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An Inner Product on Adelic Measures
With Applications to the Arakelov–Zhang Pairing

Peter J. Oberly
Abstract.

We define an inner product on a vector space of adelic measures over a number field. We find that the norm induced by this inner product governs weak convergence at each place of KK. The canonical adelic measure associated to a rational map is in this vector space, and the square of the norm of the difference of two such adelic measures is the Arakelov–Zhang pairing from arithmetic dynamics. We find that the norm of a canonical adelic measure associated to a rational map is commensurate with a height on the space of rational functions with fixed degree. As a consequence, we show that the Arakelov–Zhang pairing of two rational maps ff and gg is, when holding gg fixed, commensurate with the height of ff.

1. Introduction

Let KK be a number field and let MKM_{K} be the set of places of KK. By an adelic measure, we mean a sequence μ=(μv)vMK\mu=(\mu_{v})_{v\in M_{K}} of suitably regular complex-valued measures indexed by the places of KK. At the finite places of KK, each measure μv\mu_{v} is supported on the Berkovich projective line 𝐏v1\mathbf{P}_{v}^{1} and μv\mu_{v} is supported on the Riemann sphere at the infinite places. We also impose two global conditions on adelic measures, namely that the collection of measures (μv)vMK(\mu_{v})_{v\in M_{K}} has constant total mass, and that μv\mu_{v} is trivial for all but finitely many places; precise definitions are deferred to Section 3. The collection of such adelic measures forms complex vector space, which we denote by 𝒜K\mathcal{A}_{K}.

The principal example of an adelic measure is the canonical adelic measure μf=(μf,v)vMK\mu_{f}=(\mu_{f,v})_{v\in M_{K}} of a rational map ff defined over KK. This adelic measure encodes a good amount of information on the vv-adic Julia sets of ff, and so defines an important dynamical invariant. For example, the preperiodic points of ff distribute according to μf,v\mu_{f,v} at each place. When vv is an Archimedean place, μf,v\mu_{f,v} is the measure investigated for polynomials by Brolin [Bro65], and for rational maps by Ljubich [Lju83] and by Freire, Lopes, and Mañé, [FLM83]. For non-Archimedean places, this measure was introduced independently by several authors, including Baker–Rumely [BR06], Chambert-Loir [Cha06], and Favre–Rivera-Letelier [FR06].

We equip 𝒜K\mathcal{A}_{K} with the following pairing. Fix an adelic probability measure λ=(λv)vMK\lambda=(\lambda_{v})_{v\in M_{K}}. At each place vv we let gλ,v(x,y)g_{\lambda,v}(x,y) be an Arakelov–Green’s function of λv\lambda_{v}. (See Section 2 for the definition). We choose a normalization of gλvg_{\lambda_{v}} so that

𝐏v1𝐏v1gλ,v(x,y)dλv(x)λv(y)=:tv0\int_{\mathbf{P}_{v}^{1}}\int_{\mathbf{P}_{v}^{1}}g_{\lambda,v}(x,y)\,d\lambda_{v}(x)\,\lambda_{v}(y)=:t_{v}\geq 0

and require tv=0t_{v}=0 for all but finitely many vv, and that vMKrvtv=:t>0\sum_{v\in M_{K}}r_{v}t_{v}=:t>0, where rv=[Kv:v]/[K:]r_{v}=[K_{v}:{\mathbb{Q}}_{v}]/[K:{\mathbb{Q}}] is the ratio of local to global degrees. Inspired by the work of Favre–Rivera-Letelier and of Baker-Rumely (discussed below), given two adelic measures μ,ν𝒜K\mu,\nu\in\mathcal{A}_{K} we define

μ,νλ,t=vMKrv𝐏v1𝐏v1gλ,v(x,y)𝑑μ(x)𝑑νv¯(y).\langle\mu,\nu\rangle_{\lambda,t}=\sum_{v\in M_{K}}r_{v}\int_{\mathbf{P}_{v}^{1}}\int_{\mathbf{P}_{v}^{1}}g_{\lambda,v}(x,y)\,d\mu(x)\,d\overline{\nu_{v}}(y).

For example, take the Arakelov adelic measure, λAr=(λAr,v)vMK\lambda_{\mathrm{Ar}}=(\lambda_{\mathrm{Ar},v})_{v\in M_{K}}. At Archimedean places vv, λAr,v\lambda_{\mathrm{Ar},v} is the spherical measure, and is trivial at finite places (see (2.2)). An Arakelov–Green’s function for λAr,v\lambda_{\mathrm{Ar},v} which satisfies the above conditions is gλAr,v(x,y)=log||x,y||v1g_{\lambda_{\mathrm{Ar}},v}(x,y)=\log||x,y||_{v}^{-1}, where ||,||v||\cdot,\cdot||_{v} is a continuous extension of the projective metric on 1(v){\mathbb{P}}^{1}({\mathbb{C}}_{v}) to 𝐏v1\mathbf{P}_{v}^{1}. (This is called the spherical kernel in the book by Baker and Rumely [BR10]). It is not hard to check that 𝐏v1𝐏v1log||x,y||v1dλAr,v(x)dλAr(y)=1/2\int_{\mathbf{P}_{v}^{1}}\int_{\mathbf{P}_{v}^{1}}\log||x,y||_{v}^{-1}\,d\lambda_{\mathrm{Ar},v}(x)\,d\lambda_{\mathrm{Ar}}(y)=1/2 for Archimedean vv and is 0 for non-Archimedean vv; thus vMKrvtv=1/2\sum_{v\in M_{K}}r_{v}t_{v}=1/2 and so

μ,νλAr,1/2=vMKrv𝐏v1𝐏v1log1||x,y||vdμv(x)𝑑νv¯(y).\langle\mu,\nu\rangle_{\lambda_{\mathrm{Ar}},1/2}=\sum_{v\in M_{K}}r_{v}\int_{\mathbf{P}_{v}^{1}}\int_{\mathbf{P}_{v}^{1}}\log\frac{1}{||x,y||_{v}}\,d\mu_{v}(x)\,d\overline{\nu_{v}}(y).

Our first theorem is that this pairing is an inner product, and that, in most situations of interest, convergence in the norm λ,t\|\cdot\|_{\lambda,t} induced by this inner product gives weak convergence at each place.

Theorem 1.1.

Fix an adelic probability measure λ=(λv)vMK\lambda=(\lambda_{v})_{v\in M_{K}} and a normalization of Arakelov–Green’s functions as above. Then map (μ,ν)μ,νλ,t(\mu,\nu)\mapsto\langle\mu,\nu\rangle_{\lambda,t} is an inner product on 𝒜K\mathcal{A}_{K}. Furthermore, if μn,μ𝒜K\mu_{n},\mu\in\mathcal{A}_{K} with supn|μn,v|(𝐏v1)<\sup_{n}|\mu_{n,v}|(\mathbf{P}_{v}^{1})<\infty for all vMKv\in M_{K}, then μnμλ,t0\|\mu_{n}-\mu\|_{\lambda,t}\to 0 implies μn,vμv\mu_{n,v}\to\mu_{v} weakly at each place.

Similar potential theoretic pairings are used by both Favre–Rivera-Letelier and Baker–Rumely in connection with their respective proofs of the adelic equidistribution theorem [FR06],[BR06]. The novelty of Theorem 1.1 is that ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} is positive definite for adelic measures of arbitrary mass. In particular, the pairing ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} should perhaps be viewed as a modest extension of the potential theoretic pairings investigated by Favre–Rivera-Letelier and Baker–Rumely. The following comparisons between the height of a rational map ff and the norm μfλ,t2\|\mu_{f}\|^{2}_{\lambda,t} of the canonical adelic measure of ff are the primary new results of this article.

Theorem 1.2.

The map fd2μfλ,t2f\mapsto\frac{d}{2}\|\mu_{f}\|_{\lambda,t}^{2} is a Weil height on the space of monic polynomials of degree dd defined over KK.

The proof of Theorem 1.2 relies on studying the vv-adic Julia sets of ff at each place, and uses escape rate arguments to bound d2μfλ,t2\frac{d}{2}\|\mu_{f}\|^{2}_{\lambda,t} in terms of the height of the coefficients of ff. Such arguments do not apply to rational maps. However, our main theorem shows that fd2μfλ,t2f\mapsto\frac{d}{2}\|\mu_{f}\|_{\lambda,t}^{2} is at least commensurate with a height on Ratd(K)\mathrm{Rat}_{d}(K), the space of rational maps with degree dd defined over KK.

Theorem 1.3.

Let hh be a Weil height on Ratd(K)\mathrm{Rat}_{d}(K). There are positive constants c1,c2,c3,c4c_{1},c_{2},c_{3},c_{4} depending only on h,λ,th,\lambda,t, and dd so that c1h(f)c2d2μfλ,t2c3h(f)+c4c_{1}h(f)-c_{2}\leq\frac{d}{2}\|\mu_{f}\|_{\lambda,t}^{2}\leq c_{3}h(f)+c_{4} for all fRatd(K)f\in\mathrm{Rat}_{d}(K). Moreover c1,c31c_{1},c_{3}\to 1 as dd\to\infty and c2,c4c_{2},c_{4} grow linearly in dd.

These constants are given explicitly in the case of the Arakelov height of the coefficients of ff and μfλAr,1/22\|\mu_{f}\|^{2}_{\lambda_{\mathrm{Ar}},1/2} (see (5.9)). The main idea of the proof of Theorem 1.3 is that while μf\mu_{f} can be quite complicated, μfλAr,1/22\|\mu_{f}\|_{\lambda_{\mathrm{Ar}},1/2}^{2} cannot be too far from the norm of the pull-back of the Arakelov measure fλAr=(fλAr,v)vMKf^{*}\lambda_{\mathrm{Ar}}=(f^{*}\lambda_{\mathrm{Ar},v})_{v\in M_{K}}. It turns out that d2d1fλArλAr,1/22\frac{d}{2}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|_{\lambda_{\mathrm{Ar}},1/2}^{2} is a Weil height on Ratd(K)\mathrm{Rat}_{d}(K), a result of potential interest in its own right (see Section 5 for details). Combining these two results with the observation that λ,t2\|\cdot\|_{\lambda,t}^{2} is never too far from λAr,1/22\|\cdot\|^{2}_{\lambda_{\mathrm{Ar}},1/2} (Proposition 3.2) gives the theorem.

Suppose we have two rational maps f,g:11f,g:{\mathbb{P}}^{1}\to{\mathbb{P}}^{1} of degree at least two. The Arakelov–Zhang pairing (also called the dynamical height pairing), denoted here by (f,g)AZ(f,g)_{\mathrm{AZ}}, is a symmetric, non-negative pairing which in some sense is a dynamical distance between ff and gg. It is closely related to the Call–Silverman canonical heights of ff and gg: the pairing (f,g)AZ(f,g)_{\mathrm{AZ}} vanishes precisely when the canonical heights of ff and gg are equal, or, equivalently, when ff and gg have the same canonical adelic measure (see [PST12], Theorem 3). To some extent, the Arakelov–Zhang pairing measures how similar the vv-adic Julia sets of two rational maps ff and gg are at all places of a number field.

The Arakelov–Zhang pairing is not a metric on rational maps; however, Fili (Theorem 9, [Fil17]) has discovered that it is expressible as the square of a metric on adelic measures. Specifically, Fili showed that the Arakelov-Zhang pairing is equal to the mutual energy pairing:

(f,g)AZ=12((μfμg,μfμg)),(f,g)_{\mathrm{AZ}}=\frac{1}{2}(\!(\mu_{f}-\mu_{g},\mu_{f}-\mu_{g})\!),

where

((μ,ν))=vMKrv𝐀v1×𝐀v1Diagvlog1δv(x,y)dμvνv(x,y).(\!(\mu,\nu)\!)=\sum_{v\in M_{K}}r_{v}\iint_{\mathbf{A}_{v}^{1}\times\mathbf{A}_{v}^{1}\setminus\mathrm{Diag}_{v}}\log\frac{1}{\delta_{v}(x,y)}\;d\mu_{v}\otimes\nu_{v}(x,y).

Here, δv(x,y)\delta_{v}(x,y) is a continuous extension of |xy|v|x-y|_{v} on v×v{\mathbb{C}}_{v}\times{\mathbb{C}}_{v} to 𝐀v1×𝐀v1\mathbf{A}_{v}^{1}\times\mathbf{A}_{v}^{1} and Diagv\mathrm{Diag}_{v} is the diagonal of v×v{\mathbb{C}}_{v}\times{\mathbb{C}}_{v} in 𝐀v1×𝐀v1\mathbf{A}_{v}^{1}\times\mathbf{A}_{v}^{1}. (For Archimedean vv, δv(x,y)\delta_{v}(x,y) is the usual affine distance |xy|v|x-y|_{v}.) This formulation of the dynamical height pairing has been useful in studying unlikely intersection questions; see, for example, [DKY20]. The mutual energy pairing itself was introduced by Favre and Rivera-Letelier in connection with a quantitative form of the adelic equidistribution theorem [FR06]. Our inner product could be understood as a mutual energy pairing relative to a fixed adelic probability measure λ\lambda.

While quite closely related, our inner product and the mutual energy pairing are distinct on 𝒜K\mathcal{A}_{K}. For instance, the mutual energy pairing ((,))(\!(\cdot,\cdot)\!) is not an inner product on adelic measures of arbitrary mass. Indeed, it follows from a result of Baker–Hsia that if ff is a polynomial defined over KK, then ((μf,μf))=0(\!(\mu_{f},\mu_{f})\!)=0 (Theorem 4.1 of [BH05]). However, the mutual energy pairing and our inner product do agree on adelic measures of total mass zero. We may then consider our inner product to be an extension of the mutual energy pairing from the space of adelic measures of total mass zero to 𝒜K\mathcal{A}_{K}. It therefore follows from Theorem 9 of [Fil17] and Theorem 1 of [PST12] that if μf\mu_{f} and μg\mu_{g} are the canonical adelic measures of two rational maps ff and gg then

(1.1) 12μfμgλ,t2=(f,g)AZ.\frac{1}{2}\|\mu_{f}-\mu_{g}\|_{\lambda,t}^{2}=(f,g)_{\mathrm{AZ}}.

It is a straightforward consequence of Theorem 1.3 and (1.1) that, when gg is fixed, the Arakelov–Zhang pairing is commensurate with the height of ff.

Corollary 1.4.

Let hh be a Weil height on Ratd(K)\mathrm{Rat}_{d}(K). Fix a rational map gg defined over KK with degree at least 22. For any rational map ff defined over KK with deg(f)=d2\deg(f)=d\geq 2, there are positive constants c5,c6,c7,c8c_{5},c_{6},c_{7},c_{8} so that

c5h(f)c6d(f,g)AZc7h(f)+c8,c_{5}h(f)-c_{6}\leq d(f,g)_{\mathrm{AZ}}\leq c_{7}h(f)+c_{8},

where c5,c7c_{5},c_{7} depend only on dd and tend to 11 as dd\to\infty, and where c6,c8c_{6},c_{8} depend on both dd,gg, and hh. If ff is a monic polynomial then

d(f,g)AZ=h(f)+O(1)d(f,g)_{\mathrm{AZ}}=h(f)+O(1)

where the implied constants depend on gg, dd, and hh.

Bounds on the Arakelov–Zhang pairing of certain families of rational maps with the power map z2z^{2} are studied by Petsche, Szpiro, and Tucker; one such bound, which is generalized by Corollary 1.4, is (z2,z2+c)AZ=12h(c)+O(1)(z^{2},z^{2}+c)_{\mathrm{AZ}}=\frac{1}{2}h(c)+O(1) [PST12]. The lower bound (z2,f)AZhf(0)(z^{2},f)_{\mathrm{AZ}}\geq h_{f}(0), where hfh_{f} is the Call–Silverman canonical height of a rational map ff, has been shown by Bridy and Larson [BL21]. Perhaps the strongest known comparisons between the dynamical height pairing and a height on rational maps have been shown by DeMarco, Krieger, and Ye. In [DKY20], they show that (ft1,ft2)AZh(t1,t2)(f_{t_{1}},f_{t_{2}})_{\mathrm{AZ}}\asymp h(t_{1},t_{2}) for a certain family of Latès maps ftf_{t} associated to an elliptic curve written in Legendre form with parameter tt. In a similar spirit, they show that (z2+c1,z2+c2)AZh(c1,c2)(z^{2}+c_{1},z^{2}+c_{2})_{\mathrm{AZ}}\asymp h(c_{1},c_{2}) [DKY22]. These estimates are stronger than those of Corollary 1.4, though they hold in specific families of rational maps. It is immediate from Corollary 1.4 and the Northcott property of heights that (f,g)AZ(f,g)_{\mathrm{AZ}} can be bounded from below by constant depending on one of the rational maps.

Corollary 1.5.

Fix a rational map ff of degree d2d\geq 2, defined over KK. There is a positive constant Cf=C(f,d,K)C_{f}=C(f,d,K) depending on f,df,d and KK so that for any rational map gg defined over KK with degree dd, 0<(f,g)AZCf(f,g)AZ0<(f,g)_{\mathrm{AZ}}\implies C_{f}\leq(f,g)_{\mathrm{AZ}}.

A uniform lower bound on (z2+c1,z2+c2)AZ(z^{2}+c_{1},z^{2}+c_{2})_{\mathrm{AZ}} with c1c2c_{1}\neq c_{2} and c1,c2¯c_{1},c_{2}\in\bar{{\mathbb{Q}}}, is given by DeMarco, Krieger, and Ye ([DKY22], Theorem 1.6). They use this lower bound on the Arakelov–Zhang pairing to prove a uniform upper bound on the number of preperiodic points shared by z2+c1z^{2}+c_{1} and z2+c2z^{2}+c_{2}. It is to be hoped that the lower bound of Corollary 1.5 has analogous implications for the number of common preperiodic of two rational maps of degree dd, but we do not explore this possibility here.

Remark 1.

The estimates of Theorems 4.1 and 1.3 give estimates on μλ,t2\|\mu\|_{\lambda,t}^{2} when μ=μf\mu=\mu_{f} is the canonical adelic measure associated to a rational map ff. It is natural to wonder if the norm of a general adelic measure can be estimated, or at least bounded from below. It is a formal consequence of the definitions that μλ,t2t\|\mu\|_{\lambda,t}^{2}\geq t for any adelic probability measure μ\mu; see Corollary 3.4. There is a class of adelic probability measures for which better lower bounds are possible. We say that an adelic measure μ\mu has points of small height if there is a sequence of distinct point {αn}n=1\{\alpha_{n}\}_{n=1}^{\infty} for which hμ(αn)0h_{\mu}(\alpha_{n})\to 0 as nn\to\infty, where hμh_{\mu} is the Favre–Rivera-Letelier height of μ\mu. For example, every canonical adelic measure μf\mu_{f} associated to a rational map of degree at least 22 has small points (indeed, hμf(α)=0h_{\mu_{f}}(\alpha)=0 if and only if α\alpha is preperiodic). For such measures, it is straightforward to show that μλAr,1/2212log(2)\|\mu\|^{2}_{\lambda_{\mathrm{Ar},1/2}}\geq\frac{1}{2}\log(2) with equality if and only if μ=μz2\mu=\mu_{z^{2}}. See Proposition 5.12 for details.

