Abstract 1 Introduction 2 Main Results 3 Univalence of 𝑰(𝑮,𝒛) around 𝜷(𝑮) 4 Gap around every point on the circle with radius 𝜷(𝑮) 5 Upper bound on the Majorant Function near the origin 6 Some Explicit Lower Bounds On The Gap 7 Concluding Remarks References Appendix A Basic Results

On the Roots of Independence Polynomial: Quantifying the Gap

Om Prakash ORCID The Institute of Mathematical Sciences, HBNI, Chennai, India Vikram Sharma ORCID The Institute of Mathematical Sciences, HBNI, Chennai, India
Abstract

The independence polynomial of a graph G is the generating polynomial corresponding to its independent sets of different sizes. More formally, if ak(G) denotes the number of independent sets of G of size k then I(G,z):=k(1)kak(G)zk. The study of evaluating I(G,z) has several deep connections to problems in combinatorics, complexity theory and statistical physics. Consequently, the roots of the independence polynomial have been studied in detail. In particular, many works have provided regions in the complex plane that are devoid of any roots of the polynomial. One of the first such results showed a lower bound on the absolute value of the smallest root β(G) of the polynomial. Furthermore, when G is connected, Goldwurm and Santini established that β(G) is a simple real root of I(G,z) smaller than one. An alternative proof was given by Csikvári. Both proofs do not provide a gap from β(G) to the smallest absolute value amongst all the other roots of I(G,z). In this paper, we quantify this gap.

Keywords and phrases:
Independence Polynomial, Root separation, Zero-free regions
Copyright and License:
[Uncaptioned image] © Om Prakash and Vikram Sharma; licensed under Creative Commons License CC-BY 4.0
2012 ACM Subject Classification:
Mathematics of computing Generating functions
Acknowledgements:
We would like to thank the anonymous referees for their valuable inputs.
Editors:
C. Aiswarya, Ruta Mehta, and Subhajit Roy

1 Introduction

Let G=(V,E) be a simple undirected graph, that is, without loops and multiple edges, with V representing its set of n vertices and E its set of edges. An independent set of G is a subset of vertices of V such that there is no edge between any pair of vertices in the subset. Let ak(G) denote the number of independent sets of size k in G, where a0(G):=1. Following the convention in [3], we define the independence polynomial

I(G,z):=k=0n(1)kak(G)zk. (1)

Let β(G) denote the smallest real root of I(G,z). It is well known that such a root exists and is indeed in the interval (0,1]. Moreover, it is also known that any other root ρ of I(G,z) is strictly greater than β(G) in absolute value [5, 3]. We next describe their proofs in brief, but for this we need to introduce some notation.

For a vertex vV, let NG(v) denote the set of neighbors of v and d(v) its degree in G; we will also use N(v) if G is clear from the context. The set of closed neighbors of v is N[v]:=N(v){v}. Given a subset SV, the graph GS denotes the subgraph of G induced by the vertices VS. A key recursive property of the independence polynomial is the following: For all vertices uV, we have

I(G,z)=I(Gu,z)zI(GN[u],z). (2)

One of the key tools used in both [5] and [3] is the Taylor series expansion of 1/I(G,z) around the origin. In [5], the vertices of the graph are treated as symbols of an alphabet and the edge relations as congruence relations on the alphabet, that is, if two vertices have an edge then the corresponding alphabets can be swapped in any string. The congruence relations impose an equivalence relation, called the trace monoid, on the set of all finite strings over the alphabet. It is well known that the nth coefficient of the power series 1/I(G,z) is the number of traces of length n in the monoid. Using the properties of the trace monoid, it is shown that the power series can be expressed as a rational function where both the numerator and denominator correspond to the characteristic polynomial of two positive matrices. Furthermore, the positive matrix that appears in the denominator dominates the one in the numerator entry wise. Therefore, its largest eigenvalue is unique (due to Perron-Frobenius) and it does not appear as an eigenvalue of the numerator. This establishes the uniqueness of the pole, which is also β(G). We do not see an immediate way to quantify the proof.

In [3] it is shown, using Equation 1, that the coefficients of the power series 1/I(G,z) are all positive. Moreover, from Pringsheim’s theorem we know that the radius of convergence of this power series is β(G). Now consider the power series 1/I(H,z) for any proper subgraph H of G. We can express

1I(G,z)=I(H,z)I(G,z)1I(H,z).

By repeated applications of Equation 1, along with induction, one can argue that the coefficients of both I(H,z)/I(G,z) and 1/I(H,z) are positive. Therefore, the coefficients of the series on the left-hand side above are greater than the coefficients of 1/I(H,z). Hence, β(G)<β(H). By an inductive argument, it is then shown that β(G) is in fact a simple root of I(G,z), when G is connected. To show that any other root ρ of I(G,z) is strictly greater than β(G) in absolute value, they consider the function

fu(z):=zI(GN[u],z)I(Gu,z),

where uV. An inductive argument, similar to the one used for 1/I(G,z), shows that the coefficients (except the constant coefficient) of this power series are also positive. Now if ρ is any other root of I(G,z) with absolute value β(G) then fu(ρ)=fu(|ρ|)=1, that is, fu is periodic on the circle β(G)eiθ, where θ[0,2π) and i:=1. Using the “Daffodil Lemma” from complex analysis [4, p. 266], this implies that the coefficients of fu(z) are a subset of an arithmetic progression. However, since the kth coefficient of fu(z) asymptotically is of the form (β(Gu))k, it does not satisfy an arithmetic progression and this gives us a contradiction that ρ can have the same absolute value as β(G). As the proof is by contradiction, it also fails to quantify the gap between β(G) and ρ.

