930761n2+6465660n+1080000)x2+(59628n6+799668n5+4257252n4+11406255n3+15964242n2+10757127n+2565612)x3+(110781n5+1228365n4+5215302n3+10470267n2+9734049n+3223854)x4(122760n4+1099197n3+3570660n2+4898043n+2323908)x5+(75141n3+542916n2+1286307n+964224)x6(19602n2+137214n+213840)x7+ 19602x8,s_{2}\;=\;256n(n+5)(n+4)(n+3)^{2}(n+2)^{2}(n+1)^{2}\\ -4(n+3)(n+2)(n+1)\cdot\\ (848n^{5}+10503n^{4}+46749n^{3}+88974n^{2}+64168n+7680)x\\ +(19140n^{7}+303416n^{6}+1959723n^{5}+6630515n^{4}+12527817n^{3}\\ +12930761n^{2}+6465660n+1080000)x^{2}\\ +(59628n^{6}+799668n^{5}+4257252n^{4}+11406255n^{3}\\ +15964242n^{2}+10757127n+2565612)x^{3}\\ +(110781n^{5}+1228365n^{4}+5215302n^{3}\\ +10470267n^{2}+9734049n+3223854)x^{4}\\ -(122760n^{4}+1099197n^{3}+3570660n^{2}+4898043n+2323908)x^{5}\\ +(75141n^{3}+542916n^{2}+1286307n+964224)x^{6}\\ -(19602n^{2}+137214n+213840)x^{7}\;+\;19602x^{8},
s1= 4n(n+4)(n+3)(n+2)(n+1)(184n2+595n+538)(288n7+10832n6+97908n5+388214n4+782118n3+803168n2+363528n+39360)x+(3492n6+66912n5+417975n4+1177485n3+1603200n2+969000n+174744)x2(17964n5+225066n4+972648n3+1831368n2+1476624n+375000)x3+(50805n4+445635n3+1302147n2+1485999n+534402)x4(85266n3+519912n2+949644n+510462)x5+(84861n2+331209n+293922)x6(46332n+88938)x7+10692x8,s_{1}\;=\;4n(n+4)(n+3)(n+2)(n+1)(184n^{2}+595n+538)\\ -(288n^{7}+10832n^{6}+97908n^{5}+388214n^{4}+782118n^{3}\\ +803168n^{2}+363528n+39360)x\\ +(3492n^{6}+66912n^{5}+417975n^{4}+1177485n^{3}\\ +1603200n^{2}+969000n+174744)x^{2}\\ -(17964n^{5}+225066n^{4}+972648n^{3}+1831368n^{2}+1476624n+375000)x^{3}\\ +(50805n^{4}+445635n^{3}+1302147n^{2}+1485999n+534402)x^{4}\\ -(85266n^{3}+519912n^{2}+949644n+510462)x^{5}\\ +(84861n^{2}+331209n+293922)x^{6}-(46332n+88938)x^{7}+10692x^{8},

and

s032(x+1)(nx)= 4(n+4)(n+3)(n+2)2(n+1)(20n4+185n3+616n2+883n+468)x+(33n3+222n2+501n+402)x2(18n2+90n+144)x3+18x4.{s_{0}\over 32(x+1)(n-x)}\;=\;4(n+4)(n+3)(n+2)^{2}(n+1)\\ -(20n^{4}+185n^{3}+616n^{2}+883n+468)x\\ +(33n^{3}+222n^{2}+501n+402)x^{2}-(18n^{2}+90n+144)x^{3}+18x^{4}.

In view of (5.2), (5.3) and (5.4), it suffices to show that both s2s_{2} and s1+2n2xs0s_{1}+2^{n-2x}s_{0} are nonnegative for xn/2x\leq n/2.

First, we show that s20s_{2}\geq 0. Toward this objective, we write x=knx=kn. Then 0k1/20\leq k\leq 1/2. Define s~2=s2/n\tilde{s}_{2}=s_{2}/n. Then s~2\tilde{s}_{2} is a polynomial of degree 88 in nn. For 0j80\leq j\leq 8, define

qj=djdnjs~2.q_{j}={d^{j}\over dn^{j}}\tilde{s}_{2}.