1.1. Outline

We discuss the notation and tools needed in the next section. Section 3 contains the proof of Theorem 1.1. Section 4 has the proof of Theorem 1.2. Section 5 contains the proof of 1.3 and of Corollary 1.5. Section 6 contains some examples where the norm can be computed or bounded explicitly. Here we obtain exact expressions for the norm (with respect to the Arakelov measure) associated to Chebyshev polynomials, and for the norm associated to power maps after an affine change of variables. We also see that the norm associated to a certain family of Lattès maps can be bounded in a stronger way than the general bounds of Theorem 1.3 for rational maps.

1.2. Acknowledgements

Many of the results of this article have appeared in my PhD thesis [Obe23], which was written at Oregon State University. To my advisor, Clayton Petsche, I owe my deepest thanks. I am also very grateful to the anonymous referee for several insightful comments and useful suggestions.

2. Preliminaries

Fix a number field KK and let MKM_{K} be the set of places of KK. Let v{\mathbb{C}}_{v} be the completion of a fixed algebraic closure of KvK_{v}. We denote by ||v|\cdot|_{v} the absolute value on v{\mathbb{C}}_{v} whose restriction to {\mathbb{Q}} coincides with the usual real or pp-adic absolute value. Let rv=[Kv:v]/[K:]r_{v}=[K_{v}:{\mathbb{Q}}_{v}]/[K:{\mathbb{Q}}] be the ratio of local-to-global degrees. It it well known that KK satisfies the product formula, which states that vMK|x|vrv=1\prod_{v\in M_{K}}|x|_{v}^{r_{v}}=1 for all xK×x\in K^{\times}. Moreover the extension formula reads wMLwvrw=rv\sum_{\begin{subarray}{c}w\in M_{L}\\ w\mid v\end{subarray}}r_{w}=r_{v}, where LL is a finite extension of KK, and where wvw\mid v means that ww lies above vv (so |α|w=|α|v|\alpha|_{w}=|\alpha|_{v} for all αK\alpha\in K). We write MK0M_{K}^{0} for the set of non-Archimedean places of KK and MKM_{K}^{\infty} for the Archimedean places.

Of central importance to this article is the v-adic chordal metric, ||,||v:1(v)×1(v)[0,1]||\cdot,\cdot||_{v}:{\mathbb{P}}^{1}({\mathbb{C}}_{v})\times{\mathbb{P}}^{1}({\mathbb{C}}_{v})\to[0,1]. In homogeneous coordinates x=[x1:x2]x=[x_{1}:x_{2}] and y=[y1:y2]y=[y_{1}:y_{2}] the chordal metric is given by

||x,y||v={|x1y2x2y1|v|x1|v2+|x2|v2|y1|v2+|y2|v2,ifv;|x1y2x2y1|vmax(|x1|v,|x2|v)max(|y1|v,|y2|v)ifv.||x,y||_{v}=\begin{dcases}\frac{|x_{1}y_{2}-x_{2}y_{1}|_{v}}{\sqrt{|x_{1}|_{v}^{2}+|x_{2}|_{v}^{2}}\sqrt{|y_{1}|_{v}^{2}+|y_{2}|_{v}^{2}}},&\operatorname{\;\;\text{if}\;\;}v\mid\infty;\\ \frac{|x_{1}y_{2}-x_{2}y_{1}|_{v}}{\max(|x_{1}|_{v},|x_{2}|_{v})\max(|y_{1}|_{v},|y_{2}|_{v})}&\operatorname{\;\;\text{if}\;\;}v\nmid\infty.\end{dcases}

It is well known that ||,||v||\cdot,\cdot||_{v} is a metric on 1(v){\mathbb{P}}^{1}({\mathbb{C}}_{v}), and that when vv is not Archimedean, then ||,||v||\cdot,\cdot||_{v} satisfies the strong triangle inequality (see, for example, chapters 1 and 3 of [Sil07]). For non-Archimedean vv, there is a continuous extension of ||,||v||\cdot,\cdot||_{v} to 𝐏v1\mathbf{P}_{v}^{1} called the spherical kernel which we denote again by ||,||v||\cdot,\cdot||_{v}. The spherical kernel is not a metric on 𝐏v1\mathbf{P}_{v}^{1}; indeed, the Gauss point ζGauss\zeta_{\mathrm{Gauss}} satisfies ||z,ζGauss||v=1||z,\zeta_{\mathrm{Gauss}}||_{v}=1 for all z𝐏v1z\in\mathbf{P}_{v}^{1}. See Proposition 4.7 of [BR10] for more properties of the spherical kernel.

There is an analogous extension of the absolute value |xy|v|x-y|_{v} on v{\mathbb{C}}_{v} to the Berkovich affine line, 𝐀v1\mathbf{A}_{v}^{1}, which, following [BR10], we refer to as the Hsia Kernel, which we will write as δv(x,y)\delta_{v}(x,y). (In [BR10], this is written δ(x,y)\delta(x,y)_{\infty} to distinguish the Hsia kernel from the generalized Hsia kernel. In the work of Favre and Rivera-Letelier, this extension is written sup{S,S}\sup\{S,S^{\prime}\}.) Similar to the classical relationship between the affine distance on {\mathbb{C}} and the chordal metric, we have

(2.1) ||x,y||v=δv(x,y)||x,||v||y,||v||x,y||_{v}=\delta_{v}(x,y)||x,\infty||_{v}||y,\infty||_{v}

for any two points x,y𝐀v1𝐏v1{}x,y\in\mathbf{A}_{v}^{1}\cong\mathbf{P}_{v}^{1}\setminus\{\infty\}. We will also write δv(x,y)=|xy|v\delta_{v}(x,y)=|x-y|_{v} for the affine distance on v{\mathbb{C}}_{v} when vv is Archimedean.

2.1. The Measure-valued Laplacian

Given a sufficiently regular function f:𝐏v1f:\mathbf{P}_{v}^{1}\to{\mathbb{R}}, the measure-valued Laplacian is a an operator Δ\Delta which assigns to ff a Radon measure Δf\Delta f on 𝐏v1\mathbf{P}_{v}^{1} of total mass 0 (Chapter 5, [BR10]). When vv is Archimedean, we identify 𝐏v1\mathbf{P}_{v}^{1} with the Riemann Sphere 1(){}{\mathbb{P}}^{1}({\mathbb{C}})\cong{\mathbb{C}}\cup\{\infty\}. In this case, the measure valued Laplacian is defined for twice continuously differentiable functions f:1()f:{\mathbb{P}}^{1}({\mathbb{C}})\to{\mathbb{R}} by Δf(z)=12π(xx+yy)f(z)dxdy\Delta f(z)=\frac{-1}{2\pi}(\partial_{xx}+\partial_{yy})f(z)\;dx\;dy, where z=[z:1]z=[z:1] and z=x+iyz=x+iy. We then extend Δ\Delta in a distributional sense. When vv is non-Archimedean, the measure-valued Laplacian is first defined on finitely branching subgraphs of 𝐏v1\mathbf{P}_{v}^{1}, and then extended to functions f:𝐏v1f:\mathbf{P}_{v}^{1}\to{\mathbb{R}} which satisfy appropriate coherence conditions. Following [BR10], we denote by BDVv\mathrm{BDV}_{v} the space of functions of bounded differential variation on 𝐏v1\mathbf{P}_{v}^{1}; in a certain sense, this is the largest class of functions for which the measure-valued Laplacian can be defined. For Archimedean vv, we will also use the notation BDVv\mathrm{BDV}_{v} to denote those functions whose distributional Laplacian also defines a Radon measure; in particular, this class contains the sub-harmonic functions ([Ran95], Theorem 3.7.2). We record the standard properties of the Laplacian in the following proposition.

Proposition 2.1.

Fix vMKv\in M_{K} and let f,g:𝐏v1f,g:\mathbf{P}_{v}^{1}\to{\mathbb{R}} be in C(𝐏v1)BDVvC(\mathbf{P}_{v}^{1})\cap\mathrm{BDV}_{v}. The measure valued Laplacian has the following properties:

  1. (1)

    The Laplacian is self-adjoint: f𝑑Δg=g𝑑Δf\int f\;d\Delta g=\int g\;d\Delta f whenever ff is Δg\Delta g-integrable and gg is Δf\Delta f-integrable;

  2. (2)

    if Δf=Δg\Delta f=\Delta g, then ff and gg differ by a constant;

  3. (3)

    f𝑑Δf0\int f\;d\Delta f\geq 0 with equality if and only if ff is constant.

When vv is Archimedean, these are standard facts which follow from Green’s identities. See Corollary 5.38 of [BR10] for a proof of the non-Archimedean case.

2.2. Local Potential Theory

Given a complex Radon measure μ\mu on 𝐏v1\mathbf{P}_{v}^{1}, the (local) potential of μ\mu is the function Uμ:𝐏v1U_{\mu}:\mathbf{P}_{v}^{1}\to{\mathbb{C}} defined by

Uμ(x)=𝐏v1log1||x,y||vdμ(y),U_{\mu}(x)=\int_{\mathbf{P}_{v}^{1}}\log\frac{1}{||x,y||_{v}}\;d\mu(y),

supposing that the integrand is μ\mu-integrable for all xx. We say that μ\mu has continuous potential if UμU_{\mu} is continuous. For each place vMKv\in M_{K} set

(2.2) dλAr,v={d(z)π(1+|z|v2)2ifv;dδζGaussifv,d\lambda_{\mathrm{Ar},v}=\begin{cases}\frac{d\ell(z)}{\pi(1+|z|_{v}^{2})^{2}}&\operatorname{\;\;\text{if}\;\;}v\mid\infty;\\ d\delta_{\zeta_{\mathrm{Gauss}}}&\operatorname{\;\;\text{if}\;\;}v\nmid\infty,\end{cases}

where \ell is the Lebesgue measure on {\mathbb{C}} and δζGauss\delta_{\zeta_{\mathrm{Gauss}}} is the point mass concentrated at the Gauss point ζGauss\zeta_{\mathrm{Gauss}}. For Archimedean vv, a straightforward computation shows that λAr,v\lambda_{\mathrm{Ar},v} is invariant under the action of the unitary group U2()U_{2}({\mathbb{C}}) on 1(){\mathbb{P}}^{1}({\mathbb{C}}).

Proposition 2.2.

Let vMKv\in M_{K} and let μ\mu be a signed Radon measure on 𝐏v1\mathbf{P}_{v}^{1} with continuous potential UμU_{\mu}. Then UμBDVvU_{\mu}\in\mathrm{BDV}_{v} and ΔUμ=μμ(𝐏v1)λAr,v\Delta U_{\mu}=\mu-\mu(\mathbf{P}_{v}^{1})\lambda_{\mathrm{Ar},v}.

Proof.

For non-Archimedean vv, the proposition is Examples 5.19 and 5.22 of [BR10]. For Archimedean vv, Theorem 1.5 of [Lan85] states that Δxlog||x,y||v1=δyλAr,v\Delta_{x}\log||x,y||_{v}^{-1}=\delta_{y}-\lambda_{\mathrm{Ar},v}. Thus, if ϕ\phi is a smooth test function, then

Uμ(x)𝑑Δϕ(x)\displaystyle\int U_{\mu}(x)\,d\Delta\phi(x) =log1||x,y||vdμ(y)𝑑Δϕ(x)\displaystyle=\int\int\log\frac{1}{||x,y||_{v}}\,d\mu(y)\,d\Delta\phi(x)
=log1||x,y||vdΔϕ(x)𝑑μ(y)\displaystyle=\int\int\log\frac{1}{||x,y||_{v}}\,d\Delta\phi(x)\,d\mu(y)
=(ϕ(y)ϕ(x)𝑑λAr,v(x))𝑑μ(y)\displaystyle=\int\left(\phi(y)-\int\phi(x)\,d\lambda_{\mathrm{Ar},v}(x)\right)\,d\mu(y)
=ϕ(y)𝑑μ(y)μ(𝐏v1)ϕ(x)𝑑λAr,v(x),\displaystyle=\int\phi(y)\,d\mu(y)-\mu(\mathbf{P}_{v}^{1})\int\phi(x)\,d\lambda_{\mathrm{Ar},v}(x),

where the use of Fubini’s theorem in the second line is justified as UμU_{\mu} is continuous, hence |Δϕ||\Delta\phi|-integrable, and where the distributional equation Δxlog||x,y||v1=δy(x)λAr,v(x)\Delta_{x}\log||x,y||_{v}^{-1}=\delta_{y}(x)-\lambda_{\mathrm{Ar},v}(x) is used in the third line. Consequently ΔUμ=μμ(𝐏v1)λAr,v\Delta U_{\mu}=\mu-\mu(\mathbf{P}_{v}^{1})\lambda_{\mathrm{Ar},v} for Archimedean vv as well. ∎

Given a probability measure on 𝐏v1\mathbf{P}_{v}^{1} with continuous potential UμU_{\mu}, an Arakelov–Green’s function of μ\mu is a map gμ:𝐏v1×𝐏v1(,]g_{\mu}:\mathbf{P}_{v}^{1}\times\mathbf{P}_{v}^{1}\to(-\infty,\infty] which is symmetric, continuous off of the diagonal of 𝐏v1×𝐏v1\mathbf{P}_{v}^{1}\times\mathbf{P}_{v}^{1} and satisfies the distributional equation Δxgμ(x,y)=δyμ\Delta_{x}g_{\mu}(x,y)=\delta_{y}-\mu. These conditions determine gμg_{\mu} up to an additive constant. In terms of the potentials UμU_{\mu}, gμg_{\mu} is given by the expression

(2.3) gμ(x,y)=log1||x,y||vUμ(x)Uμ(y)+Cg_{\mu}(x,y)=\log\frac{1}{||x,y||_{v}}-U_{\mu}(x)-U_{\mu}(y)+C

where CC is a constant (p. 241 of [BR10]). For example, an Arakelov–Green’s function of λAr,v\lambda_{\mathrm{Ar},v} is gλAr,v(x,y)=log||x,y||v1+Cg_{\lambda_{\mathrm{Ar}},v}(x,y)=\log||x,y||_{v}^{-1}+C, a fact which follows from the distributional equation Δxlog||x,y||v1=δyλAr,v\Delta_{x}\log||x,y||_{v}^{-1}=\delta_{y}-\lambda_{\mathrm{Ar},v}.

3. Adelic Measures

We come to the main object of study in this article. We adopt the convention that complex or real valued measures have finite total variation.

Definition 3.1.

An adelic measure defined over KK is a sequence μ=(μv)vMK\mu=(\mu_{v})_{v\in M_{K}} indexed by places vMKv\in M_{K} so that:

  1. (1)

    For each vMKv\in M_{K}, μv\mu_{v} is a complex-valued Radon measure on 𝐏v1\mathbf{P}_{v}^{1};

  2. (2)

    There is a constant cμc_{\mu}\in{\mathbb{C}} so that μv(𝐏v1)=cμ\mu_{v}(\mathbf{P}_{v}^{1})=c_{\mu} for all vMKv\in M_{K};

  3. (3)

    For all but finitely many vv, μv=cμδζGauss\mu_{v}=c_{\mu}\delta_{\zeta_{\mathrm{Gauss}}};

  4. (4)

    μv\mu_{v} has continuous potentials for all vMKv\in M_{K}.

We say that an adelic measure μ\mu is a signed, probability or positive adelic measure if each μv\mu_{v} is a signed, probability or positive measure respectively. We write Uμ,vU_{\mu,v} instead of the more cumbersome UμvU_{\mu_{v}} for the local potential of μv\mu_{v}. Likewise we will write gμ,vg_{\mu,v} for the Arakelov–Green’s function gμvg_{\mu_{v}} of μv\mu_{v}. The total mass of an adelic measure is defined to be the constant cμc_{\mu}. We denote by 𝒜K\mathcal{A}_{K} the complex vector space of all proper complex adelic measures with continuous potentials, and by 𝒜K0\mathcal{A}_{K}^{0} the subspace consisting of those adelic measures with total mass 0.

Observe that if μ=(μv)vMK\mu=(\mu_{v})_{v\in M_{K}} is an adelic measure with μv=μr,v+iμi,v\mu_{v}=\mu_{r,v}+i\mu_{i,v} for signed measures μr,v,μi,v\mu_{r,v},\mu_{i,v} at each place, then (μr,v)vMK(\mu_{r,v})_{v\in M_{K}} and (μi,v)vMK(\mu_{i,v})_{v\in M_{K}} are again (signed) adelic measures. Indeed, ReUμ,v=Uμr,v\mathrm{Re}\,U_{\mu,v}=U_{\mu_{r},v} so that μr,v\mu_{r,v} has continuous potentials at each place vv; moreover Recμ=Reμv(𝐏v1)=μr,v(𝐏v1)\mathrm{Re}\,c_{\mu}=\mathrm{Re}\,\mu_{v}(\mathbf{P}_{v}^{1})=\mu_{r,v}(\mathbf{P}_{v}^{1}) so that μr,v(𝐏v1)\mu_{r,v}(\mathbf{P}_{v}^{1}) is a constant independent of vv. So μr=(μr,v)\mu_{r}=(\mu_{r,v}) is a signed adelic measure. Similar remarks apply to (μi,v)vMK(\mu_{i,v})_{v\in M_{K}}.

The primary examples of adelic probability measures in 𝒜K\mathcal{A}_{K} relevant to arithmetic dynamics are the adelic canonical measures associated to a rational map, which can be defined as the weak (really, weak-*) limit of the sequence (d1f)nλAr,v(d^{-1}f^{*})^{n}\lambda_{\mathrm{Ar},v} of normalized pull-backs of the Arakalov measure (or, any other measure with continuous potentials). It follows from this definition that fμf,v=dμf,vf^{*}\mu_{f,v}=d\mu_{f,v}; in fact, μf,v\mu_{f,v} is the unique log-continuous probability measure satisfying this equation (Theorem (d) in [FLM83], Théorème A in [FR10]). As shown in [FR04], μf,v=δζGauss\mu_{f,v}=\delta_{\zeta_{\mathrm{Gauss}}} precisely when ff has good reduction, and so μf,v=δζGauss\mu_{f,v}=\delta_{\zeta_{\mathrm{Gauss}}} for all but finitely many vv. That μf\mu_{f} has continuous potentials (in fact, Holder continuous) is also due to Favre and Rivera-Letelier for non-Archimedean vv, and due to Mañé for Archimedean vv [Mañ06]. So μf=(μf,v)vMK\mu_{f}=(\mu_{f,v})_{v\in M_{K}} is indeed an element of 𝒜K\mathcal{A}_{K}.

3.1. A Family of Inner Products

Fix an adelic probability measure λ=(λv)vMK𝒜K\lambda=(\lambda_{v})_{v\in M_{K}}\in\mathcal{A}_{K}. At each place vv, let gλ,v(x,y)g_{\lambda,v}(x,y) be the Arakelov–Green’s function of λv\lambda_{v}, normalized so that

(3.1) gλ,v(x,y)dλ(x)=:tv0\int g_{\lambda,v}(x,y)\,d\lambda(x)=:t_{v}\geq 0

at each place, and where tv=0t_{v}=0 for all but finitely many vv, and vMKrvtv=:t>0\sum_{v\in M_{K}}r_{v}t_{v}=:t>0. Given adelic measures μ=(μv)vMK,ν=(νv)vMK𝒜K\mu=(\mu_{v})_{v\in M_{K}},\nu=(\nu_{v})_{v\in M_{K}}\in\mathcal{A}_{K}, define

μv,νvλ,t,v=gλ,v(x,y)𝑑μv(x)𝑑νv¯(y)\langle\mu_{v},\nu_{v}\rangle_{\lambda,t,v}=\int\int g_{\lambda,v}(x,y)\,d\mu_{v}(x)\,d\overline{\nu_{v}}(y)

and

(3.2) μ,νλ,t=vMKrvμv,νvλ,t,v.\langle\mu,\nu\rangle_{\lambda,t}=\sum_{v\in M_{K}}r_{v}\langle\mu_{v},\nu_{v}\rangle_{\lambda,t,v}.