The insight in this paper builds on the observation that since fu(z) is holomorphic for all z such that |z|<β(Gu), from the Maximum Modulus Principle [4, p. 545] we know that the largest absolute value of fu(z) on the disc D(0,β(G)eiθ) is attained on its boundary. Moreover, as the coefficients of fu(z) are positive, a simple calculation shows that the maximum absolute value is attained on the positive real axis, namely at β(G). This gives an alternate proof to the ones given above. To quantify this argument, we proceed in two steps: first, we show that the function is univalent in a neighborhood of β(G), and second, by constructing a disc around all points with absolute value β(G), except in a certain neighborhood of β(G), where fu(z) does not take the value one. The two steps should intuitively hold, since in the case of the former, as the derivative fu(z) does not vanish at β(G) there must be a neighborhood of β(G) where the function is injective; the latter case follows from the continuity of fu(z). The main challenge is to quantify these two intuitive ideas. For this purpose, we need tools, such as, Smale’s γ-function to study the function locally, and some simple results from complex analysis on radius of univalence of a function, such as fu(z). The main result of the paper is the following:

Theorem 1.1.

Let G be a connected graph on n vertices. Then the disc centered at the origin

D(0,β(G)+(β(G)n)O(n))

contains only the smallest root β(G) of I(G,z).

In the next section, we describe the main results of the paper with intuitive details. The proofs of these results are developed in the subsequent sections. The necessary preliminary results and definitions from graph theory and complex analysis that are needed are provided in the appendix Appendix A.

2 Main Results

Our focus will be to understand the properties of the following function: For any uV, let

fu(z):=zI(GN[u],z)I(Gu,z), (3)

For example, consider the star graph Sn with one central vertex of degree n connected to n leaves. It is not hard to verify that its independence polynomial is (1z)nz. Now, if u is the “center” vertex in Sn then fu(z)=z/(1z)n, but if u is one of the leaves in Sn then

fu(z)=z(1z)n1/((1z)n1z). (4)

If N[u]={u,u1,,uk}, where k=d(u), then

fu(z)=zI(G{u,u1},z)I(Gu,z)I(G{u,u1,,uk},z)I(G{u,u1,,uk1},z).

By k applications of Equation 2, one can recursively construct functions gj(z), j=1,, such that

fu(z)=z(1z)d(v)j=1(1gj(z)), (5)

where gj(z) is not identity for all j. Again consider Sn with u as one of the leaves then the function given in Equation 4 can be re-written as

fu(z)=z1z(1z)n1.

The depth of fu(z) is one more than the maximum depth of gj(z)’s, where the base case

fu(z)=z(1z), (6)

for 1, has depth one. The example function for Sn with u as a leaf has depth two. The reason why we treat powers of (1z) in the denominator separately will shortly become clearer.

Now if ρ is a root of I(G,z), then from Proposition A.1 we know that fu(ρ)=1. As mentioned in Section 1, to quantify the gap between β(G) and the second smallest absolute value over the remaining roots of I(G,z), involves two steps.

Our first result is to show using Proposition A.2 that I(G,z) is injective in a neighborhood of β(G). For this purpose, we define

rG:=β(G)dia(G)2n, (7)

where dia(G) is the diameter of G (see Appendix A). We show the following:

Theorem 2.1.

The polynomial I(G,z) is injective on D(β(G),rG/2), that is, β(G) is the unique root of the polynomial in this disc.

Figure 1: The absolute value function is not always monotone. In (a) we have the plot of |z/(1z/(1z)2)| in red color, corresponding to S3 as given in Equation 4, where z:=βeit, and β0.318 is the point where the function takes the value one. The plot in blue color shows the corresponding majorizing function. (b) Shows the derivative with respect to t of the absolute value in [0,π] and (c) shows the same graph zoomed in to highlight an additional root of the derivative besides 0 and π.

We next need to show that for the points on the circle β(G)eiθ that are outside the disc D(β(G),rG/4), there is a disc centered around each of the points such that the value |fu(z)| is smaller than one on these discs. The following result makes this precise:

Lemma 2.2.

If |wβ(G)eiθ|rG(1|fu(β(G)eiθ)|) then |fu(w)|<1. In other words, there is no root of I(G,z) in the disc D(β(G)eiθ,rG(1|fu(β(G)eiθ)|)), for θ>0.

Note that the radius of the disc goes to zero as θ approaches zero, but this case is already handled in Theorem 2.1. In order to make the bound explicit in terms of graph parameters, we need to upper bound |fu(βeiθ)| for θ sufficiently far away from the origin. Ideally one would expect |fu(βeiθ)| to monotonically decrease in θ as it varies from 0 to π, but this is not the case, as shown in Figure 1 for the function z/(1z/(1z)2).