Then we have

q8=40320(12k)(3k2)2(33k233k+8)20.q_{8}=40320(1-2k)(3k-2)^{2}(33k^{2}-33k+8)^{2}\geq 0.

So q7q_{7} is increasing in nn for any 0k1/20\leq k\leq 1/2. We compute

q7|n=4=98794080k83852969120k7+14855037120k625338685680k5+24057719280k413647130560k3+4616115840k2861376320k+68382720.q_{7}\big{|}_{n=4}=98794080k^{8}-3852969120k^{7}+14855037120k^{6}\\ -25338685680k^{5}+24057719280k^{4}-13647130560k^{3}\\ +4616115840k^{2}-861376320k+68382720.

It is elementary to prove that

q7|n=4>0for all k[0,1/2].q_{7}\big{|}_{n=4}>0\qquad\text{for all $k\in[0,1/2]$}.

Alternatively, one may find this positivity by drawing its figure in Maple. It follows that q6q_{6} is increasing in the interval [4,)[4,\infty) of nn. Next, we can compute

q6|n=4=395176320k89243020160k7+36108808560k664328152320k5+64252375200k438420136000k3+13701665520k22694375360k+225239040.q_{6}\big{|}_{n=4}=395176320k^{8}-9243020160k^{7}+36108808560k^{6}\\ -64328152320k^{5}+64252375200k^{4}-38420136000k^{3}\\ +13701665520k^{2}-2694375360k+225239040.

Again, it is routine to prove that

q6|n=4>0for all k[0,1/2].q_{6}\big{|}_{n=4}>0\qquad\text{for all $k\in[0,1/2]$}.

So q5q_{5} is increasing in nn on the interval [4,)[4,\infty). Continuing in this bootstrapping way, we can prove that all q4q_{4}, q3q_{3}, q2q_{2}, q1q_{1}, q0q_{0} are increasing for n[4,)n\in[4,\infty). Since

q0|n=4=321159168k84408639488k7+20075655168k646290382848k5+62167349376k450943602304k3+25184659968k26919073280k+812851200q_{0}\big{|}_{n=4}=321159168k^{8}-4408639488k^{7}+20075655168k^{6}\\ -46290382848k^{5}+62167349376k^{4}-50943602304k^{3}\\ +25184659968k^{2}-6919073280k+812851200

is positive for all k[0,1/2]k\in[0,1/2], we conclude that q0>0q_{0}>0 for all n4n\geq 4 and all k[0,1/2]k\in[0,1/2]. That is, s2>0s_{2}>0.

On the other hand, we define

pn=s1+2n2xs0p_{n}=s_{1}+2^{n-2x}s_{0}

It remains to show pn0p_{n}\geq 0 for all x[0,n/2]x\in[0,n/2]. We shall do that for the intervals [0,n/3][0,n/3] and [n/3,n/2][n/3,n/2], respectively.

For the first interval, we claim that

(5.5) s00for all n100 and all 0xn/2.s_{0}\geq 0\quad\text{for all $n\geq 100$ and all $0\leq x\leq n/2$}.

• We will show (5.5) by using the same derivative method. In fact, consider

s0~(x)=s032(x+1)(nx).\tilde{s_{0}}(x)=\frac{s_{0}}{32(x+1)(n-x)}.

Note that s0~(x)\tilde{s_{0}}(x) is a polynomial in xx of degree 44. For 0j40\leq j\leq 4, denote

djdxjs0~(x)=s~0(j)(x).\frac{d^{j}}{dx^{j}}\tilde{s_{0}}(x)=\tilde{s}_{0}^{(j)}(x).

Since s~0(4)(x)=432>0\tilde{s}_{0}^{(4)}(x)=432>0, the 3rd derivative

s0~(3)(x)=432x108(n2+5n+8)\tilde{s_{0}}^{(3)}(x)=432x-108(n^{2}+5n+8)

is increasing on the interval [0,n/2][0,n/2]. Since

s0~(3)(n/2)=108(n2+3n+8)<0,\tilde{s_{0}}^{(3)}(n/2)=-108(n^{2}+3n+8)<0,

we infer that s0~(3)(x)<0\tilde{s_{0}}^{(3)}(x)<0 for all x[0,n/2]x\in[0,n/2]. So the second derivative