Note that gλ,v𝑑μv𝑑νv¯\iint g_{\lambda,v}\,d\mu_{v}d\overline{\nu_{v}} exists as μv,νv\mu_{v},\nu_{v} have continuous potentials. Moreover, that gλ,v(x,y)=log||x,y||v1g_{\lambda,v}(x,y)=\log||x,y||_{v}^{-1} and μv=cμδζGauss\mu_{v}=c_{\mu}\delta_{\zeta_{\mathrm{Gauss}}} for all but finitely many vv, and also that log||x,y||v1dδζGauss(y)=0\int\log||x,y||_{v}^{-1}\,d\delta_{\zeta_{\mathrm{Gauss}}}(y)=0 implies μv,νvλ,t,v=0\langle\mu_{v},\nu_{v}\rangle_{\lambda,t,v}=0 for all but finitely many places vv. So the sum (3.2 defining μ,νλ,t\langle\mu,\nu\rangle_{\lambda,t} is finite. Notice that ,λ,t,v\langle\cdot,\cdot\rangle_{\lambda,t,v} is linear in the first coordinate and is conjugate-symmetric; consequently so is ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t}.

We write μvλ,t,v2=μv,μvλ,t,v\|\mu_{v}\|_{\lambda,t,v}^{2}=\langle\mu_{v},\mu_{v}\rangle_{\lambda,t,v} and μλ,t2=μ,μλ,t\|\mu\|^{2}_{\lambda,t}=\langle\mu,\mu\rangle_{\lambda,t}. It follows from our choice of normalization of gλ,vg_{\lambda,v} that

λvλ,t,v2=gλ,v(x,y)𝑑λv(x)𝑑λv(y)=tv\|\lambda_{v}\|^{2}_{\lambda,t,v}=\int\int g_{\lambda,v}(x,y)\,d\lambda_{v}(x)\,d\lambda_{v}(y)=t_{v}

and so

λλ,t2=vMKrvtv=t.\|\lambda\|_{\lambda,t}^{2}=\sum_{v\in M_{K}}r_{v}t_{v}=t.

Our first theorem describes the properties of this pairing and shows that it is an extension of the mutual energy pairing investigated by Favre and Rivera-Letelier, and by Fili. We adopt the terminology common in probability and say that a sequence of (signed or complex-valued) Radon measures {μn}n=1\{\mu_{n}\}_{n=1}^{\infty} converges weakly to a measure μ\mu if ϕ𝑑μnϕ𝑑μ\int\phi\,d\mu_{n}\to\int\phi\,d\mu for all continuous ϕ\phi.

Theorem 3.1.

Let λ=(λv)vMK𝒜K\lambda=(\lambda_{v})_{v\in M_{K}}\in\mathcal{A}_{K} be an adelic probability measure, and, at each place vv, choose a normalization of gλ,vg_{\lambda,v} as in (3.1). Then ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} defines an inner product on 𝒜K\mathcal{A}_{K} which agrees with the mutual energy pairing on 𝒜K0\mathcal{A}_{K}^{0}. Moreover, if μn,μ𝒜K\mu_{n},\mu\in\mathcal{A}_{K} with μnμλ,t0\|\mu_{n}-\mu\|_{\lambda,t}\to 0 and if supn1|μn,v|(𝐏v1)<\sup_{n\geq 1}|\mu_{n,v}|(\mathbf{P}_{v}^{1})<\infty, then μn,v\mu_{n,v} converges weakly to μv\mu_{v}.

3.2. Proof of Theorem 3.1

Rather than studying the whole family of pairings ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t}, it will be convenient to study one particular pairing. Proposition 3.2 shows that there is little loss of generality in doing so.

Given μ=(μv)vMK,ν=(νv)vMK\mu=(\mu_{v})_{v\in M_{K}},\nu=(\nu_{v})_{v\in M_{K}} in 𝒜K\mathcal{A}_{K}, set

μv,νvv=𝐏v1𝐏v1log1||x,y||vdμv(x)𝑑νv¯(y)=𝐏v1Uμ,v(y)𝑑νv¯(y),\langle\mu_{v},\nu_{v}\rangle_{v}=\int_{\mathbf{P}_{v}^{1}}\int_{\mathbf{P}_{v}^{1}}\log\frac{1}{||x,y||_{v}}\;d\mu_{v}(x)d\overline{\nu_{v}}(y)=\int_{\mathbf{P}_{v}^{1}}U_{\mu,v}(y)\;d\overline{\nu_{v}}(y),

and

(3.3) μ,ν=vMKrvμv,νvv.\langle\mu,\nu\rangle=\sum_{v\in M_{K}}r_{v}\langle\mu_{v},\nu_{v}\rangle_{v}.

We will write μvv2=μv,μvv\|\mu_{v}\|^{2}_{v}=\langle\mu_{v},\mu_{v}\rangle_{v} and μ2=μ,μ\|\mu\|^{2}=\langle\mu,\mu\rangle.

This is the pairing associated to λAr=(λAr,v)vMK\lambda_{\mathrm{Ar}}=(\lambda_{\mathrm{Ar},v})_{v\in M_{K}} with t=1/2t=1/2. Thus

μv,νvv=μv,νvλAr,1/2,v.\langle\mu_{v},\nu_{v}\rangle_{v}=\langle\mu_{v},\nu_{v}\rangle_{\lambda_{\mathrm{Ar}},1/2,v}.

To see this, note that gλAr,v(x,y)=log||x,y||v1+Cg_{\lambda_{\mathrm{Ar}},v}(x,y)=\log||x,y||_{v}^{-1}+C. For non-Archimedean vv, λAr,v=δζGauss\lambda_{\mathrm{Ar},v}=\delta_{\zeta_{\mathrm{Gauss}}} and log||x,y||v1dδζGauss(x)=log||ζGauss,y||v1=0\int\log||x,y||_{v}^{-1}\,d\delta_{\zeta_{\mathrm{Gauss}}}(x)=\log||\zeta_{\mathrm{Gauss}},y||_{v}^{-1}=0. For Archimedean vv, a straightforward computation, using the invariance of both the projective metric ||,||v||\cdot,\cdot||_{v} and λAr,v\lambda_{\mathrm{Ar},v} under the action of U2()U_{2}({\mathbb{C}}) on 1(){\mathbb{P}}^{1}({\mathbb{C}}), shows that log||x,y||v1dλAr,v(x)=12\int\log||x,y||_{v}^{-1}\,d\lambda_{\mathrm{Ar},v}(x)=\frac{1}{2}. Therefore vMKrvgλAr,v𝑑λAr,v𝑑λAr,v=vrv12=12\sum_{v\in M_{K}}r_{v}\int\int g_{\lambda_{\mathrm{Ar}},v}\,d\lambda_{\mathrm{Ar},v}d\lambda_{\mathrm{Ar},v}=\sum_{v\mid\infty}r_{v}\frac{1}{2}=\frac{1}{2}, where we have used the fact that vrv=1\sum_{v\mid\infty}r_{v}=1.

Proposition 3.2.

Let λ=(λv)vMK\lambda=(\lambda_{v})_{v\in M_{K}} be an adelic probability measure, and choose a normalization of Arakelov–Green’s functions gλ,vg_{\lambda,v} as in (3.1). Then

  1. (1)

    μ,νλ,t=μcμλ,νcνλ+cμcν¯t\langle\mu,\nu\rangle_{\lambda,t}=\langle\mu-c_{\mu}\lambda,\nu-c_{\nu}\lambda\rangle+c_{\mu}\overline{c_{\nu}}t for any μ,ν𝒜K\mu,\nu\in\mathcal{A}_{K};

  2. (2)

    there is a constant κ\kappa depending only on λ\lambda so that |μ,νλ,tμ,ν|cμcν(κ+t)|\langle\mu,\nu\rangle_{\lambda,t}-\langle\mu,\nu\rangle|\leq c_{\mu}c_{\nu}(\kappa+t) whenever μ\mu and ν\nu are positive adelic measures.

We remark that item (1) shows that ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} depends only on vMKrvtv=t\sum_{v\in M_{K}}r_{v}t_{v}=t and not on the specific normalization of gλ,vg_{\lambda,v} at each place.

Proof.

It is a formal consequence of (2.3) that

tv\displaystyle t_{v} =gλ,v(x,y)𝑑λv(x)𝑑λv(y)\displaystyle=\int\int g_{\lambda,v}(x,y)\,d\lambda_{v}(x)\,d\lambda_{v}(y)
={log1||x,y||vUλ,v(x)Uλ,v(y)+C}𝑑λv(x)𝑑λv(y)\displaystyle=\int\int\left\{\log\frac{1}{||x,y||_{v}}-U_{\lambda,v}(x)-U_{\lambda,v}(y)+C\right\}\,d\lambda_{v}(x)d\,\lambda_{v}(y)
=λvv2+C,\displaystyle=-\|\lambda_{v}\|_{v}^{2}+C,

and so

(3.4) gλ,v(x,y)=log1||x,y||vUλ,v(x)Uλ,v(y)+λvv2+tv.g_{\lambda,v}(x,y)=\log\frac{1}{||x,y||_{v}}-U_{\lambda,v}(x)-U_{\lambda,v}(y)+\|\lambda_{v}\|_{v}^{2}+t_{v}.

Note that Uλ,v(x)dμv(x)=log||x,y||v1dλv(y)dμv(x)=μv,λvv\int U_{\lambda,v}(x)\,d\mu_{v}(x)=\int\int\log||x,y||_{v}^{-1}\,d\lambda_{v}(y)\,d\mu_{v}(x)=\langle\mu_{v},\lambda_{v}\rangle_{v}, and similarly that Uλ,v(y)νv¯(y)=λv,νvv\int U_{\lambda,v}(y)\,\overline{\nu_{v}}(y)=\langle\lambda_{v},\nu_{v}\rangle_{v}. By (3.4), we have

μv,νvλ,t,v\displaystyle\langle\mu_{v},\nu_{v}\rangle_{\lambda,t,v} =gλ,v(x,y)𝑑μv(x)𝑑ν¯v(y)\displaystyle=\int\int g_{\lambda,v}(x,y)\;d\mu_{v}(x)\;d\overline{\nu}_{v}(y)
={log1||x,y||vUλ,v(x)Uλ,v(y)+λvv2+tv}𝑑μv(x)𝑑ν¯v(y)\displaystyle=\int\int\left\{\log\frac{1}{||x,y||_{v}}-U_{\lambda,v}(x)-U_{\lambda,v}(y)+\|\lambda_{v}\|^{2}_{v}+t_{v}\right\}\;d\mu_{v}(x)\;d\overline{\nu}_{v}(y)
=μv,νvvcν¯μv,λvvcμλv,νvv+cμcν¯λvv2+cμcν¯tv\displaystyle=\langle\mu_{v},\nu_{v}\rangle_{v}-\overline{c_{\nu}}\langle\mu_{v},\lambda_{v}\rangle_{v}-c_{\mu}\langle\lambda_{v},\nu_{v}\rangle_{v}+c_{\mu}\overline{c_{\nu}}\|\lambda_{v}\|_{v}^{2}+c_{\mu}\overline{c_{\nu}}t_{v}
=μv,νvcνλvvcμλv,νvv+cμλv,cνλvv+cμcν¯tv\displaystyle=\langle\mu_{v},\nu_{v}-c_{\nu}\lambda_{v}\rangle_{v}-\langle c_{\mu}\lambda_{v},\nu_{v}\rangle_{v}+\langle c_{\mu}\lambda_{v},c_{\nu}\lambda_{v}\rangle_{v}+c_{\mu}\overline{c_{\nu}}t_{v}
=μv,νvcνλvvcμλv,νvcνλvv+cμcν¯tv\displaystyle=\langle\mu_{v},\nu_{v}-c_{\nu}\lambda_{v}\rangle_{v}-\langle c_{\mu}\lambda_{v},\nu_{v}-c_{\nu}\lambda_{v}\rangle_{v}+c_{\mu}\overline{c_{\nu}}t_{v}
=μvcμλv,νvcνλvv+cμcν¯tv,\displaystyle=\langle\mu_{v}-c_{\mu}\lambda_{v},\nu_{v}-c_{\nu}\lambda_{v}\rangle_{v}+c_{\mu}\overline{c_{\nu}}t_{v},

where we have used the linearity and conjugate-symmetry of ,v\langle\cdot,\cdot\rangle_{v} several times. Multiplying by rvr_{v} and summing over all places of KK gives item (1).
For (2), note that as Uλ,v(x)U_{\lambda,v}(x) is continuous on 𝐏v1\mathbf{P}_{v}^{1}, (2.3) implies that there is a constant κv\kappa_{v} so that

(3.5) |gλ,v(x,y)tvlog||x,y||v1|κv\big{|}g_{\lambda,v}(x,y)-t_{v}-\log||x,y||_{v}^{-1}\big{|}\leq\kappa_{v}

for all xyx\neq y. Moreover, when λv=δζGauss\lambda_{v}=\delta_{\zeta_{\mathrm{Gauss}}}, gλ,v(x,y)tv=log||x,y|v1g_{\lambda,v}(x,y)-t_{v}=\log||x,y|_{v}^{-1}. Therefore κv=0\kappa_{v}=0 for all but finitely many vMKv\in M_{K}. So, if μ=(μv)vMK,ν=(νv)vMK\mu=(\mu_{v})_{v\in M_{K}},\nu=(\nu_{v})_{v\in M_{K}} are positive adelic measures, then integrating (3.5) at each place gives |μv,νvλ,t,vcμcνtvμv,νv|κvcμcν\big{|}\langle\mu_{v},\nu_{v}\rangle_{\lambda,t,v}-c_{\mu}c_{\nu}t_{v}-\langle\mu_{v},\nu_{v}\rangle\big{|}\leq\kappa_{v}c_{\mu}c_{\nu}. Therefore, using the fact that tvt_{v} is non-negative, we have |μv,νvλ,t,vμv,νv|cμcν(κv+tv)|\langle\mu_{v},\nu_{v}\rangle_{\lambda,t,v}-\langle\mu_{v},\nu_{v}\rangle|\leq c_{\mu}c_{\nu}(\kappa_{v}+t_{v}). Multiplying by rvr_{v} and summing over all places of KK gives item (2) with κ=vrvκv\kappa=\sum_{v}r_{v}\kappa_{v}. ∎

For the remainder of this section, fix an adelic probability measure λ=(λv)vMK\lambda=(\lambda_{v})_{v\in M_{K}} and a normalization of gλ,vg_{\lambda,v} at each place vv. The next proposition will allow us to use the positive definiteness of the mutual energy pairing on 𝒜K0\mathcal{A}_{K}^{0} to deduce the positive definiteness of ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t}.

Proposition 3.3.

For any μ,ν𝒜K\mu,\nu\in\mathcal{A}_{K}, we have μ,νλ,t=((μcμλ,νcνλ))+cμcν¯t\langle\mu,\nu\rangle_{\lambda,t}=(\!(\mu-c_{\mu}\lambda,\nu-c_{\nu}\lambda)\!)+c_{\mu}\overline{c_{\nu}}t. In particular, μ,νλ,t=((μ,ν))\langle\mu,\nu\rangle_{\lambda,t}=(\!(\mu,\nu)\!) whenever μ,ν𝒜K0\mu,\nu\in\mathcal{A}_{K}^{0}.

Proof.

Let μ=(μv)vMK\mu=(\mu_{v})_{v\in M_{K}} and ν=(νv)vMK\nu=(\nu_{v})_{v\in M_{K}} be adelic measures. We assume first that μv(𝐏v1)=ν(𝐏v1)=0\mu_{v}(\mathbf{P}_{v}^{1})=\nu(\mathbf{P}_{v}^{1})=0. That μv\mu_{v} and νv\nu_{v} are log-continuous Radon measures on 𝐏v1\mathbf{P}_{v}^{1} implies that μ\mu and ν\nu do not charge the point at infinity; moreover μvνv¯(Diag)=0\mu_{v}\otimes\overline{\nu_{v}}(\mathrm{Diag})=0. By (2.1), we have

μv,νvv\displaystyle\langle\mu_{v},\nu_{v}\rangle_{v} =𝐏v1𝐏v1log||x,y||vdμv(x)dνv¯(y)\displaystyle=\int_{\mathbf{P}_{v}^{1}}\int_{\mathbf{P}_{v}^{1}}-\log||x,y||_{v}\;d\mu_{v}(x)d\overline{\nu_{v}}(y)
=𝐀v1𝐀v1(logδv(x,y)log||x,||vlog||y,||v)dμv(x)dνv¯(y)\displaystyle=\int_{\mathbf{A}_{v}^{1}}\int_{\mathbf{A}_{v}^{1}}\big{(}-\log\delta_{v}(x,y)-\log||x,\infty||_{v}-\log||y,\infty||_{v}\big{)}\;d\mu_{v}(x)\;d\overline{\nu_{v}}(y)
=𝐀v1×𝐀v1logδv(x,y)dμvνv¯(x,y)νv¯(𝐏v1)𝐏v1log||x,||vdμv(x)\displaystyle=\iint_{\mathbf{A}_{v}^{1}\times\mathbf{A}_{v}^{1}}-\log\delta_{v}(x,y)\;d\mu_{v}\otimes\overline{\nu_{v}}(x,y)-\overline{\nu_{v}}(\mathbf{P}_{v}^{1})\int_{\mathbf{P}_{v}^{1}}\log||x,\infty||_{v}\;d\mu_{v}(x)
μv(𝐏v1)𝐏v1log||y,||vdνv¯(y)\displaystyle\qquad-\mu_{v}(\mathbf{P}_{v}^{1})\int_{\mathbf{P}_{v}^{1}}\log||y,\infty||_{v}\;d\overline{\nu_{v}}(y)
=𝐀v1×𝐀v1Diaglogδv(x,y)dμνv¯(x,y)\displaystyle=\iint_{\mathbf{A}_{v}^{1}\times\mathbf{A}_{v}^{1}\setminus\mathrm{Diag}}-\log\delta_{v}(x,y)\;d\mu\otimes\overline{\nu_{v}}(x,y)
=((μv,νv))v,\displaystyle=(\!(\mu_{v},\nu_{v})\!)_{v},

where we have used the assumption μv(𝐏v1)=νv(𝐏v1)=0\mu_{v}(\mathbf{P}_{v}^{1})=\nu_{v}(\mathbf{P}_{v}^{1})=0. Multiplying by rvr_{v} and summing over all places shows that μ,ν=((μ,ν))\langle\mu,\nu\rangle=(\!(\mu,\nu)\!) when μ\mu and ν\nu have total mass 0.
Now, assuming that μ\mu and ν\nu have arbitrary mass cμc_{\mu} and cνc_{\nu}, we apply the above result to μcμλ\mu-c_{\mu}\lambda and νcνλ\nu-c_{\nu}\lambda and invoke item (1) of Proposition (3.2) to find

μ,νλ,tcμcν¯t=μcμλ,νcνλ=((μcμλ,νcνλ)).\langle\mu,\nu\rangle_{\lambda,t}-c_{\mu}\overline{c_{\nu}}t=\langle\mu-c_{\mu}\lambda,\nu-c_{\nu}\lambda\rangle=(\!(\mu-c_{\mu}\lambda,\nu-c_{\nu}\lambda)\!).