Nevertheless, this is not far away from the truth, since as the depth of fu(z) increases it concentrates around the origin and drops sharply as θ increases; we are not able to prove this, but our observation is that it has the properties of a “good kernel” [11]. Instead, we show that there is a natural function that majorizes |fu(z)| on the boundary of the disc D(0,reiθ), within its domain of holomorphy, and that is also monotonically decreasing with θ.

A majorant function Gr(θ) for a complex valued function g(reiθ) satisfies the following two properties:

  1. 1.

    Gr(0)=g(r).

  2. 2.

    For all θ, |g(reiθ)|Gr(θ), that is, the function majorizes g on the circle reiθ.

  3. 3.

    It is a monotone decreasing function, i.e., Gr(θ)0; attains its maximum at the origin, i.e., Gr(0)=0; and it is symmetric about the y-axis, i.e., Gr(θ)=Gr(θ).

For example, consider the function in the base case z/(1z). Its absolute value on reiθ is r/|1reiθ|, which by a simple calculation turns out to be

gr(θ)=r(12rcosθ+r2)/2.

In this case it is easier to argue monotonicity because the derivative with respect to θ is

r2sinθ(12rcosθ+r2)(+2)/2,

which is negative for θ(0,π). However, we use a simpler majorant function that upper bounds the absolute value in the base case and behaves similarly. Based on the observation that |1reiθ|1rcosθ, one such function is

gr(θ):=r(1rcosθ). (8)

For rβ(Gu), consider the function

fu(reiθ)=reiθ(1reiθ)j(1gj(reiθ)),

where j varies over some fixed index, and 0. A majorant function Fu,r(θ) for |fu(reiθ)| is obtained recursively from the majorant functions Gj,r(θ) for |gj(reiθ)|, respectively, as follows:

Fu,r(θ):=r(1rcosθ)j(1Gj,r(θ)). (9)

The reason we treat powers of (1reiθ) separately is because if we take the absolute value inside, as we will immanently do for the gj’s, we will get a constant function r. So, in principle, we assume that the gj’s have depth more than one.

Let us verify that Fu,r(θ) satisfies all the properties of a majorant function. Firstly,

Fu,r(0)=r(1r)kj(1Gj,r(0)).

But as Gj,r(0)=gj(r) and the latter is positive it follows that

Fu,r(0)=r(1r)kj|1gj(r)|=fu(r).

Secondly

|fu(reiθ)|r|1reiθ|kj(1|gj(reiθ)|)r(1rcosθ)kj(1Gj,r(θ))=Fu,r(θ)

and thirdly, taking the logarithmic derivative with respect to θ of Fu,r(θ) we obtain

Fu,r(θ)Fu,r(θ)=krsinθ(1rcosθ)+jGj,r(θ)(1Gj,r(θ)). (10)

Therefore, the derivative is non-positive since by induction Gj,r(θ)0 and Fu,r(θ)>0; moreover, it also vanishes at θ=0, hence, the maximum value is attained at the origin which is equal to fu(r)1, for rβ(G); the symmetric nature also follows by applying induction to Equation 9.

The majorant function will be used in Lemma 2.2 instead of |fu(βeiθ)|. However, we still need a more explicit upper bound on Fu,r(θ). The monotone nature of the function comes to rescue, since locally around the origin we will show that the function is upper bounded by an inverted parabola, that is, Fu,r(θ)Fu,r(0)cθ2 for θθG and some constant c dependent on graph parameters. Therefore, the upper bound at θG holds for all Fu,r(θ), for θ>θG. Substituting this upper bound at θG in Lemma 2.2 then gives us the desired explicit disc around every point βeiθ that is devoid of roots. In order to derive this local upper bound, we need to derive an upper bound on a variant of the gamma-function for Fu,r(θ). This is done inductively. Define Fu(θ):=Fu,β(G)(θ), that is, Fu,r(θ) with r=β(G), and Gj(θ):=Gj,β(G)(θ). Then from Equation 9 it follows that

Fu(θ)=β(G)(1β(G)cosθ)j=1d(u)(1Gj(θ)). (11)

In particular, we show the following result:

Lemma 2.3.

For Fu(θ) defined as in Equation 11, and

Γ:=maxj=1dsupm0|Gj(m+1)(0)(m+1)!|1/(m+1)

we have

supk0|Fu(k)(0)k!|1/k2dΓβ(G).

As a consequence, we have

Lemma 2.4.

If θ(β(G)/2d)2Δ, where d is the maximum degree of G, and Δ is the depth of Fu(θ), then

Fu(θ)1(β(G)θ)24.

To express the bound only in terms of d, we can use Shearer’s bound λS(d) instead of β(G).

Substituting this in Lemma 2.2, we obtain

Corollary 2.5.

Define

θG:=(β(G)4n)dia(G). (12)

Then for all θθG there is no root of I(G,z) in the disc D(β(G)eiθ,rG(β(G)θ)2/4),

Finally, combining this result with Theorem 2.1 gives us Theorem 1.1 as desired.

In the next sections, we develop the proofs and details of the results above.