s0~(2)(x)=6(11n3+74n2+167n+134)108(n2+5n+8)x+216x2\tilde{s_{0}}^{(2)}(x)=6(11n^{3}+74n^{2}+167n+134)-108(n^{2}+5n+8)x+216x^{2}

is decreasing. Since

s0~(2)(n/2)=6(2n3+38n2+95n+134)>0,\tilde{s_{0}}^{(2)}(n/2)=6(2n^{3}+38n^{2}+95n+134)>0,

we deduce that s0~(2)(x)>0\tilde{s_{0}}^{(2)}(x)>0 for all xx. Therefore,

s0~(1)(x)=(20n4+185n3+616n2+883n+468)+6(11n3+74n2+167n+134)x54(n2+5n+8)x2+72x3\tilde{s_{0}}^{(1)}(x)=-(20n^{4}+185n^{3}+616n^{2}+883n+468)\\ +6(11n^{3}+74n^{2}+167n+134)x-54(n^{2}+5n+8)x^{2}+72x^{3}

is increasing. Since

s0~(1)(n/2)=2(n4+43n3+446n2+962n+936)<0,\tilde{s_{0}}^{(1)}(n/2)=-2(n^{4}+43n^{3}+446n^{2}+962n+936)<0,

we find s0~(1)(x)<0\tilde{s_{0}}^{(1)}(x)<0. It follows that s0~(x)\tilde{s_{0}}(x) is decreasing. Since

s0~(n/2)=18(7n4+154n3+1112n2+2096n+1536)>0,\tilde{s_{0}}(n/2)=\frac{1}{8}(7n^{4}+154n^{3}+1112n^{2}+2096n+1536)>0,

we infer that s0(x)0s_{0}(x)\geq 0 and this completes the proof for Claim (5.5).

Now, for x[0,n/3]x\in[0,n/3], it suffices to prove that p1(x)=s1+2n/3s00p_{1}(x)=s_{1}+2^{n/3}s_{0}\geq 0. This can be done by considering derivatives of p1(x)p_{1}(x), with respect to xx, along the same way. So we omit the proof.

For the other interval [n/3,n/2][n/3,n/2], we compute

fn(n/2)=4n1474560(397n6+9528n5+102100n4+619680n3+2315488n2+5041152n+5898240)>0.f_{n}(n/2)=\frac{4^{n}}{1474560}(397n^{6}+9528n^{5}+102100n^{4}+619680n^{3}\\ +2315488n^{2}+5041152n+5898240)>0.

So we can suppose x[n/3,n/21]x\in[n/3,n/2-1], i.e., n[2x+2,3x]n\in[2x+2,3x]. Define

hj(n)=djdnjpnh_{j}(n)=\frac{d^{j}}{dn^{j}}p_{n}

Expanding in n22xn-2-2x, the function 22xnh8(n)2^{2x-n}h_{8}(n) can be recast as

22xnh8(n)=i=06j=07iaijxj(n22x)i,2^{2x-n}h_{8}(n)=\sum_{i=0}^{6}\sum_{j=0}^{7-i}a_{ij}x^{j}(n-2-2x)^{i},

where aij0a_{ij}\geq 0. So h8(n)0h_{8}(n)\geq 0 for all n[2x+2,3x]n\in[2x+2,3x]. It is elementary to prove that the univariate function h7(2x+2)h_{7}(2x+2) is non-negative. Again, it is routine to see this by drawing a graph of the function h7h_{7} with the aid of Maple. It follows that h7(n)0h_{7}(n)\geq 0 for all n[2x+2,3x]n\in[2x+2,3x]. Then, we check with Maple that h6(2x+2)0h_{6}(2x+2)\geq 0, from which it follows that h6(n)0h_{6}(n)\geq 0 for all n[2x+2,3x]n\in[2x+2,3x]. Continuing in this way, we can show that, for all n[2x+2,3x]n\in[2x+2,3x], we have

h5(n)0,h4(n)0,,h0(n)0\begin{matrix}h_{5}(n)\geq 0,&h_{4}(n)\geq 0,&\cdots,&h_{0}(n)\geq 0\end{matrix}

In particular, we have pn=h0(n)0p_{n}=h_{0}(n)\geq 0. ∎


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