Remark 2.

If λ\lambda is taken to be the canonical adelic measure μg\mu_{g} of a rational map gg with degree at least 22, and if ff is another rational map of degree at least 22, then Proposition 3.3 gives the following relationship between μg,t\|\cdot\|_{\mu_{g},t} and the Arakelov–Zhang pairing:

(3.6) limt0μfμg,t2=((μfμg,μfμg))=2(f,g)AZ,\lim_{t\to 0}\|\mu_{f}\|_{\mu_{g},t}^{2}=(\!(\mu_{f}-\mu_{g},\mu_{f}-\mu_{g})\!)=2(f,g)_{\mathrm{AZ}},

where, as remarked in the introduction, the last equality is due to Fili (Theorem 9, [Fil17]).

Corollary 3.4.

For all μ𝒜K\mu\in\mathcal{A}_{K}, μ,μλ,t=μλ,t2|cμ|2t\langle\mu,\mu\rangle_{\lambda,t}=\|\mu\|^{2}_{\lambda,t}\geq|c_{\mu}|^{2}t with equality if and only if μ=cμλ\mu=c_{\mu}\lambda.

Proof.

Propositions 2.6 and 4.5 of [FR06] state that if ρv\rho_{v} is a signed measure of total mass 0 on 𝐏v1\mathbf{P}_{v}^{1}, then ((ρv,ρv))v0(\!(\rho_{v},\rho_{v})\!)_{v}\geq 0, with equality if and only if ρv=0\rho_{v}=0. See also Theorem 8.72 of [BR10] and Theorem 5.3 of [BR06]. Consequently, if μ=(μv)vMK𝒜K\mu=(\mu_{v})_{v\in M_{K}}\in\mathcal{A}_{K} is a signed adelic measure then Proposition 3.3 implies μ,μλ,t=((μcμλ,μcμλ))+|cμ|2t|cμ|2t\langle\mu,\mu\rangle_{\lambda,t}=(\!(\mu-c_{\mu}\lambda,\mu-c_{\mu}\lambda)\!)+|c_{\mu}|^{2}t\geq|c_{\mu}|^{2}t with equality if and only if μ=cμλ\mu=c_{\mu}\lambda. We recall that if μ\mu is a complex-valued adelic measure, say μv=μr,v+iμi,v\mu_{v}=\mu_{r,v}+i\mu_{i,v} at each place, then μr=(μr,v)vMK\mu_{r}=(\mu_{r,v})_{v\in M_{K}} and μi=(μi,v)vMK\mu_{i}=(\mu_{i,v})_{v\in M_{K}} are signed adelic measures. Therefore

μv,μvλ,t\displaystyle\langle\mu_{v},\mu_{v}\rangle_{\lambda,t} =μr+iμi,μr+iμiλ,t\displaystyle=\langle\mu_{r}+i\mu_{i},\mu_{r}+i\mu_{i}\rangle_{\lambda,t}
=μrλ,t2μr,iμiλ,tiμi,μrλ,t+μiλ,t2\displaystyle=\|\mu_{r}\|_{\lambda,t}^{2}-\langle\mu_{r},i\mu_{i}\rangle_{\lambda,t}-\langle i\mu_{i},\mu_{r}\rangle_{\lambda,t}+\|\mu_{i}\|^{2}_{\lambda,t}
=μrλ,t2+iμr,μiλ,tiμi,μrλ,t+μiλ,t2\displaystyle=\|\mu_{r}\|_{\lambda,t}^{2}+i\langle\mu_{r},\mu_{i}\rangle_{\lambda,t}-i\langle\mu_{i},\mu_{r}\rangle_{\lambda,t}+\|\mu_{i}\|^{2}_{\lambda,t}
=μrλ,t2+μiλ,t2.\displaystyle=\|\mu_{r}\|^{2}_{\lambda,t}+\|\mu_{i}\|^{2}_{\lambda,t}.

Now μrλ,t2|cμr|2t\|\mu_{r}\|_{\lambda,t}^{2}\geq|c_{\mu_{r}}|^{2}t with equality if and only if μr=cμrλ\mu_{r}=c_{\mu_{r}}\lambda; similar remarks apply to μi\mu_{i}. Thus

μλ,t2=μrλ,t2+μiλ,t2(|cμr|2+|cμi|2)t=|cμ|2t\|\mu\|^{2}_{\lambda,t}=\|\mu_{r}\|^{2}_{\lambda,t}+\|\mu_{i}\|^{2}_{\lambda,t}\geq(|c_{\mu_{r}}|^{2}+|c_{\mu_{i}}|^{2})t=|c_{\mu}|^{2}t

with equality if and only if μr=cμrλ\mu_{r}=c_{\mu_{r}}\lambda and μi=cμiλ\mu_{i}=c_{\mu_{i}}\lambda. That is, equality holds if and only if μ=cμλ=(cμr+icμi)λ\mu=c_{\mu}\lambda=(c_{\mu_{r}}+ic_{\mu_{i}})\lambda. ∎

It follows from Corollary 3.4 that μλ,t20\|\mu\|^{2}_{\lambda,t}\geq 0 with equality if and only if μ=0λ=0\mu=0\lambda=0. Thus ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} is positive-definite on 𝒜K\mathcal{A}_{K}. Since ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} is linear in the first coordinate and conjugate symmetric, then we have shown that ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} is an inner product on 𝒜K\mathcal{A}_{K}. Proposition 3.3 shows that ,λ,t\langle\cdot,\cdot\rangle_{\lambda,t} extends the mutual energy pairing to 𝒜K\mathcal{A}_{K}. To finish the proof of Theorem 3.1 we need only show the statement on weak convergence. We remark that Favre and Rivera-Letelier show a more general statement which holds for differences of probability measures; see Propositions 2.11 and 4.12 of [FR06]. We denote by |μ|(𝐏v1)|\mu|(\mathbf{P}_{v}^{1}) the total variation of a complex valued measure μ\mu on 𝐏v1\mathbf{P}_{v}^{1}.

Proposition 3.5.

Let μn,μ𝒜K\mu_{n},\mu\in\mathcal{A}_{K} and suppose that μnμλ,t20\|\mu_{n}-\mu\|^{2}_{\lambda,t}\to 0 as nn\to\infty. Let vMKv\in M_{K}. Then:

  1. (1)

    For every ϕC(𝐏v1)BDVv\phi\in C(\mathbf{P}_{v}^{1})\cap\mathrm{BDV}_{v}, ϕ𝑑μn,vϕ𝑑μv\int\phi\,d\mu_{n,v}\to\int\phi\,d\mu_{v} as nn\to\infty;

  2. (2)

    If supn1|μn,v|(𝐏v1)<\sup_{n\geq 1}|\mu_{n,v}|(\mathbf{P}_{v}^{1})<\infty then μn,vμv\mu_{n,v}\to\mu_{v} weakly as nn\to\infty.

Proof.

By Replacing μn\mu_{n} with μnμ\mu_{n}-\mu, we assume that μ=0\mu=0. We note that it suffices to prove the proposition with 2\|\cdot\|^{2} in place of λ,t2\|\cdot\|_{\lambda,t}^{2}. Indeed, by Proposition 3.2, if μnλ,t20\|\mu_{n}\|_{\lambda,t}^{2}\to 0 then μncμnλ2+|cμn|2t0\|\mu_{n}-c_{\mu_{n}}\lambda\|^{2}+|c_{\mu_{n}}|^{2}t\to 0 as nn\to\infty; so μncμnλ\|\mu_{n}-c_{\mu_{n}}\lambda\| and |cμn||c_{\mu_{n}}| both tend to 0 as nn goes to infinity. Then the triangle inequality implies lim supnμnlim supn(μncμnλ+|cμ|λ)=0.\limsup_{n\to\infty}\|\mu_{n}\|\leq\limsup_{n\to\infty}(\|\mu_{n}-c_{\mu_{n}}\lambda\|+|c_{\mu}|\|\lambda\|)=0. So μnλ,t0\|\mu_{n}\|_{\lambda,t}\to 0 implies μ0\|\mu\|\to 0.

Let Ev=C(𝐏v1)BDV(𝐏v1)E_{v}=C(\mathbf{P}_{v}^{1})\cap\mathrm{BDV}(\mathbf{P}_{v}^{1}), and let ϕEv\phi\in E_{v}. In both non-Archimedean and Archimedean cases, EvE_{v} is a dense subspace of C(𝐏v1)C(\mathbf{P}_{v}^{1}) (Proposition 5.4 and Example 5.18 of [BR10] when vv\nmid\infty; for 1(){\mathbb{P}}^{1}({\mathbb{C}}), this is well known - in fact, EvE_{v} includes the smooth functions for Archimedean vv).
That ϕEv\phi\in E_{v} implies that Δϕ\Delta\phi exits, and, from Propositions 2.2, 2.1, we have

UΔϕ(x)=log1||x,y||vd(Δϕ)(y)=ϕ(y)𝑑Δylog1||x,y||=ϕ(x)ϕ(y)𝑑λAr,v(y)U_{\Delta\phi}(x)=\int\log\frac{1}{||x,y||_{v}}\;d(\Delta\phi)(y)=\int\phi(y)\;d\Delta_{y}\log\frac{1}{||x,y||}=\phi(x)-\int\phi(y)\;d\lambda_{\mathrm{Ar},v}(y)

so that UΔϕU_{\Delta\phi} differs from ϕ\phi by a constant. In particular UΔϕU_{\Delta\phi} is continuous. By Proposition 2.2, ΔUμn,v=μn,vμn,v(𝐏v1)λAr,v\Delta U_{\mu_{n,v}}=\mu_{n,v}-\mu_{n,v}(\mathbf{P}_{v}^{1})\lambda_{\mathrm{Ar},v} and therefore

ϕ𝑑μn,v\displaystyle\int\phi\;d\mu_{n,v} =fd(ΔUμn,v+μn,v(𝐏v1)λAr,v)\displaystyle=\int f\;d(\Delta U_{\mu_{n,v}}+\mu_{n,v}(\mathbf{P}_{v}^{1})\lambda_{\mathrm{Ar},v})
=Uμn,v𝑑Δϕ+μn,v(𝐏v1)ϕ𝑑λAr,v\displaystyle=\int U_{\mu_{n,v}}\;d\Delta\phi+\mu_{n,v}(\mathbf{P}_{v}^{1})\int\phi\;d\lambda_{\mathrm{Ar},v}
=μn,v,Δϕv+μn,v(𝐏v1)ϕ𝑑λAr,v.\displaystyle=\langle\mu_{n,v},\Delta\phi\rangle_{v}+\mu_{n,v}(\mathbf{P}_{v}^{1})\int\phi\;d\lambda_{\mathrm{Ar},v}.

As log||x,y||v10\log||x,y||_{v}^{-1}\geq 0, the local form ,v\langle\cdot,\cdot\rangle_{v} is always at least positive semi-definite; in particular, the Cauchy-Schwarz inequality applies. Thus |μn,v,Δϕv|μn,vvΔϕv|\langle\mu_{n,v},\Delta\phi\rangle_{v}|\leq\|\mu_{n,v}\|_{v}\|\Delta\phi\|_{v} and so

|ϕ𝑑μn,v|μn,vvΔϕv+|μn,v(𝐏v1)||ϕ|𝑑λAr,v.\bigg{|}\int\phi\;d\mu_{n,v}\bigg{|}\leq\|\mu_{n,v}\|_{v}\|\Delta\phi\|_{v}+\left|\mu_{n,v}(\mathbf{P}_{v}^{1})\right|\int|\phi|\;d\lambda_{\mathrm{Ar},v}.

From Corollary 3.4, that μn0\|\mu_{n}\|\to 0 implies |μn,v(𝐏v1)|0|\mu_{n,v}(\mathbf{P}_{v}^{1})|\to 0 as nn\to\infty, and by assumption μn,vv2\|\mu_{n,v}\|_{v}^{2} also tends to 0 as nn\to\infty. Consequently ϕ𝑑μn,v0asn\int\phi\;d\mu_{n,v}\to 0\operatorname{\;\;\text{as}\;\;}n\to\infty for all ϕEv\phi\in E_{v}, which shows the first statement. The second statement follows from the first and from the fact that EvE_{v} is dense in C(𝐏v1)C(\mathbf{P}_{v}^{1}). ∎

Remark 3.

It is easy to see that weak convergence at each place does not give convergence in the norm of 𝒜K\mathcal{A}_{K}. Here is a simple illustration. For each place vKv\in K, let νv\nu_{v} be any log-continuous Radon measure of total mass 0 with rvνvv2=1r_{v}\|\nu_{v}\|_{v}^{2}=1. Enumerating the places of KK by vnv_{n} (n1)n\geq 1), let μn\mu_{n} be the adelic measure which is the zero measure at all places vvnv\neq v_{n} and μn,vn=νv\mu_{n,v_{n}}=\nu_{v}. Then μn2=1\|\mu_{n}\|^{2}=1 for all nn, yet μn,v0\mu_{n,v}\to 0 weakly at each place.

The following observation will be useful in the following section.

Proposition 3.6.

Let μ=(μv)vMK𝒜K\mu=(\mu_{v})_{v\in M_{K}}\in\mathcal{A}_{K} be an adelic probability measure with ((μ,μ))=0(\!(\mu,\mu)\!)=0. Then μ2=2vMKrvUμ,v()\|\mu\|^{2}=2\sum_{v\in M_{K}}r_{v}U_{\mu,v}(\infty). In particular, μf2=2vMKrvUf,v()\|\mu_{f}\|^{2}=2\sum_{v\in M_{K}}r_{v}U_{f,v}(\infty) whenever ff is a polynomial.

Proof.

By (2.1) we have

μvv2\displaystyle\|\mu_{v}\|^{2}_{v} =log1δv(x,y)dμv(x)𝑑μv(y)+log1||x,||vdμv(x)𝑑μv(y)+log1||y,||vdμv(x)𝑑μv(y)\displaystyle=\iint\log\frac{1}{\delta_{v}(x,y)}\,d\mu_{v}(x)\,d\mu_{v}(y)+\iint\log\frac{1}{||x,\infty||_{v}}\,d\mu_{v}(x)\,d\mu_{v}(y)+\iint\log\frac{1}{||y,\infty||_{v}}\,d\mu_{v}(x)\,d\mu_{v}(y)
=((μv,μv))v+2Uμ,v().\displaystyle=(\!(\mu_{v},\mu_{v})\!)_{v}+2U_{\mu,v}(\infty).

Thus μ2=vMKrv(((μv,μv))v+2Uμ,v())=((μ,μ))+2vMKrvUμ,v()=2vMKrvUμ,v()\|\mu\|^{2}=\sum_{v\in M_{K}}r_{v}((\!(\mu_{v},\mu_{v})\!)_{v}+2U_{\mu,v}(\infty))=(\!(\mu,\mu)\!)+2\sum_{v\in M_{K}}r_{v}U_{\mu,v}(\infty)=2\sum_{v\in M_{K}}r_{v}U_{\mu,v}(\infty). As remarked in the introduction, a result of Baker and Hsia implies ((μf,μf))=0(\!(\mu_{f},\mu_{f})\!)=0 whenever ff is a polynomial [BH05]; this also follows from Lemme 5.3 of [FR06]. Therefore μf2=2vMKrvUf,v()\|\mu_{f}\|^{2}=2\sum_{v\in M_{K}}r_{v}U_{f,v}(\infty) in this case. ∎

4. Comparison With the Arakelov Height: Monic Polynomials

In both this section and the next, the pull-back of a measure on 𝐏v1\mathbf{P}_{v}^{1} by a rational map ff will play an important role. We briefly summarize the discussion in chapter 9 of [BR10]. Given a rational map ff defined over v{\mathbb{C}}_{v} and a continuous function ϕ\phi defined on f1(V)f^{-1}(V) of 𝐏v1\mathbf{P}_{v}^{1}, where VV is a subset of 𝐏v1\mathbf{P}_{v}^{1}, the push-forward of ϕ\phi by ff is the function (fϕ)(z)=f(ζ)=zmf(ζ)ϕ(ζ)(f_{*}\phi)(z)=\sum_{f(\zeta)=z}m_{f}(\zeta)\phi(\zeta). Here mf(ζ)m_{f}(\zeta) is an extension of the notion of algebraic multiplicity to 𝐏v1\mathbf{P}_{v}^{1}. In particular, if zvz\in{\mathbb{C}}_{v} and αi\alpha_{i} are the roots of f(ζ)=zf(\zeta)=z counting multiplicity, then (fϕ)(z)=i=1deg(f)ϕ(αi)(f_{*}\phi)(z)=\sum_{i=1}^{\deg(f)}\phi(\alpha_{i}). The function fϕf_{*}\phi is defined and continuous on VV. Given a Radon probability measure μ\mu on 𝐏v1\mathbf{P}_{v}^{1}, the pull-back of μ\mu by ff, written fμf^{*}\mu, is defined to be the unique Radon measure with ϕ𝑑fμ=fϕ𝑑μ\int\phi\;df^{*}\mu=\int f_{*}\phi\;d\mu. From this definition and the fact that f(ζ)=zmf(ζ)=deg(f)\sum_{f(\zeta)=z}m_{f}(\zeta)=\deg(f) for all z𝐏v1z\in\mathbf{P}_{v}^{1} we find that f(fμ)=deg(f)μf_{*}(f^{*}\mu)=\deg(f)\cdot\mu, where f(ν)f_{*}(\nu) is the usual push-forward of a measure ν\nu. For proofs of these claims, see chapter 9 of [BR10]. We recall that the canonical measure of ff on 𝐏v1\mathbf{P}_{v}^{1} is characterized among log-continuous probability measures by fμf,v=deg(f)μf,vf^{*}\mu_{f,v}=\deg(f)\mu_{f,v}.

The Arakelov height of a rational map ff of degree dd is the Arakelov height of the coefficients of ff, viewed as a point in projective space. Thus, if f(z)=adzd++a0bdzd++b0f(z)=\frac{a_{d}z^{d}+\cdots+a_{0}}{b_{d}z^{d}+\cdots+b_{0}} (where one of ada_{d} or bdb_{d} is non-zero) is defined over KK, then hAr(f)=vMKrvlog|f|vh_{Ar}(f)=\sum_{v\in M_{K}}r_{v}\log|f|_{v}, where

|f|v={max0i,jd(|ai|v,|bj|v)ifv,(i=0d|ai|v2+|bi|v2)1/2ifv.|f|_{v}=\begin{cases}\max_{0\leq i,j\leq d}(|a_{i}|_{v},|b_{j}|_{v})&\operatorname{\;\;\text{if}\;\;}v\nmid\infty,\\ \left(\sum_{i=0}^{d}|a_{i}|_{v}^{2}+|b_{i}|_{v}^{2}\right)^{1/2}&\operatorname{\;\;\text{if}\;\;}v\mid\infty.\end{cases}

In particular, if f(z)=zd+ad1zd1++a0f(z)=z^{d}+a_{d-1}z^{d-1}+\cdots+a_{0} is a monic polynomial defined over KK, then |f|v=(2+i=0d1|ai|v2)1/2|f|_{v}=\left(2+\sum_{i=0}^{d-1}|a_{i}|_{v}^{2}\right)^{1/2} for Archimedean vv and |f|v=maxi(1,|ai|v)|f|_{v}=\max_{i}(1,|a_{i}|_{v}) at finite places vv of KK. The main theorem of this section is the following estimate on the norm μf\|\mu_{f}\| when ff is a monic polynomial.