3 Univalence of 𝑰(𝑮,𝒛) around 𝜷(𝑮)

Throughout this section, we use β:=β(G), and vV as a representative vertex. The function fv(z) given in Equation 3 can also be expressed as

fv(z)=zI(GN[v],z)I(Gv,z)=1I(G,z)I(Gv,z). (13)

Then fv(β)=1, fv(0)=0, and fv(0)=1. The next result gives a lower bound on the growth of fv in the vicinity of βG.

Lemma 3.1.

At the smallest root β(G) of I(G,z), we have fv(βG)>1/βG.

Proof.

Taking the derivative on both sides of Equation 13, considering the second formulation, we get that

fv(z)=(I(G,z)I(Gv,z))=I(G,z)I(Gv,z)+I(G,z)I(Gv,z)I(Gv,z)2.

Since β is a root of I(G), we get

fv(β)=I(G,β)I(Gv,β).

Substituting Equation 29 for the derivative, we further obtain that

fv(β) =uVI(GN[u],β)I(Gv,β) (14)
=I(GN[v],β)I(Gv,β)+uV,uvI(GN[u],β)I(Gv,β)
=1β+uV,uvI(GN[u],β)I(Gv,β),

where the last step follows from the definition of β. Now observe that the graphs GN[u], for uV{v} and Gv are all subgraphs of G. Therefore, from Proposition A.1 we know that their smallest root is larger than β and hence the corresponding independence polynomials evaluated at β are all positive. This means that the terms in the summation above are all positive, which gives us the desired lower bound on fv(β).

We also have a corresponding upper bound on fv(β).

Lemma 3.2.

For all vV, fv(β)nβdia(G), where dia(G) is the diameter of G.

Proof.

Let the vertex set of the graph G be V=v,v1,,vn1. Again consider Equation 14. We start with a lower bound on the denominator I(Gv,β) as follows. We know that I(Gv,β)=βI(GN[v],β). Let Gv=GN[v]+v1 where v1N[v], and βv be the smallest root of I(Gv,z). Now I(G,z) is continuously decreasing on the real line starting from the origin down to its smallest root. At the origin we have I(G,0)=|V(G)|. Since Gv is a subgraph of G, we have βv>β. Therefore,

I(Gv,β)=βI(GN[v],β)=βI(Gvv1,β)βI(Gvv1,βv).

Repeating the above argument for vertex v1 and so on we obtain I(Gv,β)βk, where k is the maximum distance of any vertex from the vertex v. Since the diameter dia(G) of the graph is the longest shortest path in the graph and β<1 we have

I(Gv,β)βdia(G). (15)

Note that I(GN[u],β)<1 for all uV. Substituting these two bounds in Equation 14 we get

fv(β)1β+n1βdia(G)=βdia(G)1+n1βdia(G)nβdia(G),

since β1, βdia(G)1.

We next derive an upper bound on higher-order derivatives of I(G,z), which will be useful later.

Lemma 3.3.

Let β be the smallest root of I(G,z), then for all 0kn we have |I(k)(G,β)|(nk)nk. More generally, if H is a subgraph of G, then I(k)(H,β)(|H|k)|H|k.

Proof.

For a general k, we have

I(k)(G,z)=(1)ku1V,u2GN[u1],,ukGj=1k1N[uj]I(GN[u1]N[u2]N[uk],z).

Since the graph GN[u1]N[u2]N[uk] is a subgraph of G, its evaluation at β is smaller than one. The number of distinct choices of u1,,uk are at most (nk), which completes the proof.

Using the bounds above, we derive an upper bound on γI(G,z) (see Equation 32), the standard gamma-function for the derivative I(G,z) at β. We start with deriving a lower bound on I(G,β): Since

I(G,β)=uVI(GN[u],β)

and each I(GN[u],β) has the same sign and by Equation 15 is at least βdia(G), we obtain

|I(G,β)|nβdia(G). (16)

It is not hard to see from the bound in Lemma 3.3 above and Equation 16 that

γ=γI(G,z)(β):=maxk=1,,n|I(k+1)(G,β)k!I(G,β)|1/kmaxk=1,,n|nk+1k!nβdia(G)|1/knβdia(G). (17)

In order to apply Proposition A.2 to I(G,z) centered at β, we first need to derive an upper bound on |I(G,z)| in a neighborhood of β. Consider the Taylor series expansion of the derivative around β

I(G,z)=k0I(k+1)(G,β)k!(zβ)k.

Taking absolute values and pulling out the constant term we get

|I(G,z)||I(G,β)|k0|I(k+1)(G,β)k!I(G,β)||zβ|k.

Substituting the upper bound from Equation 17 in the right-side, we obtain that for zD(β,r)

|I(G,z)||I(G,β)|k0γkrk=|I(G,β)|(1rγ),

as long as rγ<1. By Equation 7, we know that, r(G)γ1/2. Therefore, for all zD(β,rG), |I(G,z)|2|I(G,β)|. Substituting this upper bound, along with the definition of r(G), in Proposition A.2 applied to I(G,z) at β, we get Theorem 2.1.