Theorem 4.1.

Let f(z)=zd+ad1zd1++a0f(z)=z^{d}+a_{d-1}z^{d-1}+\cdots+a_{0} be a monic polynomial of degree d2d\geq 2 defined over KK. Then d2μf2=hAr(f)+O(1)\frac{d}{2}\|\mu_{f}\|^{2}=h_{\mathrm{Ar}}(f)+O(1), where the implied constants depend only on dd.

This and the second item of Proposition 3.2 imply Theorem 1.2 from the introduction. The strategy for proving Theorem 4.1 is to make use of the (classical) filled Julia set, which, following [Ben19], we denote by 𝒦I,v{\mathcal{K}}_{I,v}. This is defined to be those elements of v{\mathbb{C}}_{v} which are bounded under iteration by ff, hence 𝒦I,v={zv:limn|fn(z)|v}{\mathcal{K}}_{I,v}=\{z\in{\mathbb{C}}_{v}:\lim_{n\to\infty}|f^{n}(z)|_{v}\neq\infty\}. When vv is Archimedean, this is the usual filled Julia set from complex dynamics. For finite places vv, this consists of the Type I points of the Berkovich filled Julia set, 𝒦v{\mathcal{K}}_{v}, which is defined by

𝒦v={ζ𝐏v1:limnfn(ζ)},so that𝒦I,v=𝒦vv.{\mathcal{K}}_{v}=\{\zeta\in\mathbf{P}_{v}^{1}:\lim_{n\to\infty}f^{n}(\zeta)\neq\infty\},\;\text{so that}\;{\mathcal{K}}_{I,v}={\mathcal{K}}_{v}\cap{\mathbb{C}}_{v}.

At each place vv, the Julia set 𝒥v{\mathcal{J}}_{v} can be defined as the topological boundary of 𝒦v{\mathcal{K}}_{v}. As in the classical case, μf,v\mu_{f,v} is supported on 𝒥v{\mathcal{J}}_{v}. We can therefore control the norm μf2\|\mu_{f}\|^{2} via escape rate arguments at each place. Namely, we employ escape rate arguments to prove the following.

Lemma 4.2.

Let ff be a monic polynomial of degree d2d\geq 2 defined over v{\mathbb{C}}_{v} and let y𝒦I,vy\in{\mathcal{K}}_{I,v}. Let fy(z)f_{y}(z) be the polynomial f(z)yf(z)-y. There are positive constants AvA_{v} and BvB_{v} depending only on the degree dd so that Av|f|v|fy|vBv|f|vA_{v}|f|_{v}\leq|f_{y}|_{v}\leq B_{v}|f|_{v}. Furthermore, Av=Bv=1A_{v}=B_{v}=1 when vv is non-Archimedean.

We defer the proof of Lemma 4.2 to the end of this section. We will also need to know how the roots of a monic polynomial are related to the quantities |f|v|f|_{v}.

Lemma 4.3.

Let ff be a monic polynomial of degree d2d\geq 2 defined over v{\mathbb{C}}_{v}. Factor f(z)f(z) over v{\mathbb{C}}_{v} as f(z)=i=1d(zαi)f(z)=\prod_{i=1}^{d}(z-\alpha_{i}). There are positive constants CvC_{v} and DvD_{v} depending only on the degree dd so that Cv|f|vi=1d||αi,||v1Dv|f|vC_{v}|f|_{v}\leq\prod_{i=1}^{d}||\alpha_{i},\infty||_{v}^{-1}\leq D_{v}|f|_{v}. Furthermore, Cv=Dv=1C_{v}=D_{v}=1 when vv is non-Archimedean

This is proved as part of Theorem VIII.5.9 of [Sil09]. (Silverman uses max(1,|α|v)\max(1,|\alpha|_{v}) at the infinite places, but, with minor modifications, the same proof works with ||αi,||v1=1+|α|v2||\alpha_{i},\infty||_{v}^{-1}=\sqrt{1+|\alpha|_{v}^{2}} instead of max(1,|α|v)\max(1,|\alpha|_{v}).) We turn to the proof of Theorem 4.1.

Proof of Theorem 4.1.

By Proposition 3.6, we have vMKrvUμ,v()=12μf2\sum_{v\in M_{K}}r_{v}U_{\mu,v}(\infty)=\frac{1}{2}\|\mu_{f}\|^{2}. The characterizing equation fμf,v=dμf,vf^{*}\mu_{f,v}=d\mu_{f,v} implies

(4.1) d2μf2=dvMKrvUf,v()=vMKrvf(z)=ymf(z)log1||z,||vdμf,v(y).\frac{d}{2}\|\mu_{f}\|^{2}=d\sum_{v\in M_{K}}r_{v}U_{f,v}(\infty)=\sum_{v\in M_{K}}r_{v}\int\sum_{f(z)=y}m_{f}(z)\log\frac{1}{||z,\infty||_{v}}\;d\mu_{f,v}(y).

Thus, it suffices to bound dUf,v()=f(z)=ymf(z)log||z,||v1dμf,v(y)dU_{f,v}(\infty)=\int\sum_{f(z)=y}m_{f}(z)\log||z,\infty||^{-1}_{v}\;d\mu_{f,v}(y) in terms of |f|v|f|_{v}.

Suppose that vv is non-Archimedean. Define ψ:𝐀v1[0,)\psi:\mathbf{A}_{v}^{1}\to[0,\infty) by ψ(ζ)=log||ζ,||v\psi(\zeta)=-\log||\zeta,\infty||_{v}. Then ψ\psi is continuous on 𝐀v1\mathbf{A}_{v}^{1}. That ff fixes the point at infinity implies that the push forward (fψ)(ζ)=f(α)=ζmf(α)log||α,||v1(f_{*}\psi)(\zeta)=\sum_{f(\alpha)=\zeta}m_{f}(\alpha)\log||\alpha,\infty||_{v}^{-1} is also continuous on 𝐀v1\mathbf{A}_{v}^{1}. Let y𝒦I,vy\in{\mathcal{K}}_{I,v}. Factor f(z)yf(z)-y over v{\mathbb{C}}_{v} as f(z)y=i=1d(zαi)f(z)-y=\prod_{i=1}^{d}(z-\alpha_{i}), counting multiplicities. Then (fψ)(y)=logi=1d||αi,||v1(f_{*}\psi)(y)=\log\prod_{i=1}^{d}||\alpha_{i},\infty||_{v}^{-1}. Apply Lemma 4.3 to the polynomial fy(z)=f(z)yf_{y}(z)=f(z)-y to conclude that (fψ)(y)=log|fy|v(f_{*}\psi)(y)=\log|f_{y}|_{v}. From Lemma 4.2, then (fψ)(y)=log|fy|v=log|f|v.(f_{*}\psi)(y)=\log|f_{y}|_{v}=\log|f|_{v}. That v{\mathbb{C}}_{v} is dense in 𝐀v1\mathbf{A}_{v}^{1} implies that 𝒦I,v{\mathcal{K}}_{I,v} is dense in 𝒦v{\mathcal{K}}_{v}. Thus fψf_{*}\psi is a continuous function which is equal to the constant log|f|v\log|f|_{v} on a dense subset of 𝒦v{\mathcal{K}}_{v}. Hence (fψ)(ζ)=log|f|v(f_{*}\psi)(\zeta)=\log|f|_{v} for all ζ𝒦v\zeta\in{\mathcal{K}}_{v}. As suppμf,v𝒦v\mathrm{supp}\;\mu_{f,v}\subset{\mathcal{K}}_{v}, then dUf,v()=(fψ)𝑑μf,v=log|f|vdU_{f,v}(\infty)=\int(f_{*}\psi)\;d\mu_{f,v}=\log|f|_{v}.

The Archimedean case is similar: let y𝒦vy\in{\mathcal{K}}_{v} and factor f(z)yf(z)-y over {\mathbb{C}} as f(z)y=i=1d(zαi)f(z)-y=\prod_{i=1}^{d}(z-\alpha_{i}), counting multiplicities. By Lemmas 4.3 and 4.2 we find that logi=1d1+|αi|v2=log|fy|v+O(1)\log\prod_{i=1}^{d}\sqrt{1+|\alpha_{i}|_{v}^{2}}=\log|f_{y}|_{v}+O(1) and that log|fy|v=log|f|v+O(1)\log|f_{y}|_{v}=\log|f|_{v}+O(1); therefore logi=1d1+|αi|v2=log|f|v+O(1)\log\prod_{i=1}^{d}\sqrt{1+|\alpha_{i}|_{v}^{2}}=\log|f|_{v}+O(1). As suppμf,v𝒦v\mathrm{supp}\;\mu_{f,v}\subset{\mathcal{K}}_{v}, we simply integrate this with respect to yy to find dUf,v()=log|f|v+O(1)dU_{f,v}(\infty)=\log|f|_{v}+O(1), where, as in the statements of Lemmas 4.3 and 4.2, the implied constants depend only on the degree of ff. Multiplying dUf,v()dU_{f,v}(\infty) by rvr_{v}, summing over all places, and applying (4.1) gives the theorem. ∎

Proof of Lemma 4.2.

Suppose vv\nmid\infty. An elementary escape rate argument shows that |y|v|f|v|y|_{v}\leq|f|_{v} for all y𝒦I,vy\in{\mathcal{K}}_{I,v}. Thus, if |ak|v=|f|v=max0jd1(1,|aj|v)|a_{k}|_{v}=|f|_{v}=\max_{0\leq j\leq d-1}(1,|a_{j}|_{v}) for some k>0k>0, then |ak|v|a0|v|a_{k}|_{v}\geq|a_{0}|_{v} and |ak|v|y|v|a_{k}|_{v}\geq|y|_{v}. So |ak|vmax(|a0|v,|y|v)|a0y|v|a_{k}|_{v}\geq\max(|a_{0}|_{v},|y|_{v})\geq|a_{0}-y|_{v}. Hence

|fy|v=max(1,|aj|v,|a0y|v)=|f|v.|f_{y}|_{v}=\max(1,|a_{j}|_{v},|a_{0}-y|_{v})=|f|_{v}.

Similarly, if |f|v=1|f|_{v}=1 then |fy|v=1|f_{y}|_{v}=1. So assume |a0|v=|f|v>1|a_{0}|_{v}=|f|_{v}>1 and |ak|v<|f|v|a_{k}|_{v}<|f|_{v} for 1kd11\leq k\leq d-1. We claim that then |y|v<|f|v|y|_{v}<|f|_{v}. Indeed, if |y|v=|f|v|y|_{v}=|f|_{v} then |yd|v>|ajyj|v|y^{d}|_{v}>|a_{j}y^{j}|_{v} for 0j<d0\leq j<d so that |f(y)|v=|y|d|f(y)|_{v}=|y|^{d} (by the equality case of the strong triangle inequality). Iterating this equation shows that |fn(y)|v|f^{n}(y)|_{v}\to\infty so that y𝒦I,vy\notin{\mathcal{K}}_{I,v}. Thus |y|v<|f|v|y|_{v}<|f|_{v} and so |a0y|v=|a0|v=|f|v|a_{0}-y|_{v}=|a_{0}|_{v}=|f|_{v}; it follows that max1jd1(1,|aj|v,|a0y|v)=max0jd1(1,|aj|v)\max_{1\leq j\leq d-1}(1,|a_{j}|_{v},|a_{0}-y|_{v})=\max_{0\leq j\leq d-1}(1,|a_{j}|_{v}).

We turn to the Archimedean case. To ease notation, we omit the dependence on vv. The quantity Ef:=1+j=0d1|aj|E_{f}:=1+\sum_{j=0}^{d-1}|a_{j}| is more amenable to study than |f||f|. Clearly (1/2)|f|Ef(1/2)|f|\leq E_{f}, and, by Jensen’s inequality applied to the map tt2t\mapsto t^{2}, we find that Efd|f|vE_{f}\leq\sqrt{d}|f|_{v}. So it is enough to show that the lemma holds at Archimedean places with EfE_{f} in place of |f||f|.

An easy escape rate argument shows that |y|Ef|y|\leq E_{f} for yy in the filled Julia set. By the triangle inequality

Efy=1+|a0y|+j=1d1|aj|1+|a0|+Ef+j=1d1|aj|2Ef,E_{f_{y}}=1+|a_{0}-y|+\sum_{j=1}^{d-1}|a_{j}|\leq 1+|a_{0}|+E_{f}+\sum_{j=1}^{d-1}|a_{j}|\leq 2E_{f},

which gives the upper bound. For the lower bound, we break into cases depending on the size of the constant term. Suppose that 1+j=1d1|aj|ϵ|a0|1+\sum_{j=1}^{d-1}|a_{j}|\geq\epsilon|a_{0}|, where ϵ(0,1/2)\epsilon\in(0,1/2) is an absolute constant to be determined later. Thus 1+j=1d1|aj|ϵ1+ϵEf1+\sum_{j=1}^{d-1}|a_{j}|\geq\frac{\epsilon}{1+\epsilon}E_{f}, which implies

Efy=1+|a0y|+j=1d1|aj|ϵ1+ϵEf.E_{f_{y}}=1+|a_{0}-y|+\sum_{j=1}^{d-1}|a_{j}|\geq\frac{\epsilon}{1+\epsilon}E_{f}.

So assume that 1+j=1d1|aj|<ϵ|a0|1+\sum_{j=1}^{d-1}|a_{j}|<\epsilon|a_{0}|. We claim that then |y|(1ϵ)|a0||y|\leq(1-\epsilon)|a_{0}|. Suppose to the contrary that |y|>(1ϵ)|a0||y|>(1-\epsilon)|a_{0}|. Then |y|>ϵ1(1ϵ)>1|y|>\epsilon^{-1}(1-\epsilon)>1, as |a0|>ϵ1|a_{0}|>\epsilon^{-1} and ϵ<1/2\epsilon<1/2. Now

|f(y)|\displaystyle|f(y)| =|yd+ad1yd1++a0|\displaystyle=|y^{d}+a_{d-1}y^{d-1}+\cdots+a_{0}|
|y|d(|a0|+|y|d1j=1d1|aj|)\displaystyle\geq|y|^{d}-\left(|a_{0}|+|y|^{d-1}\sum_{j=1}^{d-1}|a_{j}|\right)
|y|d(|a0|+|y|d1(ϵ|a0|1))\displaystyle\geq|y|^{d}-\left(|a_{0}|+|y|^{d-1}(\epsilon|a_{0}|-1)\right)
=|y|d+|y|d1|a0|ϵ|a0||y|d1.\displaystyle=|y|^{d}+|y|^{d-1}-|a_{0}|-\epsilon|a_{0}||y|^{d-1}.

That |y|ϵ(1ϵ)1>1|y|\epsilon(1-\epsilon)^{-1}>1 implies

|y|d1+ϵ|y|d1|y|dϵ1ϵ|y|d1+ϵ|y|d1=|y|1ϵϵ(2ϵ).\frac{|y|^{d}}{1+\epsilon|y|^{d-1}}\geq\frac{|y|^{d}}{\frac{\epsilon}{1-\epsilon}|y|^{d-1}+\epsilon|y|^{d-1}}=|y|\frac{1-\epsilon}{\epsilon(2-\epsilon)}.

Now choose ϵ\epsilon to be the smallest real root of (1T)2T(2T)=0(1-T)^{2}-T(2-T)=0; i.e., ϵ=11/2\epsilon=1-1/\sqrt{2}. Then ϵ(0,1/2)\epsilon\in(0,1/2) and (1ϵ)(ϵ(2ϵ))1=(1ϵ)1(1-\epsilon)(\epsilon(2-\epsilon))^{-1}=(1-\epsilon)^{-1} so that

|y|d1+ϵ|y|d1|y|1ϵϵ(2ϵ)=|y|1ϵ>|a0|,\frac{|y|^{d}}{1+\epsilon|y|^{d-1}}\geq|y|\frac{1-\epsilon}{\epsilon(2-\epsilon)}=\frac{|y|}{1-\epsilon}>|a_{0}|,

where the final inequality is by assumption on |y||y|. Therefore

|f(y)||y|d+|y|d1|a0|ϵ|a0||y|d1>|y|d1.|f(y)|\geq|y|^{d}+|y|^{d-1}-|a_{0}|-\epsilon|a_{0}||y|^{d-1}>|y|^{d-1}.

Iterating this inequality shows that |fn(y)||f^{n}(y)|\to\infty as nn\to\infty. But this contradicts yy being in the filled Julia set. So |y|(1ϵ)|a0||y|\leq(1-\epsilon)|a_{0}| in this case, hence |a0y||a0|(1ϵ)|a0|=ϵ|a0||a_{0}-y|\geq|a_{0}|-(1-\epsilon)|a_{0}|=\epsilon|a_{0}|. Consequently

Efy1+ϵ|a0|+j=1d1|aj|ϵEfϵ1+ϵEf.E_{f_{y}}\geq 1+\epsilon|a_{0}|+\sum_{j=1}^{d-1}|a_{j}|\geq\epsilon E_{f}\geq\frac{\epsilon}{1+\epsilon}E_{f}.

Thus, regardless of the size of the constant term, we have Efyϵ1+ϵEfE_{f_{y}}\geq\frac{\epsilon}{1+\epsilon}E_{f}.

5. Comparison with the Arakelov Height: Rational Maps

We turn to our main theorem (Theorem 1.3).

5.1. An Adjoint Formula

We define the pull-back and push-forward of an adelic measure
μ=(μv)vMK𝒜K\mu=(\mu_{v})_{v\in M_{K}}\in\mathcal{A}_{K} coordinate-wise: fμ=(fμv)vMKf^{*}\mu=(f^{*}\mu_{v})_{v\in M_{K}} and fμ=(fμv)vMKf_{*}\mu=(f_{*}\mu_{v})_{v\in M_{K}}. It is useful to know how the pull-back and push-forward interact with our inner product. For measures of total mass zero, the push-forward and pull-back are adjoints of each other.

Proposition 5.1.

Suppose that μ\mu and ν\nu are in 𝒜K0\mathcal{A}_{K}^{0}. If ff is a non-constant rational map defined over KK then fμ,ν=μ,fν\langle f^{*}\mu,\nu\rangle=\langle\mu,f_{*}\nu\rangle. In particular, fμ2=dμ2\|f^{*}\mu\|^{2}=d\|\mu\|^{2}.

The proof is entirely local, and indeed the adjoint relationship holds for local forms as well. The key is the following relationship between the Laplacian and the action of a rational map: if φBDVv(𝐏v1)\varphi\in\mathrm{BDV}_{v}(\mathbf{P}_{v}^{1}) then

(5.1) fΔ(φ)=Δ(φf).f^{*}\Delta(\varphi)=\Delta(\varphi\circ f).