4 Gap around every point on the circle with radius 𝜷(𝑮)

In this section, we prove Lemma 2.2, that is, we show that the gap to unity for every θ>θG is governed by the gap of fu(reiθ) to fu(r) and a constant that depends on r. We will do the argument only for r=β(G). For this purpose, we first need an upper bound on |fu(k)(β(G))|. Again, for convenience, let β:=β(G).

The kth derivative, up to sign, will have the form

(I(G,z)I(Gu,z))(k)=j=max{0,kn}k(kj)I(G,z)(kj)(1I(Gu,z))(j). (18)

Applying Arbogast’s formula Equation 33 we obtain

(1I(Gu,z))(j)=i1,,ij(1)i1++ijI(Gu,z)1+i1++ijj!(i1++ij)!i1!ij!m=1j(I(m)(Gu,z)m!)im (19)

where the sum is over all indices i1,,ij such that

i1+2i2+3i3++jij=j (20)

Substituting z=β in Equation 18, the term corresponding to j=k disappears in the sum. Plugging the upper bound on the derivatives from Lemma 3.3 in Equation 19 above we get that

|fu(β)(k)|k!j=0k11j!(kj)!n(kj)i1,,ij1I(Gu,β)1+i1++ijj!(i1++ij)!i1!ij!m=1j(nmm!)im.

From Equation 36, we obtain that nmmim=nj. Moreover, as I(Gu,β)<1, we can upper bound its exponent by k as well to get

|fu(β)(k)|k!(nI(Gu,β))kj=0k11j!(kj)!i1,,ijj!(i1++ij)!i1!ij!m=1j(1m!)im.

Using Equation 35 the summation over the indices i1,,ij can be expressed as

|fu(β)(k)|k!(nI(Gu,β))kj=0k11j!(kj)!t=0jt!Bj,t(1,,1),

The last summation over t is the ordered Bell number, B~j (see Appendix A), which gives us

|fu(β)(k)|k!(nI(Gu,β))kj=0k1B~jj!(kj)!.

Furthermore, applying the upper bound from Equation 38 we derive that

|fu(β)(k)|k!(nI(Gu,β))kj=0k12j(kj)!.

Notice that the summation

j=0k12j(kj)!=2kj=1k1j!2j<2kj=11j!2j=2k(e1/21)2k.

Therefore, we finally obtain that

|fu(β)(k)|k!(2nI(Gu,β))k.

As a consequence, we get that

γfu(β)2nI(Gu,β)2nβdia(G)=1rG. (21)

From this bound, we can derive the following estimate, an alternate proof of Theorem 2.1:

Lemma 4.1.

For all zD(0,β+rG/2), |fu(z)|2.

Proof.

A straightforward application of the triangle inequality to the Taylor series of fu around β yields

|fu(z)|fu(β)k0(rγfu(β))k=fu(β)1rγfu(β).

Since rrG/2 it follows that rγfu(β)2, whence the upper bound on |fu(z)| in D(β,rG/2). Because of the maximum modulus principle, the upper bound holds on the whole disc.

Let w be a point in the vicinity of β(G)eiθ. Then taking the Taylor expansion around β(G)eiθ, we get the following upper bound:

|fu(w)||fu(βeiθ)|+k1|fu(k)(βeiθ)|k!|wβeiθ|k.

Since fu is holomorphic with positive coefficients around the origin, from the strong maximum modulus principle, the maximum of |fu(k)(βeiθ)| for all θ is attained at the origin. Now, using the upper bound for r=β from Equation 21, we obtain that

|fu(w)|<|fu(βeiθ)|+k1(|wβeiθ|rG)k.

Define r:=|wβeiθ|/rG. If r<1 then using the formula for a geometric series we have

|fu(w)|<|fu(βeiθ)|+r1r.

Therefore, as long as

r1r1|fu(βeiθ)|

we have |fu(w)|<1, or equivalently, if

|wβeiθ|rG(1|fu(βeiθ)|2|fu(βeiθ)|)

the function cannot take the value one in the vicinity of βeiθ. The denominator can be simplified to one since the maximum value of |fu(βeiθ)| is one at the origin. This completes the proof of the following Lemma 2.2.

5 Upper bound on the Majorant Function near the origin

In this section, we give the proofs of Lemma 2.3 and Lemma 2.4. We again use the shorthand β:=β(G). The idea is to consider the Taylor series expansion of Fu,r(θ) around the origin. More precisely, we have

Fu,r(θ)=Fu,r(0)+Fu,r(0)θ+k2Fu,r(k)(0)k!θk.

Since the first derivative vanishes, we have

Fu,r(θ)=Fu,r(0)+k2Fu,r(k)(0)k!θk.

In fact, all the odd derivatives vanish and, the second derivative is negative. We first verify the latter condition. From Equation 10 it follows that

Fu,r(2)(θ)=Fu,r(θ)jGj,r(θ)(1Gj,r(θ))+Fu,r(θ)j(Gj,r(2)(θ)(1Gj,r(θ))+(Gj,r(θ))2(1Gj,r(θ))2). (22)

Now inductively, the second derivatives Gj,r(2)(0) are negative (the base case from Equation 8 is r2/(1r)2), all the other terms vanish, which yield us that Fu,r(2)(θ)(0)<0 as desired. This means that locally near the origin Fu,r(θ)Fu,r(0)cθ2. We will next show that for θ sufficiently small, half of the second term will dominate the remaining summation in absolute value, and so Fu,r(θ)Fu,r(0)Fu,r(2)(0)θ2/4 for θθG. For this purpose we need an upper bound on the absolute values of the kth derivatives of Fu,r at the origin with r=β, which will be used to derive an upper bound on the γ-function for Fu,r. The upper bound will be derived inductively.

Let us begin with recalling some definitions: From Equation 11 we have

Fu(θ)=βj=1d(u)(1Gj(θ)),

where we have simplified the denominator to subsume the functions βcosθ in the product by appropriate indexing, and Gj(θ):=Gj,β(θ). We next derive a formula for the kth derivative of Fu(θ).

It can be verified that for k1,

Fu(k)(θ)==0k1(k1)Fu(k1)(θ)j(ln(1Gj(θ)))(+1). (23)

Using Arbogast’s formula, Equation 33, for the functions ln(1Gj(θ)), along with Equation 41, we further get that

Fu(k)(θ)==0k1(k1)Fu(k1)(θ)ji0,,i(+1)!i0!i!(i0++i)!(1Gj(θ))m=0imm=0(Gj(m+1)(θ)(m+1)!)im,

where i0,,i is an (+1)-tuple of non-negative integers satisfying the equation

i0+2i1++(+1)i=+1. (24)

At this stage, we can inductively argue that if k is odd then the derivative at the origin vanishes; this is because one of the indices m will be odd and by induction Gj(m+1)(0) vanishes. Dividing both sides by k!, simplifying the binomial (k1) term, and substituting θ=0 we obtain that

Fu(k)(0)k!==0k1Fu(k1)(0)k(k1)!!ji0,,i(+1)!i0!i!(i0++i)!(1Gj(0))m=0imm=0(Gj(m+1)(0)(m+1)!)im, (25)

Define

Γ:=maxj=1dsupm0(|Gj(m+1)(0)|(m+1)!)1/(m+1), (26)

which implies that

|Gj(m+1)(0)|(m+1)!Γm+1.

Furthermore, we inductively assume that

maxj=0k1(|Fu(j)(0)|j!)1/j2dΓβ.

Since Fu(0)=1, we also know that j(1Gj(0))=β, which implies that for all j, (1Gj(0))β. Taking the absolute value, applying the triangle inequality, and substituting these upper and lower bounds in the right-hand side, we get the following

|Fu(k)(0)|k! =0k1(2dΓβ)(k1)1k!ji0,,i(i0++i)!(+1)!i0!i!m=0(Γ(m+1)β)im

From Equation 24, the term mΓim(m+1)=Γ+1 and hence

|Fu(k)(0)|k! Γk=0k1(2dβ)(k1)(+1)!k!ji0,,i(i0++i)!i0!i!(1β)mim
=Γk=0k1(2dβ)(k1)(+1)kji0,,i(i0++i)!i0!i!m=0(1β)mim.

The summation term over j is independent of it, so we can upper bound the summation by the degree d. Furthermore, if we define t=i0++i, for a fixed t, then the right-hand side further simplifies to

|Fu(k)(0)|k! dΓk=0k1(2dβ)(k1)(+1)kt=1+11βti0,,ii0++i=tt!i0!i!
dΓk=0k1(2dβ)(k1)(+1)kt=1+11βt(+1t1),

where the last step follows from Equation 39. Since β1, we can use β(+1) instead of βt to get

|Fu(k)(0)|k! d(Γβ)k=0k1(2d)(k1)(+1)kt=1+1(+1t1)
d(2Γβ)k=0k1(+1)kd(k1),

where in the last step we upper bound the summation of the binomials by 2+1. Since d2, it can be showed that the new summation term is at most dk1, which finally yields us the desired claim in Lemma 2.3.

In the base case Γ is the standard gamma-function for the cosine function, which is smaller than 1/2<1. Therefore, we get

|Fu(k)(0)|k!1/k (2dβ)Δ,

where Δ is the depth of fu(z).

In order for half of the second term in the Taylor series expansion of Fu(θ) around the origin to dominate the sum of the remaining terms, we want

|Fu(2)(0)4|θ22(2dβ)2Δθ2.

Assuming

θ2(β/2d)Δ/2, (27)

the above inequality follows if

θ2|Fu(2)(0)|4(β2d)Δ. (28)

We next derive an explicit lower bound on the second-derivative.

Recall that the first derivatives Fu(0) and Gj(0) vanish, and that the second derivatives Gj(2)(0) are all negative. Therefore, from Equation 22 we obtain that

Fu(2)(0)=jGj(2)(0)(1Gj(0))jGj(2)(0).

Therefore, |Fu(2)(0)|dmin|Gj(2)(0)|. Inductively, we obtain that

|Fu(2)(0)|dΔ1β2/(1β)d+1,

since the absolute value of the second derivative of the majorant function in the base case is dβ2/(1β)d+1. Substituting this in Equation 28, we get a slightly weaker constraint than Equation 27, namely, θ2βΔ+2/4d. So, in order to simplify, we combine the two constraints to obtain Lemma 2.4.