See Proposition 9.56 of [BR10] for a proof, or the remarks in Section 6.1 of [FR06].

Proof of Proposition 5.1.

The proof is essentially a reformulation of (5.1). Since Uμ,vU_{\mu,v} is in BDVv\mathrm{BDV}_{v} for all vv, and since ΔUμ,v=μv\Delta U_{\mu,v}=\mu_{v}, ΔUν,v=νv\Delta U_{\nu,v}=\nu_{v} as μv\mu_{v} and νv\nu_{v} have total mass 0, then

fμv,νvv=Uν,v𝑑fμv=Uν,v𝑑Δ(Uμ,vf)=Uμ,vf𝑑νv=μv,fνvv.\langle f^{*}\mu_{v},\nu_{v}\rangle_{v}=\int U_{\nu,v}\;df^{*}\mu_{v}=\int U_{\nu,v}d\Delta(U_{\mu,v}\circ f)=\int U_{\mu,v}\circ f\;d\nu_{v}=\langle\mu_{v},f_{*}\nu_{v}\rangle_{v}.

The second statement follows from the first: fμv,fμvv=μv,ffμvv=dμv,μvv\langle f^{*}\mu_{v},f^{*}\mu_{v}\rangle_{v}=\langle\mu_{v},f_{*}f^{*}\mu_{v}\rangle_{v}=d\langle\mu_{v},\mu_{v}\rangle_{v}. Multiplying by rvr_{v} and summing over all places gives the proposition. ∎

5.2. Comparison with the pull-back of the Arakelov Measure.

The Arakelov height of a given rational map ff in some sense measures the arithmetic complexity of ff. It is therefore natural to wonder if the norm μf2\|\mu_{f}\|^{2} of ff, which is a measure of arithmetic-dynamical size, can be related to Arakelov height of ff. It turns out that μf2\|\mu_{f}\|^{2} can be bounded in terms of the Arakelov height of ff.

Theorem 5.2.

Let ff be a rational map of degree d2d\geq 2, defined over a number field KK. There are positive constants c1,c2,c3,c4c_{1},c_{2},c_{3},c_{4} depending only on the degree of ff so that

c1hAr(f)c2d2μf2c3hAr(f)+c4.c_{1}h_{Ar}(f)-c_{2}\leq\frac{d}{2}\|\mu_{f}\|^{2}\leq c_{3}h_{Ar}(f)+c_{4}.

Moreover c1,c31c_{1},c_{3}\to 1 as dd\to\infty and c2,c4c_{2},c_{4} grow linearly in dd.

As hAr=h+O(1)h_{\mathrm{Ar}}=h+O(1) for any Weil height hh on Ratd(K)\mathrm{Rat}_{d}(K), with the implied constants depending on dd and hh, Theorem 5.2 and Proposition 3.2 imply Theorem 1.3 from the introduction. When examining the norm associated to monic polynomials, we could deduce information on μf,v\mu_{f,v} via the filled Julia sets 𝒦I,v{\mathcal{K}}_{I,v} at each place. In the case of rational maps, such tools are not available and we are forced to take a more circuitous route in proving Theorem 5.2. Rather than working with the norm of μf\mu_{f} directly, we instead study the pull-back of the Arakelov adelic measure λAr\lambda_{Ar} by ff. As the following simple lemma shows, the norms of these two adelic measures are never too far apart.

Lemma 5.3.

Let μf=(μf,v)vMK\mu_{f}=(\mu_{f,v})_{v\in M_{K}} be the canonical adelic measure of a rational map ff defined over KK with degree d2d\geq 2. Then

(5.2) d(d+1)2d1fλAr2μf2d(d1)2d1fλAr2.\frac{d}{(\sqrt{d}+1)^{2}}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|^{2}\leq\|\mu_{f}\|^{2}\leq\frac{d}{(\sqrt{d}-1)^{2}}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|^{2}.
Proof.

From Proposition 5.1 and the fact that d1fμf=μfd^{-1}f^{*}\mu_{f}=\mu_{f}, we have

d1fλArμf2=d1f(λArμf)2=d1λArμf2.\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}-\mu_{f}\|^{2}=\|d^{-1}f^{*}(\lambda_{\mathrm{Ar}}-\mu_{f})\|^{2}=d^{-1}\|\lambda_{\mathrm{Ar}}-\mu_{f}\|^{2}.

Now λArμf2=μf21/2\|\lambda_{\mathrm{Ar}}-\mu_{f}\|^{2}=\|\mu_{f}\|^{2}-1/2, by Proposition 3.2. (Recall that ,=,λAr,1/2\langle\cdot,\cdot\rangle=\langle\cdot,\cdot\rangle_{\lambda_{\mathrm{Ar}},1/2}.) So the triangle inequality gives

|d1fλArμf|d1fλArμfd1/2μf212d1/2μf.\bigg{|}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|-\|\mu_{f}\|\bigg{|}\leq\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}-\mu_{f}\|\leq d^{-1/2}\sqrt{\|\mu_{f}\|^{2}-\frac{1}{2}}\leq d^{-1/2}\|\mu_{f}\|.

Simple manipulation of this inequality shows that

dd+1d1fλArμfdd1d1fλAr.\frac{\sqrt{d}}{\sqrt{d}+1}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|\leq\|\mu_{f}\|\leq\frac{\sqrt{d}}{\sqrt{d}-1}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|.

Squaring these inequalities gives (5.2).

So, to prove Theorem 5.2, it suffices to bound fλAr2\|f^{*}\lambda_{\mathrm{Ar}}\|^{2} in terms of the Arakelov height of ff.

5.3. Bounds on the pull-back of the Arakelov Measure

We are going to prove a fact which may be of interest in its own right: for fRatd(K)f\in\mathrm{Rat}_{d}(K), (d/2)d1fλAr2=hAr(f)+O(1)(d/2)\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|^{2}=h_{\mathrm{Ar}}(f)+O(1), with implied constants depending only on dd. The strategy is to compare fλAr,vv2\|f^{*}\lambda_{\mathrm{Ar},v}\|^{2}_{v} with |f|v|f|_{v} at each place of KK. At finite places, we obtain an exact formula (Lemma 5.6), and at Archimedean places we obtain an integral representation which is easily bounded in terms of the Archimedean contribution to hAr(f)h_{\mathrm{Ar}}(f) (Propositions 5.8 and 5.9). We begin by fixing some notation. Write

f(z)=P(z)Q(z)=adzd++a0bdzd++b0,f(z)=\frac{P(z)}{Q(z)}=\frac{a_{d}z^{d}+\cdots+a_{0}}{b_{d}z^{d}+\cdots+b_{0}},

where at least one of ada_{d} or bdb_{d} is non-zero and where PP and QQ have no common zero. Set p=degPp=\deg P and q=degQq=\deg Q, and d=degf=max(p,q)d=\deg f=\max(p,q). So apa_{p} is the leading coefficient of P(x)P(x) and bqb_{q} is the leading coefficient of Q(x)Q(x). For non-Archimedean places vv we write ||v|\cdot|_{v} for the continuous extension of the vv-adic absolute value on v{\mathbb{C}}_{v} to 𝐀v1\mathbf{A}_{v}^{1}. Explicitly, |x|v=δv(x,0)|x|_{v}=\delta_{v}(x,0), where δv\delta_{v} is the Hsia kernel from Section 2. Equivalently, |x|v=[T]x|x|_{v}=[T]_{x}, where []x𝐀v1[\cdot]_{x}\in\mathbf{A}_{v}^{1} is viewed as a seminorm on v[T]{\mathbb{C}}_{v}[T] (see chapters 1 and 2 of [BR10] for the semi-norm definition of Berkovich spaces). The following consequence of Jensen’s formula and its non-Archimedean analogue will be central to what follows.

Proposition 5.4.

Let vMKv\in M_{K} and let x,yvx,y\in{\mathbb{C}}_{v}. Then

log|xzy|vdλAr,v(z)={logmax(|x|v,|y|v)ifv;log|x|v2+|y|v2ifv.\int\log|x-zy|_{v}\;d\lambda_{\mathrm{Ar},v}(z)=\begin{cases}\log\max(|x|_{v},|y|_{v})&\operatorname{\;\;\text{if}\;\;}v\nmid\infty;\\ \log\sqrt{|x|^{2}_{v}+|y|^{2}_{v}}&\operatorname{\;\;\text{if}\;\;}v\mid\infty.\end{cases}
Proof.

The proposition is trivial if y=0y=0, so assume yy is non-zero. Suppose vv is non-Archimedean. Then log[T(x/y)]ζGauss=logsup|z|v1|z(x/y)|v=log+|x/y|v\log[T-(x/y)]_{\zeta_{\mathrm{Gauss}}}=\log\sup_{|z|_{v}\leq 1}|z-(x/y)|_{v}=\log^{+}|x/y|_{v}, and so

log|xzy|vdλAr,v(z)=log|y|v+log|(x/y)z|vdλAr,v(z)=logmax(|x|v,|y|v).\int\log|x-zy|_{v}\;d\lambda_{\mathrm{Ar},v}(z)=\log|y|_{v}+\int\log|(x/y)-z|_{v}\;d\lambda_{\mathrm{Ar},v}(z)=\log\max(|x|_{v},|y|_{v}).

Suppose that vv is Archimedean and that y=1y=1. We write λAr,v\lambda_{\mathrm{Ar},v} in polar coordinates, suppress the dependence on vv, and apply Jensen’s formula:

log|xz|dλAr(z)\displaystyle\int\log|x-z|\;d\lambda_{\mathrm{Ar}}(z) =0(02πlog|xreit|dt2π)2rdr(1+r2)2\displaystyle=\int_{0}^{\infty}\left(\int_{0}^{2\pi}\log|x-re^{it}|\frac{dt}{2\pi}\right)\frac{2r\ dr}{(1+r^{2})^{2}}
=0logmax(r,|x|)2dr(1+r2)2(by Jensen’s formula)\displaystyle=\int_{0}^{\infty}\log\max(r,|x|)\;\frac{2\,dr}{(1+r^{2})^{2}}\;\;\;\;\;\;(\text{by Jensen's formula})
=log|x|0|x|2rdr(1+r2)2+|x|logr2rdr(1+r2)2\displaystyle=\log|x|\int_{0}^{|x|}\frac{2rdr}{(1+r^{2})^{2}}+\int_{|x|}^{\infty}\log r\frac{2rdr}{(1+r^{2})^{2}}
=|x|21+|x|2log(|x|)+12log(1+|x|2)+log|x|1+|x|2\displaystyle=\frac{|x|^{2}}{1+|x|^{2}}\log(|x|)+\frac{1}{2}\log(1+|x|^{-2})+\frac{\log|x|}{1+|x|^{2}}
=log1+|x|2.\displaystyle=\log\sqrt{1+|x|^{2}}.

Applying the above computation to log|xyz|=log|y|+log|(x/y)z|\log|x-yz|=\log|y|+\log|(x/y)-z| finishes the proof. ∎

We define a function Iv:vI_{v}:{\mathbb{C}}_{v}\to{\mathbb{R}} by

Iv(w)=log|P(z)wQ(z)|vdλAr,v(z).I_{v}(w)=\int\log|P(z)-wQ(z)|_{v}\;d\lambda_{\mathrm{Ar},v}(z).

For non-Archimedean places vv, Iv(w)=log|(PwQ)(ζGauss)|v=logsup|z|v1|P(z)wQ(z)|vI_{v}(w)=\log|(P-wQ)(\zeta_{\mathrm{Gauss}})|_{v}=\log\sup_{|z|_{v}\leq 1}|P(z)-wQ(z)|_{v}. Of course, IvI_{v} depends on how PP and QQ are normalized; as we will summing over all places in the end, this will be irrelevant due to product formula. That λAr,v\lambda_{\mathrm{Ar},v} is log-continuous implies IvI_{v} exists for any wvw\in{\mathbb{C}}_{v}. With the preliminaries dealt with, we turn to the following key lemma, which relates the pull-back by ff with our potential kernel log||x,y||v1\log||x,y||_{v}^{-1}. We phrase this lemma so that it holds at all places.

Lemma 5.5.

Write f(z)=P(z)Q(z)f(z)=\frac{P(z)}{Q(z)} as above. Fix elements xx and yy of v{\mathbb{C}}_{v} with xyx\neq y, and with x,yx,y not equal to f()f(\infty). For 1i,jd1\leq i,j\leq d, let αi\alpha_{i} and βj\beta_{j} be respectively the roots of f(z)=xf(z)=x and f(z)=yf(z)=y as polynomials in zz, counting multiplicities. Then

i,j=1dlog1||αi,βj||v=log|apdqbqdpRes(P,Q)|vdlog|xy|v+dIv(x)+dIv(y),\sum_{i,j=1}^{d}\log\frac{1}{||\alpha_{i},\beta_{j}||_{v}}=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}-d\log|x-y|_{v}+dI_{v}(x)+dI_{v}(y),
Proof.

The proof is a straightforward, albeit rather tedious, computation. Note |Res(P,Q)|v0|\mathrm{Res}(P,Q)|_{v}\neq 0 as PP and QQ have no common zero. That xyx\neq y implies both ||αi,βj||v||\alpha_{i},\beta_{j}||_{v} and |xy|v|x-y|_{v} are not zero. Moreover, the polynomials P(z)xQ(z)P(z)-xQ(z) and P(z)yQ(z)P(z)-yQ(z) both have degree dd; for if not, then either xx or yy would equal f()f(\infty). Factor P(z)xQ(z)P(z)-xQ(z) and P(z)yQ(z)P(z)-yQ(z) over v{\mathbb{C}}_{v} as

P(z)xQ(z)=xi=1d(zαi)andP(z)yQ(z)=yj=1d(zβj)P(z)-xQ(z)=\ell_{x}\prod_{i=1}^{d}(z-\alpha_{i})\operatorname{\;\;\text{and}\;\;}P(z)-yQ(z)=\ell_{y}\prod_{j=1}^{d}(z-\beta_{j})

where x=adxbd\ell_{x}=a_{d}-xb_{d} and y=adybd\ell_{y}=a_{d}-yb_{d}. By definition of βj\beta_{j},

i,j=1d|αiβj|v=i=1d|y|v1|P(αi)yQ(αi)|v,\prod_{i,j=1}^{d}|\alpha_{i}-\beta_{j}|_{v}=\prod_{i=1}^{d}|\ell_{y}|^{-1}_{v}|P(\alpha_{i})-yQ(\alpha_{i})|_{v},

and, as P(αi)=xQ(αi)P(\alpha_{i})=xQ(\alpha_{i}),

i,j=1d|αiβj|v=|y|vd|xy|vdi=1d|Q(αi)|v.\prod_{i,j=1}^{d}|\alpha_{i}-\beta_{j}|_{v}=|\ell_{y}|^{-d}_{v}|x-y|_{v}^{d}\prod_{i=1}^{d}|Q(\alpha_{i})|_{v}.

Factor Q(z)Q(z) over v{\mathbb{C}}_{v} as Q(z)=bqk=1q(zrk)Q(z)=b_{q}\prod_{k=1}^{q}(z-r_{k}). Then

i=1d|Q(αi)|v\displaystyle\prod_{i=1}^{d}|Q(\alpha_{i})|_{v} =i=1d|bq|vk=1q|αirk|v\displaystyle=\prod_{i=1}^{d}|b_{q}|_{v}\prod_{k=1}^{q}|\alpha_{i}-r_{k}|_{v}
=|bq|vdk=1qi=1d|αirk|v\displaystyle=|b_{q}|_{v}^{d}\prod_{k=1}^{q}\prod_{i=1}^{d}|\alpha_{i}-r_{k}|_{v}
=|bq|vdk=1q|x|v1|P(rk)xQ(rk)|v\displaystyle=|b_{q}|_{v}^{d}\prod_{k=1}^{q}|\ell_{x}|_{v}^{-1}|P(r_{k})-xQ(r_{k})|_{v}
=|bq|vd|x|vqk=1q|P(rk)|v\displaystyle=|b_{q}|_{v}^{d}|\ell_{x}|_{v}^{-q}\prod_{k=1}^{q}|P(r_{k})|_{v}
=|x|vq|bq|vdp|Res(P,Q)|v.\displaystyle=|\ell_{x}|_{v}^{-q}|b_{q}|_{v}^{d-p}|\mathrm{Res}(P,Q)|_{v}.

Thus

(5.3) i,j=1d|αiβj|v=|y|vd|x|vq|bq|vdp|xy|vd|Res(P,Q)|v.\prod_{i,j=1}^{d}|\alpha_{i}-\beta_{j}|_{v}=|\ell_{y}|_{v}^{-d}|\ell_{x}|_{v}^{-q}|b_{q}|_{v}^{d-p}|x-y|_{v}^{d}|\mathrm{Res}(P,Q)|_{v}.