In order to combine this lemma with Theorem 2.1, we notice that the disc D(β,rG/2) subtends the angle arcsin(rG/2β), which is at least βdia(G)/(4n), at the origin. Take θG as a quantity smaller than this bound and the constraint in Lemma 2.4, namely as defined in Equation 12. Since the function Fu(θ) is monotonically decreasing, we know that for all θθG, Fu(θ)Fu(θG). Substituting this in Lemma 2.2, we obtain that for all θθG, the disc

D(βeiθ,rG(βθG)2/4)

is devoid of roots. Since the radius here is smaller than rG/2, we combine this with Theorem 2.1 to finally obtain that the disc

D(0,β+(βn)O(dia(G)))

contains exactly one root of I(G,z) completing the proof of Theorem 1.1. Note that the depth Δ is smaller than the diameter dia(G), which instead is bounded by n.

6 Some Explicit Lower Bounds On The Gap

In this section, we derive explicit lower bounds on the gap between the smallest root β(G) and the root with the second smallest absolute value of the independence polynomial of some fundamental graph classes. In particular, we give the explicit lower bounds for the Path Graph (Pn), the Cycle Graph (Cn) on n vertices and the Complete Bipartite Graph (Kn×n) on 2n vertices. For convenience, let β:=β(G) and α:=α(G) be the root with the second smallest absolute value of the independence polynomial of graph G in each of the cases.

Path Graph

To describe the independence polynomial Pn(z) of the Path Graph we need the Fibonacci polynomials [7]: Let F1(z):=1, F2(z):=z and recursively define Fn+1(z):=zFn(z)+Fn1(z). From the relation Equation 2 for Pn(z) we obtain that zn1Pn(1/z2)=Fn+2(z). The roots of Fn+2(z) are 2icos(kπ/(n+2)), k=1,,n+1. Therefore, the roots of Pn(z) are 1/(4cos2(kπ/(n+2))), for k=1,,n+12. Therefore, β=14cos2(πm) and α=14cos2(2πm), with m:=n+2. Using the Taylor series for the cosine function, for large values of m, we get

cos(πm)cos(2πm)=1+3π22m2+O(m4).

On squaring, we obtain that

αβ=cos2(πm)cos2(2πm)=1+3π2m2+O(m4)=1+Ω(1n2).

Cycle Graph

The independence polynomial Cn(z) of the Cycle Graph can be expressed in terms of the Chebyshev polynomial of the first kind Tn(z) [9]:

Cn(z)=2zn/2Tn(12z).

Therefore, its roots are 14cos2((2k+1)π2n), k=0,1,,n12. This implies that β=14cos2(π2n) and α=14cos2(3π2n). An argument similar to the one above implies that asymptotically we have

αβ=1+2π2n2+17π46n4+O(n6)=1+Ω(1n2).

Complete Bipartite Graph

The independence polynomial Kn×n(z) of the Complete Bipartite Graph on 2n vertices is Kn×n(z)=2(1z)n1. Its roots are zk=121nei2kπn, k=0,1,,n1. Therefore β=121n and α=1rei2πn, where r:=21n. Since, in this case α is a complex root, we compute ratio of the absolute values of the roots:

|α|β=1+r22rcos(2πn)1r=(1r)2+4rsin2(θ/2)1r=1+4r(1r2)sin2(θ/2).

Take b:=ln(2) then, r=eb/n=1bn+b22n2+O(n3) and sin(πn)=πnπ36n3+O(n5). After substituting these estimates and simplifying we get that for large n

|α|β =1+4π2b2+(π234π43b2)1n2+O(n3)
=1+4π2b2π261n2+O(n3)
9.119O(1n2).

7 Concluding Remarks

This paper provides the first quantitative lower bound on the gap between the smallest root of the independence polynomial and the second smallest absolute value. A simple proof for the existence of the gap can be based on the maximum modulus principle. Quantifying the principle for the special function at hand involves studying its local behaviour. To the best of our knowledge, this is the first time a result is provided for separation between roots of the independence polynomial; earlier results always focus on zero-free regions. Our larger hope is to study the algorithmic implications of the ratio of β(G) to the second smallest absolute value. Can it be used to design algorithms that are efficient for those graphs where this ratio is large, for example, the graph classes mentioned in Section 6?

References

  • [1] Ferenc Bencs, Péter Csikvári, Piyush Srivastava, and Jan Vondrák. On complex roots of the independence polynomial. In Nikhil Bansal and Viswanath Nagarajan, editors, Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 675–699, 2023. doi:10.1137/1.9781611977554.ch29.
  • [2] Lenore Blum, Felipe Cucker, Michael Shub, and Steve Smale. Complexity and Real Computation. Springer-Verlag, New York, 1998.
  • [3] Péter Csikvári. Note on the smallest root of the independence polynomial. Combinatorics, Probability and Computing, 22:1–8, 2012. doi:10.1017/S0963548312000302.
  • [4] Philippe Flajolet and Robert Sedgewick. Analytic Combinatorics. Cambridge University Press, USA, 1 edition, 2009.
  • [5] Massimiliano Goldwurm and Massimo Santini. Clique polynomials have a unique root of smallest modulus. Information Processing Letters, 75(3):127–132, 2000. doi:10.1016/S0020-0190(00)00086-7.
  • [6] Lawrence A. Harris. On the size of balls covered by analytic transformations. Monatshefte für Mathematik, 83(1):9–23, March 1977. doi:10.1007/BF01303008.
  • [7] V. E. Hoggatt Jr. and Marjorie Bicknell. Roots of Fibonacci Polynomials. The Fibonacci Quarterly, 11(3):271–274, 1973. doi:10.1080/00150517.1973.12430825.
  • [8] Steven G. Krantz and Harold R. Parks. A Primer of Real Analytic Functions. Birkhäuser, 2012. doi:10.1007/978-0-8176-8134-0.
  • [9] Vadim E Levit and Eugen Mandrescu. The independence polynomial of a graph–a survey. In Proceedings of the 1st International Conference on Algebraic Informatics, volume 233254, pages 231–252. Aristotle Univ. Thessaloniki Thessaloniki, 2005.
  • [10] J.B. Shearer. On a problem of Spencer. Combinatorica, 5:241–245, 1985. doi:10.1007/BF02579368.
  • [11] Elias M. Stein and Rami Shakarchi. Fourier Analysis: An Introduction. Princeton University Press, 2003.

Appendix A Basic Results

Throughout this paper G=(V,E) will be assumed to be a simple undirected graph. Let n be the number of vertices in G. For every vertex uV, let d(u) denote its degree, and d:=maxud(u), for all u; we will assume that d2. Let dia(G) denote the diameter of G, that is the length of the longest path between any pair of vertices in any connected component of G. In the subsequent sections, we will need some basic properties of the independence polynomial (see [3, 1] for proofs):

Proposition A.1.

Let G be as above and I(G,z) be its independence polynomial.

  1. 1.

    The derivative I(G,z) satisfies

    I(G,z)=uVI(GN[u],z). (29)
  2. 2.

    If H is a subgraph of G then β(G)β(H).

  3. 3.

    Shearer [10] showed a lower bound on β(G), namely,

    β(G)λS(d):=(d1)d1dd. (30)

    Applying the third property with G as the complete graph and H an arbitrary graph with at most n vertices, we also have the following lower bound

    β(H)1n. (31)

We will also need variants of Smale’s gamma-function [2]: Given a function f: holomorphic at a point z, such that f(j)(z)0, define

γf,j(z):=supk>j|j!f(k)(z)k!f(j)(z)|1/(kj). (32)

The standard gamma-function corresponds to γf,0(z), and we will simply use γf(z) to denote that. Intuitively, the function is related to the inverse of the radius of convergence of f(j)(z) at z.

We recall Arbogast’s formula (also called the formula of Faà di Bruno) [8] for derivatives of composition of functions: For N0, the Nth derivative of

(fg)(N)(z)=i1,,iNN!i1!iN!f(i1++iN)(g(z))m=1N(g(m)(z)m!)im, (33)

where the sum is over all tuples of non-negative integers i1,,iN such that

i1+2i2+3i3++NiN=N.

Given a K, we can combine the terms corresponding to i1++iN=K and simplify the summation as follows. Since jjij=N it follows with the additional constraint that j(j1)ij=NK. This implies that ij=0, for j>NK+1, and so we can express Equation 33 as

(fg)(N)(z)=K=0Ni1,,iNf(K)(g(z))BN,K(g(z),g(2)(z),,g(NK+1)(z)), (34)

where BN,K(x1,,xNK+1) are the partial exponential Bell polynomials:

BN,K(x1,,xNK+1):=i1,,iNK+1N!i1!iNK+1!m=1NK+1(xmm!)im, (35)

and i1,,iNK+1 satisfy the following two constraints:

i1+2i2+3i3++(NK+1)iNK+1=N and i1+i2+i3++iNK+1=K. (36)

Notice that BN,K(1,,1)={NK}, the Sterling number of second kind, that is number of ways to partition an N element set into K non-empty parts, and hence

K=0NK!BN,K(1,,1)=B~N

the ordered Bell number, which satisfy the following recurrence:

B~N=i=1N1(Ni)B~i. (37)

From this, we can derive the following claim inductively:

B~NN!(1ln2)N. (38)

We will also need the following observation:

i1,,iNK+1K!i1!iNK+1!=(N1K1) (39)

where the sum is over all tuples (i1,,iN) satisfying the conditions in Equation 36. The left-hand side counts all partition of N into K blocks where the ordering of distinct blocks only matter (distinct blocks correspond to different choices of j). However, these are precisely the number of compositions of N into K parts, which is the term on the right-hand side.

Besides the above, we need the following observations for j0

(1x)(j)=(1)jj!xj+1 (40)

and

(lnx)(j)=(1x)(j1)=(1)j1(j1)!xj. (41)

Given α and r>0, we will denote by D(α,r) the open disc centered at α with radius r.

In addition to the above, we need the following quantified result on the injectiveness of a function in a neighborhood of a point where the derivative does not vanish [6]:

Proposition A.2.

Let h:D(α,r) be a holomorphic function such that h(α)=0 and h(α)0. Then h is injective on the disc

D(α,r|h(α)|supzD(α,r)|h(z)|).