Now assume that vv\nmid\infty. By Proposition 5.4

log|(PxQ)(ζGauss)|v=log{|x|vi=1d|zαi|v}𝑑λAr,v=log|x|v+i=1dlog+|αi|v\log|(P-xQ)(\zeta_{\mathrm{Gauss}})|_{v}=\int\log\left\{|\ell_{x}|_{v}\prod_{i=1}^{d}|z-\alpha_{i}|_{v}\right\}d\lambda_{\mathrm{Ar},v}=\log|\ell_{x}|_{v}+\sum_{i=1}^{d}\log^{+}|\alpha_{i}|_{v}

Similarly, log|(PyQ)(ζGauss)|v=log(|y|j=1dmax(1,|βj|v))\log|(P-yQ)(\zeta_{\mathrm{Gauss}})|_{v}=\log\left(|\ell_{y}|\prod_{j=1}^{d}\max(1,|\beta_{j}|_{v})\right). As αi\alpha_{i} and βj\beta_{j} are in v{\mathbb{C}}_{v}, then combining (5.3) with the expression for ||αi,βj||v||\alpha_{i},\beta_{j}||_{v} in affine coordinates yields

i,j=1dlog1||αi,βj||v\displaystyle\sum_{i,j=1}^{d}\log\frac{1}{||\alpha_{i},\beta_{j}||_{v}} =i,j=1dlog|αiβj|vmax(1,|αi|v)max(1,|βj|v)\displaystyle=-\sum_{i,j=1}^{d}\log\frac{|\alpha_{i}-\beta_{j}|_{v}}{\max(1,|\alpha_{i}|_{v})\max(1,|\beta_{j}|_{v})}
=logi,j=1d|αiβj|v+dlogi=1dmax(1,|αi|v)+dlogj=1dmax(1,|βj|v)\displaystyle=-\log\prod_{i,j=1}^{d}|\alpha_{i}-\beta_{j}|_{v}+d\log\prod_{i=1}^{d}\max(1,|\alpha_{i}|_{v})+d\log\prod_{j=1}^{d}\max(1,|\beta_{j}|_{v})
=log(|y|vd|x|vq|bq|vdp|xy|vd|Res(P,Q)|v)+\displaystyle=-\log\left(|\ell_{y}|_{v}^{-d}|\ell_{x}|_{v}^{-q}|b_{q}|_{v}^{d-p}|x-y|^{d}_{v}|\mathrm{Res}(P,Q)|_{v}\right)+
+(dIv(x)dlog|x|v)+(dIv(y)dlog|y|v)\displaystyle\;\;\;+(dI_{v}(x)-d\log|\ell_{x}|_{v})+(dI_{v}(y)-d\log|\ell_{y}|_{v})
=logCv(x,y)dlog|xy|+dIv(x)+dIv(y)\displaystyle=-\log C_{v}(x,y)-d\log|x-y|+dI_{v}(x)+dI_{v}(y)

where Cv(x,y)=|x|vdq|bq|vdp|Res(P,Q)|vC_{v}(x,y)=|\ell_{x}|_{v}^{d-q}|b_{q}|_{v}^{d-p}|\mathrm{Res}(P,Q)|_{v}. Now if d=qd=q then |x|dq=1=|ap|dq|\ell_{x}|^{d-q}=1=|a_{p}|^{d-q}. If d>qd>q then d=pd=p and bd=0b_{d}=0 so that x=adbdx=ad\ell_{x}=a_{d}-b_{d}x=a_{d}. Thus Cv(x,y)=|ap|vdq|bq|vdq|Res(P,Q)|vC_{v}(x,y)=|a_{p}|_{v}^{d-q}|b_{q}|_{v}^{d-q}|\mathrm{Res}(P,Q)|_{v}, which proves the lemma for non-Archimedean vv. The argument for Archimedean places vv is similar. From Proposition 5.4

logi=1d1+|αi|v2\displaystyle\log\prod_{i=1}^{d}\sqrt{1+|\alpha_{i}|_{v}^{2}} =logi=1d|αiw|vdλAr,v(w)\displaystyle=\int\log\prod_{i=1}^{d}|\alpha_{i}-w|_{v}\;d\lambda_{\mathrm{Ar},v}(w)
=log|x|v1|P(w)xQ(w)|vdλAr,v(w)\displaystyle=\int\log|\ell_{x}|_{v}^{-1}|P(w)-xQ(w)|_{v}\;d\lambda_{\mathrm{Ar},v}(w)
=log|x|v+Iv(x);\displaystyle=-\log|\ell_{x}|_{v}+I_{v}(x);

likewise logj=1d1+|βj|v2=log|y|v+Iv(y)\log\prod_{j=1}^{d}\sqrt{1+|\beta_{j}|_{v}^{2}}=-\log|\ell_{y}|_{v}+I_{v}(y). Combining this with Equation 5.3 shows that

i,j=1dlog1||αi,βj||v\displaystyle\sum_{i,j=1}^{d}\log\frac{1}{||\alpha_{i},\beta_{j}||_{v}} =logi,j=1d|αiβj|v1+|αi|v21+|βj|v2\displaystyle=-\log\prod_{i,j=1}^{d}\frac{|\alpha_{i}-\beta_{j}|_{v}}{\sqrt{1+|\alpha_{i}|_{v}^{2}}\sqrt{1+|\beta_{j}|_{v}^{2}}}
=logi,j=1d|αiβj|v+dlogi=1d1+|αi|v2+dlogj=1d1+|βj|v2\displaystyle=-\log\prod_{i,j=1}^{d}|\alpha_{i}-\beta_{j}|_{v}+d\log\prod_{i=1}^{d}\sqrt{1+|\alpha_{i}|_{v}^{2}}+d\log\prod_{j=1}^{d}\sqrt{1+|\beta_{j}|_{v}^{2}}
=log(|y|vd|x|vq|bq|vdp|xy|vd|Res(P,Q)|v)+\displaystyle=-\log\left(|\ell_{y}|_{v}^{-d}|\ell_{x}|_{v}^{-q}|b_{q}|_{v}^{d-p}|x-y|^{d}_{v}|\mathrm{Res}(P,Q)|_{v}\right)+
+(dIv(x)dlog|x|v)+(dIv(y)dlog|y|v)\displaystyle\;\;\;+(dI_{v}(x)-d\log|\ell_{x}|_{v})+(dI_{v}(y)-d\log|\ell_{y}|_{v})
=log(|ap|vdq|bq|vdp|Res(P,Q)|v)dlog|xy|v+dIv(x)+dIv(y),\displaystyle=-\log(|a_{p}|_{v}^{d-q}|b_{q}|_{v}^{d-p}|\mathrm{Res}(P,Q)|_{v})-d\log|x-y|_{v}+dI_{v}(x)+dI_{v}(y),

where, as in the non-Archimedean case, the terms involving y\ell_{y} cancel and |x|vdq=|ap|vdp|\ell_{x}|_{v}^{d-q}=|a_{p}|_{v}^{d-p}. ∎

5.4. Non-Archimedean Considerations

At finite places vv, we have an explicit relationship between log|f|v=logmax0i,jd(|ai|v,|bj|v)\log|f|_{v}=\log\max_{0\leq i,j\leq d}(|a_{i}|_{v},|b_{j}|_{v}) and fλAr,vv2\|f^{*}\lambda_{\mathrm{Ar},v}\|^{2}_{v}.

Lemma 5.6.

For all vMK0v\in M_{K}^{0}, fδζGaussv2=log|apdqbqdpRes(P,Q)|v+2dlog|f|v\|f^{*}\delta_{\zeta_{\mathrm{Gauss}}}\|_{v}^{2}=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}+2d\log|f|_{v}.

Conceptually, the strategy for proving Lemma 5.6 is straightforward: we are going to take the limit as (x,y)(ζGauss,ζGauss)(x,y)\to(\zeta_{\mathrm{Gauss}},\zeta_{\mathrm{Gauss}}) of the expression in Lemma 5.5. However, because log||x,y||v1\log||x,y||_{v}^{-1} is not continuous on 𝐏v1×𝐏v1\mathbf{P}_{v}^{1}\times\mathbf{P}_{v}^{1}, some care is needed in how we carry out this limiting process. We start with a simple proposition. We recall that the Berkovich projective line over the vv-adic complex numbers is metrizable (Corollary 1.20 of [BR10]). Thus we may work with sequences rather than nets.

Proposition 5.7.

Suppose that xnvx_{n}\in{\mathbb{C}}_{v} with xnζGaussx_{n}\to\zeta_{\mathrm{Gauss}}. Then Iv(xn)log|f|vI_{v}(x_{n})\to\log|f|_{v}.

Proof.

It follows from Proposition 5.4 that limxnζGauss|aixnbi|v=max(|ai|v,|bi|v)\lim_{x_{n}\to\zeta_{\mathrm{Gauss}}}|a_{i}-x_{n}b_{i}|_{v}=\max(|a_{i}|_{v},|b_{i}|_{v}). Therefore

limxnζGaussIv(xn)\displaystyle\lim_{x_{n}\to\zeta_{\mathrm{Gauss}}}I_{v}(x_{n}) =limxnζGausslog|(PxnQ)(ζGauss)|v\displaystyle=\lim_{x_{n}\to\zeta_{\mathrm{Gauss}}}\log|(P-x_{n}Q)(\zeta_{\mathrm{Gauss}})|_{v}
=limxnζGausslogmax0id|aixnbi|v\displaystyle=\lim_{x_{n}\to\zeta_{\mathrm{Gauss}}}\log\max_{0\leq i\leq d}|a_{i}-x_{n}b_{i}|_{v}
=logmax0idlimxnζGauss|aixnbi|v\displaystyle=\log\max_{0\leq i\leq d}\lim_{x_{n}\to\zeta_{\mathrm{Gauss}}}|a_{i}-x_{n}b_{i}|_{v}
=logmax0idmax(|ai|v,|bi|v)\displaystyle=\log\max_{0\leq i\leq d}\max(|a_{i}|_{v},|b_{i}|_{v})
=log|f|v.\displaystyle=\log|f|_{v}.

Proof of Lemma 5.6.

Fix yvy\in{\mathbb{C}}_{v} and let β1,,βd\beta_{1},...,\beta_{d} be the roots of f(z)=yf(z)=y, including multiplicities. Define a function ψy:𝐏v1{}\psi_{y}:\mathbf{P}_{v}^{1}\to{\mathbb{R}}\cup\{\infty\} by ψy(z)=j=1dlog||z,βj||v1\psi_{y}(z)=\sum_{j=1}^{d}\log||z,\beta_{j}||_{v}^{-1}. We remark that ψy\psi_{y} is continuous everywhere except at the finitely many points βj\beta_{j}. Let {xn}n=1\{x_{n}\}_{n=1}^{\infty} be a sequence in v{\mathbb{C}}_{v} with xnζGaussx_{n}\to\zeta_{\mathrm{Gauss}}. By replacing {xn}n=1\{x_{n}\}_{n=1}^{\infty} with a subsequence if necessary, we assume that the conditions of Lemma 5.5 are satisfied. In particular, xnyx_{n}\neq y and ζGaussy\zeta_{\mathrm{Gauss}}\neq y for all nn. Let VV be a sufficiently small open set containing yy so that ζGaussV\zeta_{\mathrm{Gauss}}\notin V and xnVx_{n}\notin V for all nn. As βjf1(V)\beta_{j}\in f^{-1}(V) for 1jd1\leq j\leq d, then ψy\psi_{y} is continuous on f1(𝐏v1V)f^{-1}(\mathbf{P}_{v}^{1}\setminus V). Therefore the push-forward of ψy\psi_{y} by ff, (fψy)(f_{*}\psi_{y}), is continuous on 𝐏v1V\mathbf{P}_{v}^{1}\setminus V. Since xnζGaussx_{n}\to\zeta_{\mathrm{Gauss}} and xn,ζGauss𝐏v1Vx_{n},\zeta_{\mathrm{Gauss}}\in\mathbf{P}_{v}^{1}\setminus V, then (fψy)(xn)(fψy)(ζGauss)(f_{*}\psi_{y})(x_{n})\to(f_{*}\psi_{y})(\zeta_{\mathrm{Gauss}}). For 1id1\leq i\leq d let αi,n\alpha_{i,n} be the roots of f(z)=xnf(z)=x_{n}, counting multiplicities. By Lemma 5.5 then

(fψy)(xn)=1i,jdlog1||αi,n,βj||v=log|apdqbqdpRes(P,Q)|vdlog|xny|v+dIv(xn)+dIv(y),(f_{*}\psi_{y})(x_{n})=\sum_{1\leq i,j\leq d}\log\frac{1}{||\alpha_{i,n},\beta_{j}||_{v}}=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}-d\log|x_{n}-y|_{v}+dI_{v}(x_{n})+dI_{v}(y),

so that

(fψy)(ζGauss)\displaystyle(f_{*}\psi_{y})(\zeta_{\mathrm{Gauss}}) =limxnζGauss{log|apdqbqdpRes(P,Q)|vdlog|xny|v+dIv(xn)+dIv(y)}\displaystyle=\lim_{x_{n}\to\zeta_{\mathrm{Gauss}}}\left\{-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}-d\log|x_{n}-y|_{v}+dI_{v}(x_{n})+dI_{v}(y)\right\}
=log|apdqbqdpRes(p,q)|v+dlog|f|v+dlog+|y|v+dIv(y),\displaystyle=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(p,q)|_{v}+d\log|f|_{v}+d\log^{+}|y|_{v}+dI_{v}(y),

where we have applied Proposition 5.7, and Proposition 5.4. This shows that if ϕ:𝐏v1\phi:\mathbf{P}_{v}^{1}\to{\mathbb{R}} is defined by

ϕ(y):=f(ζ)=ζGaussf(β)=ymf(ζ)mf(β)log1||ζ,β||v,\phi(y):=\sum_{\begin{subarray}{c}f(\zeta)=\zeta_{\mathrm{Gauss}}\\ f(\beta)=y\end{subarray}}m_{f}(\zeta)m_{f}(\beta)\log\frac{1}{||\zeta,\beta||_{v}},

then for all yvy\in{\mathbb{C}}_{v}

(5.4) ϕ(y)=ψy(ζGauss)=log|apdqbqdpRes(P,Q)|v+dlog|f|v+log+|y|v+dIv(y).\phi(y)=\psi_{y}(\zeta_{\mathrm{Gauss}})=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}+d\log|f|_{v}+\log^{+}|y|_{v}+dI_{v}(y).

Now f(ζ)=ζGaussf(\zeta)=\zeta_{\mathrm{Gauss}} implies that ζ\zeta is not in v{\mathbb{C}}_{v}. As the spherical kernel is continuous in each variable separately, and since ||ζ,y||v||ζ,ζ||v>0||\zeta,y||_{v}\geq||\zeta,\zeta||_{v}>0 whenever ζ\zeta is not in v{\mathbb{C}}_{v}, then ϕ\phi is continuous on 𝐏v1\mathbf{P}_{v}^{1}. Suppose that ynvy_{n}\in{\mathbb{C}}_{v} with ynζGaussy_{n}\to\zeta_{\mathrm{Gauss}}. Applying (5.4), Proposition 5.7, and the fact that limynζGausslog+|yn|v=0\lim_{y_{n}\to\zeta_{\mathrm{Gauss}}}\log^{+}|y_{n}|_{v}=0 yields

ϕ(ζGauss)=limynζGaussϕ(yn)=log|apdqbqdpRes(P,Q)|v+2dlog|f|v.\phi(\zeta_{\mathrm{Gauss}})=\lim_{y_{n}\to\zeta_{\mathrm{Gauss}}}\phi(y_{n})=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}+2d\log|f|_{v}.

On the other hand,

ϕ(ζGauss)=f(ζ)=ζGaussf(ζ)=ζGaussmf(ζ)mf(ζ)log1||ζ,ζ||v=fδζGaussv2.\phi(\zeta_{\mathrm{Gauss}})=\sum_{\begin{subarray}{c}f(\zeta)=\zeta_{\mathrm{Gauss}}\\ f(\zeta^{\prime})=\zeta_{\mathrm{Gauss}}\end{subarray}}m_{f}(\zeta)m_{f}(\zeta^{\prime})\log\frac{1}{||\zeta,\zeta^{\prime}||_{v}}=\|f^{*}\delta_{\zeta_{\mathrm{Gauss}}}\|_{v}^{2}.

5.5. Archimedean Considerations

The Archimedean case is simpler than the non-Archimedean, as we may simply integrate the expression in Lemma 5.5 with respect to λAr,v\lambda_{\mathrm{Ar},v}.

Proposition 5.8.

At Archimedean places vv, we have

fλAr,vv2=log|apdqbqdpRes(P,Q)|vd2+2dlog|P(z)|v2+|Q(z)|v2dλAr,v(z)\|f^{*}{\lambda_{\mathrm{Ar},v}}\|_{v}^{2}=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}-\frac{d}{2}+2d\int\log\sqrt{|P(z)|_{v}^{2}+|Q(z)|_{v}^{2}}\;d{\lambda_{\mathrm{Ar},v}}(z)
Proof.

With notation as in Lemma 5.5,

fλAr,v2\displaystyle\|f^{*}{\lambda_{\mathrm{Ar},v}}\|^{2} =i,j=1dlog1||αi,βj||vdλAr,v(x)dλAr,v(y)\displaystyle=\iint\sum_{i,j=1}^{d}\log\frac{1}{||\alpha_{i},\beta_{j}||_{v}}d{\lambda_{\mathrm{Ar},v}}(x)d{\lambda_{\mathrm{Ar},v}}(y)
=log|apdqbqdpRes(P,Q)|vdlog|xy|vdλAr,v(x)𝑑λAr,v(y)+2dIv(x)𝑑λAr,v(x).\displaystyle=-\log|a_{p}^{d-q}b_{q}^{d-p}\mathrm{Res}(P,Q)|_{v}-d\iint\log|x-y|_{v}d{\lambda_{\mathrm{Ar},v}}(x)d{\lambda_{\mathrm{Ar},v}}(y)+2d\int I_{v}(x)\;d{\lambda_{\mathrm{Ar},v}}(x).

(As λAr,v{\lambda_{\mathrm{Ar},v}} is log-continuous, we may safely ignore both the diagonal of 1()×1(){\mathbb{P}}^{1}({\mathbb{C}})\times{\mathbb{P}}^{1}({\mathbb{C}}) and the finite number of points where Lemma 5.5 fails to apply.) The first integral is easily computed:

log|xy|vdλAr,v(x)𝑑λAr,v(y)=log1+|y|v2dλAr,v(y)=12.\iint\log|x-y|_{v}\;d{\lambda_{\mathrm{Ar},v}}(x)d{\lambda_{\mathrm{Ar},v}}(y)=\int\log\sqrt{1+|y|_{v}^{2}}\;d{\lambda_{\mathrm{Ar},v}}(y)=\frac{1}{2}.

For the second:

Iv(x)𝑑λAr,v(x)\displaystyle\int I_{v}(x)\;d{\lambda_{\mathrm{Ar},v}}(x) =log|P(z)xQ(z)|vdλAr,v(z)𝑑λAr,v(x)\displaystyle=\iint\log|P(z)-xQ(z)|_{v}\;d{\lambda_{\mathrm{Ar},v}}(z)d{\lambda_{\mathrm{Ar},v}}(x)
=log|P(z)xQ(z)|vdλAr,v(x)𝑑λAr,v(z)\displaystyle=\iint\log|P(z)-xQ(z)|_{v}\;d{\lambda_{\mathrm{Ar},v}}(x)\;d{\lambda_{\mathrm{Ar},v}}(z)
=log|P(z)|v2+|Q(z)|v2dλAr,v(z),\displaystyle=\int\log\sqrt{|P(z)|_{v}^{2}+|Q(z)|_{v}^{2}}\;d{\lambda_{\mathrm{Ar},v}}(z),

using Fubini’s Theorem in the second line and Proposition 5.4 in the final line. ∎

As one might suspect, it is not difficult to bound the integral log|P(z)|v2+|Q(z)|v2dλAr,v(z)\int\log\sqrt{|P(z)|_{v}^{2}+|Q(z)|_{v}^{2}}\;d{\lambda_{\mathrm{Ar},v}}(z) in terms of the Archimedean contribution to the Arakelov height of ff. Recall that for Archimedean vv, we may write dλAr,v(z)=d(z)/(π(1+|z|v2)2d\lambda_{\mathrm{Ar},v}(z)=d\ell(z)/(\pi(1+|z|_{v}^{2})^{2}, where \ell is the Lebesgue measure on {\mathbb{C}}.

Proposition 5.9.

At Archimedean places vv, we have

|P(z)|v2+|Q(z)|v2𝑑λAr,v(z)=log|f|v+O(1)\int\sqrt{|P(z)|_{v}^{2}+|Q(z)|^{2}_{v}}\,d\lambda_{\mathrm{Ar},v}(z)=\log|f|_{v}+O(1)

where |f|v2=i=0d|ai|v2+|bi|v2|f|_{v}^{2}=\sum_{i=0}^{d}|a_{i}|_{v}^{2}+|b_{i}|_{v}^{2} and where the implied constants depend only on the degree dd.

Proof.

Set ψ(z)=|P(z)|v2+|Q(z)|v2\psi(z)=\sqrt{|P(z)|_{v}^{2}+|Q(z)|_{v}^{2}}. We begin with the upper bound, which is the easier of the two. Expanding |P(z)|v2=P(z)P(z)¯|P(z)|_{v}^{2}=P(z)\overline{P(z)} and |Q(z)|v2=Q(z)Q(z)¯|Q(z)|_{v}^{2}=Q(z)\overline{Q(z)} shows that

(5.5) 02πψ2(reit)dt2π=k=0d(|ak|v2+|bk|v2)r2k.\int_{0}^{2\pi}\psi^{2}(re^{it})\;\frac{dt}{2\pi}=\sum_{k=0}^{d}\left(|a_{k}|_{v}^{2}+|b_{k}|_{v}^{2}\right)r^{2k}.

Writing λAr,v\lambda_{\mathrm{Ar},v} in polar coordinates gives

logψ(z)𝑑λAr,v(z)\displaystyle\int\log\psi(z)d\lambda_{\mathrm{Ar},v}(z) =002πlogψ2(reit)dt2πrdr(1+r2)2\displaystyle=\int_{0}^{\infty}\int_{0}^{2\pi}\log\psi^{2}(re^{it})\frac{dt}{2\pi}\frac{rdr}{(1+r^{2})^{2}}
0log(02πψ2(reit)dt2π)rdr(1+r2)2\displaystyle\leq\int_{0}^{\infty}\log\left(\int_{0}^{2\pi}\psi^{2}(re^{it})\frac{dt}{2\pi}\right)\frac{rdr}{(1+r^{2})^{2}}
=0log(k=0d(|ak|v2+|bk|v2)r2k)rdr(1+r2)2\displaystyle=\int_{0}^{\infty}\log\left(\sum_{k=0}^{d}\left(|a_{k}|_{v}^{2}+|b_{k}|_{v}^{2}\right)r^{2k}\right)\frac{rdr}{(1+r^{2})^{2}}
0log(|f|v2k=0dr2k)rdr(1+r2)2\displaystyle\leq\int_{0}^{\infty}\log\left(|f|_{v}^{2}\sum_{k=0}^{d}r^{2}k\right)\frac{rdr}{(1+r^{2})^{2}}
=12log|f|v2+0log(k=0dr2k)rdr(1+r2)2\displaystyle=\frac{1}{2}\log|f|_{v}^{2}+\int_{0}^{\infty}\log\left(\sum_{k=0}^{d}r^{2k}\right)\;\frac{r\,dr}{(1+r^{2})^{2}}
=:log|f|v+Jd\displaystyle=:\log|f|_{v}+J_{d}

where we have used Jensen’s inequality in the second line, (5.5) in the third line, and the fact that 0rdr(1+r2)2=12\int_{0}^{\infty}\frac{r\,dr}{(1+r^{2})^{2}}=\frac{1}{2} in the penultimate line. Combining elementary calculus with trivial bounds on k=0dr2k\sum_{k=0}^{d}r^{2k} shows that Jd2d+14log(2)+14log(d+1)J_{d}\leq\frac{2d+1}{4}\log(2)+\frac{1}{4}\log(d+1). For the lower bound, we assume that degQ=d\deg Q=d and define a polynomial H(z)H(z) by

H(z)=P(z)+zd+1Q(z)=a0+a1z++adzd+b0zd+1++bdz2d+1.H(z)=P(z)+z^{d+1}Q(z)=a_{0}+a_{1}z+\cdots+a_{d}z^{d}+b_{0}z^{d+1}+\cdots+b_{d}z^{2d+1}.

Then, by the triangle inequality and the fact that (A+B)22A2+2B2(A+B)^{2}\leq 2A^{2}+2B^{2} for positive numbers AA and BB, we find that |H(z)|v22max(1,|z|v2d+2)ψ2(z)|H(z)|_{v}^{2}\leq 2\max(1,|z|_{v}^{2d+2})\psi^{2}(z) for all zz. Thus

(5.6) log|H(z)|vdλAr,v(z)|z|v1log(2ψ(z))𝑑λAr,v(z)+|z|v>1log(2|z|vd+1ψ(z))𝑑λAr,v(z).\int\log|H(z)|_{v}\;d\lambda_{\mathrm{Ar},v}(z)\leq\int_{|z|_{v}\leq 1}\log\left(\sqrt{2}\psi(z)\right)\;d\lambda_{\mathrm{Ar},v}(z)+\int_{|z|_{v}>1}\log\left(\sqrt{2}|z|_{v}^{d+1}\psi(z)\right)\;d\lambda_{\mathrm{Ar},v}(z).

Now write H(z)=bdi=12d+1(zγi)H(z)=b_{d}\prod_{i=1}^{2d+1}(z-\gamma_{i}). By Proposition 5.4

log|H(z)|vdλAr,v(z)=log|bd|v+i=12d+1log1+|γi|v2,\int\log|H(z)|_{v}\;d\lambda_{\mathrm{Ar},v}(z)=\log|b_{d}|_{v}+\sum_{i=1}^{2d+1}\log\sqrt{1+|\gamma_{i}|_{v}^{2}},

and the roots of HH are easy to relate to the coefficients of HH via Vieta’s formulas:

|bd|v2i=12d+1(1+|γi|v2)\displaystyle|b_{d}|_{v}^{2}\prod_{i=1}^{2d+1}(1+|\gamma_{i}|_{v}^{2}) |bd|v22(2d+1)i=12d+1(1+|γi|v)2\displaystyle\geq|b_{d}|_{v}^{2}2^{-(2d+1)}\prod_{i=1}^{2d+1}(1+|\gamma_{i}|_{v})^{2}
=2(2d+1)(|bd|v+|bd|v(|γ1|v++|γ2d+1|v)++|bd|vi=12d+1|γi|v)2\displaystyle=2^{-(2d+1)}\left(|b_{d}|_{v}+|b_{d}|_{v}(|\gamma_{1}|_{v}+\cdots+|\gamma_{2d+1}|_{v})+\cdots+|b_{d}|_{v}\prod_{i=1}^{2d+1}|\gamma_{i}|_{v}\right)^{2}
2(2d+1)(i=0d|ai|v+i=0d|bi|v)2\displaystyle\geq 2^{-(2d+1)}\left(\sum_{i=0}^{d}|a_{i}|_{v}+\sum_{i=0}^{d}|b_{i}|_{v}\right)^{2}
2(2d+1)(i=0d|ai|v2+|bi|v2),\displaystyle\geq 2^{-(2d+1)}\left(\sum_{i=0}^{d}|a_{i}|_{v}^{2}+|b_{i}|_{v}^{2}\right),

Consequently,

(5.7) log|H(z)|vdλAr,v(z)=log|bd|v+i=12d+1log1+|γi|v2(2d+1)log2+log|f|v.\int\log|H(z)|_{v}\;d\lambda_{\mathrm{Ar},v}(z)=\log|b_{d}|_{v}+\sum_{i=1}^{2d+1}\log\sqrt{1+|\gamma_{i}|_{v}^{2}}\geq-(2d+1)\log\sqrt{2}+\log|f|_{v}.

From (5.6), (5.7), and the fact |z|v>1log|z|vdλAr,v(z)=log2\int_{|z|_{v}>1}\log|z|_{v}\;d\lambda_{\mathrm{Ar},v}(z)=\log\sqrt{2}, we find

logψ(z)𝑑σ(z)3(d+1)log2+log|f|v.\int\log\psi(z)\;d\sigma(z)\geq-3(d+1)\log\sqrt{2}+\log|f|_{v}.

If instead degQ<d\deg Q<d, then degP=d\deg P=d and we set H(z)=Q(z)+zd+1P(z)H(z)=Q(z)+z^{d+1}P(z). The above argument then gives the same lower bound on logψdλAr,v\int\log\psi\;d\lambda_{\mathrm{Ar},v}.

Multiplying the estimates in Lemma 5.6 and Propositions 5.8 and 5.9 by rvr_{v}, summing over all places and applying the product formula shows that 12dfλAr2=d2d1fλAr2=hAr(f)+O(1)\frac{1}{2d}\|f^{*}\lambda_{\mathrm{Ar}}\|^{2}=\frac{d}{2}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|^{2}=h_{\mathrm{Ar}}(f)+O(1), as claimed at the beginning of Section 5.3. In fact, the estimates above show that

(5.8) 3(d+1)2log(2)14+hAr(f)d2d1fλAr2hAr(f)14+2d+14log(2)+14log(d+1)-\frac{3(d+1)}{2}\log(2)-\frac{1}{4}+h_{\mathrm{Ar}}(f)\leq\frac{d}{2}\|d^{-1}f^{*}\lambda_{\mathrm{Ar}}\|^{2}\leq h_{\mathrm{Ar}}(f)-\frac{1}{4}+\frac{2d+1}{4}\log(2)+\frac{1}{4}\log(d+1)

Combining the estimates in Lemma 5.3 and (5.8) gives explicit bounds on μf2\|\mu_{f}\|^{2}:

(5.9) d(d+1)2hAr(f)c2d2μf2d(d1)2hAr(f)+c4\frac{d}{(\sqrt{d}+1)^{2}}h_{\mathrm{Ar}}(f)-c_{2}\leq\frac{d}{2}\|\mu_{f}\|^{2}\leq\frac{d}{(\sqrt{d}-1)^{2}}h_{\mathrm{Ar}}(f)+c_{4}

where c2=d(d+1)2(3(d+1)2log(2)14)c_{2}=\frac{d}{(\sqrt{d}+1)^{2}}\cdot(-\frac{3(d+1)}{2}\log(2)-\frac{1}{4}) and where c4=d(d1)2(14+2d+14log(2)+14log(d+1))c_{4}=\frac{d}{(\sqrt{d}-1)^{2}}\cdot(-\frac{1}{4}+\frac{2d+1}{4}\log(2)+\frac{1}{4}\log(d+1)). This completes the proof of Theorem 5.2.

5.6. The Arakelov–Zhang Pairing is (essentially) a height

We apply Theorem 5.2 to prove Theorem 1.3 and Corollary 1.4 from the introduction.

Corollary 5.10.

Let λ=(λv)vMK\lambda=(\lambda_{v})_{v\in M_{K}} be an adelic probability measure and let t>0t>0. Then, for any rational map ff defined over KK of degree d2d\geq 2, there are constants cic_{i}, i=1,2,3,4i=1,2,3,4 depending on dd, λ\lambda, and tt so that

c1hAr(f)c2d2μfλ,t2c3hAr(f)+c4.c_{1}h_{\mathrm{Ar}}(f)-c_{2}\leq\frac{d}{2}\|\mu_{f}\|_{\lambda,t}^{2}\leq c_{3}h_{\mathrm{Ar}}(f)+c_{4}.

Moreover c1,c21c_{1},c_{2}\to 1 as dd\to\infty and c2,c4c_{2},c_{4} grow linearly with dd.

Proof.

Combine Theorem 5.2 with the fact that μfλ,t2=μf2+O(1)\|\mu_{f}\|^{2}_{\lambda,t}=\|\mu_{f}\|^{2}+O(1), where the implied constants depend only on λ\lambda and tt (Proposition 3.2). ∎

Corollary 5.11.

Fix a rational map gg with deg(g)2\deg(g)\geq 2, and let ff be a rational map of degree d2d\geq 2. There are positive constants c5,c6,c7,c8c_{5},c_{6},c_{7},c_{8} depending on gg and dd so that

c5hAr(f)c6d(f,g)AZc7hAr(f)+c8.c_{5}h_{\mathrm{Ar}}(f)-c_{6}\leq d\cdot(f,g)_{\mathrm{AZ}}\leq c_{7}h_{\mathrm{Ar}}(f)+c_{8}.

Moreover, c5,c7c_{5},c_{7} depend only on dd and satisfy c5,c71c_{5},c_{7}\to 1 as dd\to\infty, and c6,c8c_{6},c_{8} grow linearly in dd. If ff is a monic polynomial then d(f,g)AZ=hAr(f)+O(1)d(f,g)_{\mathrm{AZ}}=h_{\mathrm{Ar}}(f)+O(1) where the implied constants depend on gg and dd.

Proof.

By (3.6), (f,g)AZ=limt012μfμg,t2(f,g)_{\mathrm{AZ}}=\lim_{t\to 0}\frac{1}{2}\|\mu_{f}\|_{\mu_{g},t}^{2}. By Proposition 3.2 there is a κ\kappa depending only on μg\mu_{g} so that |μfμg,tμf2|κ+t\big{|}\|\mu_{f}\|_{\mu_{g},t}-\|\mu_{f}\|^{2}\big{|}\leq\kappa+t. Therefore |2(f,g)μf2|κ|2(f,g)-\|\mu_{f}\|^{2}|\leq\kappa, where κ\kappa depends only on μg\mu_{g}. Now apply Theorem 5.2 to μf2\|\mu_{f}\|^{2} when ff is a rational map, and Theorem 4.1 when ff is a monic polynomial. ∎

As any Weil height on Ratd(K)\mathrm{Rat}_{d}(K) differs from the Arakelov height by a bounded function, Corollaries 5.10 and 5.11 imply Theorem 1.3 and Corollary 1.4 from the introduction.

5.7. A lower bound for adelic measures with points of small height

In this section, we prove the statements in Remark 1 from the introduction. What follows summarizes some of the discussion in [FR06] and [Fil17]. Given an element α1(K¯)\alpha\in{\mathbb{P}}^{1}(\bar{K}) and a place vMKv\in M_{K}, we denote by [α]v[\alpha]_{v} the probability measure on 𝐏v1\mathbf{P}_{v}^{1} supported equally on the Galois conjugates of α\alpha over KK; thus

[α]v=1|Gal(K¯/K)α|xGal(K¯/K)αδx.[\alpha]_{v}=\frac{1}{|\mathrm{Gal}(\bar{K}/K)\cdot\alpha|}\sum_{x\in\mathrm{Gal}(\bar{K}/K)\cdot\alpha}\delta_{x}.

Each xGal(K¯/K)αx\in\mathrm{Gal}(\bar{K}/K)\cdot\alpha is viewed as an element of 𝐏v1\mathbf{P}_{v}^{1} via an embedding K¯v\bar{K}\hookrightarrow{\mathbb{C}}_{v}; averaging over the Galois conjugates of α\alpha ensures that the choice of embedding is irrelevant. We write [α]=([α]v)vMK[\alpha]=([\alpha]_{v})_{v\in M_{K}}. Recall that the mutual energy pairing of two adelic measures μ=(μv)vMK,ν=(νv)vMK\mu=(\mu_{v})_{v\in M_{K}},\nu=(\nu_{v})_{v\in M_{K}} is

((μ,ν)=vMKrv((μv,νv))v,where((μv,νv))v=𝐀v1×𝐀v1Diagvlogδv(x,y)1dμv(x)dνv(y).(\!(\mu,\nu)=\sum_{v\in M_{K}}r_{v}(\!(\mu_{v},\nu_{v})\!)_{v},\;\text{where}\;(\!(\mu_{v},\nu_{v})\!)_{v}=\iint_{\mathbf{A}_{v}^{1}\times\mathbf{A}_{v}^{1}\setminus\mathrm{Diag}_{v}}\log\delta_{v}(x,y)^{-1}\;d\mu_{v}(x)\;d\nu_{v}(y).

Recall that μ\mu has points of small height if there is a sequence {αn}n=1\{\alpha_{n}\}_{n=1}^{\infty} of distinct points in 1(K¯){\mathbb{P}}^{1}(\bar{K}) so that hμ(αn)0asnh_{\mu}(\alpha_{n})\to 0\;\;\text{as}\;\;n\to\infty, where hμ(α):=12((μ[α],μ[α]))h_{\mu}(\alpha):=\frac{1}{2}(\!(\mu-[\alpha],\mu-[\alpha])\!) is the Favre–Rivera-Letelier height associated to μ\mu. The Arakelov height of a point α1(K¯){}\alpha\in{\mathbb{P}}^{1}(\bar{K})\setminus\{\infty\} is defined to be

hAr(α)=1ni=1nvMKrvlog||αi,||v1h_{\mathrm{Ar}}(\alpha)=\frac{1}{n}\sum_{i=1}^{n}\sum_{v\in M_{K}}r_{v}\log||\alpha_{i},\infty||_{v}^{-1}

where α1,α2,,αn\alpha_{1},\alpha_{2},...,\alpha_{n} are the Gal(K¯/K)\mathrm{Gal}(\bar{K}/K)-conjugates of α\alpha. For α=\alpha=\infty, we set hAr()=0h_{\mathrm{Ar}}(\infty)=0. The Arakelov height and the Arakelov measure are related by

(5.10) hλAr(α)=hAr(α)14h_{\lambda_{\mathrm{Ar}}}(\alpha)=h_{\mathrm{Ar}}(\alpha)-\frac{1}{4}

for all α1(K¯)\alpha\in{\mathbb{P}}^{1}(\bar{K}). This is because

((λAr,λAr))=12,((α,λAr))=hAr(α),and(([α],[α]))=0.(\!(\lambda_{\mathrm{Ar}},\lambda_{\mathrm{Ar}})\!)=\frac{-1}{2},\;\;-(\!(\alpha,\lambda_{\mathrm{Ar}})\!)=h_{\mathrm{Ar}}(\alpha),\;\;\text{and}\;\;(\!([\alpha],[\alpha])\!)=0.

The first equality is a consequence of Proposition 5.4, the second follows from Proposition 5.4 and the definition of the Arakelov height, and the third is by the product formula. The standard adelic measure, λstd=(λstd,v)vMK\lambda_{\mathrm{std}}=(\lambda_{\mathrm{std},v})_{v\in M_{K}} is defined to be the Haar measure on the unit circle when vv is Archimedean, and λstd,v=δζGauss\lambda_{\mathrm{std},v}=\delta_{\zeta_{\mathrm{Gauss}}} when vv is non-Archimedean. A direct calculation shows that λstd\lambda_{\mathrm{std}} is invariant under the pull-back by a power map. Therefore λstd\lambda_{\mathrm{std}} is the canonical adelic measure of zzdz\mapsto z^{d} for |d|2|d|\geq 2.

Proposition 5.12.

Let μ\mu be an adelic probability measure and let {αn}n=1\{\alpha_{n}\}_{n=1}^{\infty} a sequence in 1(K¯){\mathbb{P}}^{1}(\bar{K}) with hμ(αn)0h_{\mu}(\alpha_{n})\to 0. Then hAr(αn)12μ2h_{\mathrm{Ar}}(\alpha_{n})\to\frac{1}{2}\|\mu\|^{2} as nn\to\infty. Moreover μ2log(2)\|\mu\|^{2}\geq\log(2) with equality if and only if μ=λstd\mu=\lambda_{\mathrm{std}}.

Proof.

Suppose that {αn}n=1\{\alpha_{n}\}_{n=1}^{\infty} is a sequence of distinct points in 1(K¯){\mathbb{P}}^{1}(\bar{K}) so that hμ(αn)0h_{\mu}(\alpha_{n})\to 0. Then Theorem 9 of [Fil17] implies hλAr(αn)12μλAr2=12μ214h_{\lambda_{\mathrm{Ar}}}(\alpha_{n})\to\frac{1}{2}\|\mu-\lambda_{\mathrm{Ar}}\|^{2}=\frac{1}{2}\|\mu\|^{2}-\frac{1}{4}. So (5.10) implies hAr(αn)12μ2h_{\mathrm{Ar}}(\alpha_{n})\to\frac{1}{2}\|\mu\|^{2} as nn\to\infty.
Now hAr(α)12log(2)h_{\mathrm{Ar}}(\alpha)\geq\frac{1}{2}\log(2) for all α1(K¯){0,}\alpha\in{\mathbb{P}}^{1}(\bar{K})\setminus\{0,\infty\}; see [FPP17], [Som05]. Therefore 12μ2=limnhAr(αn)12log(2)\frac{1}{2}\|\mu\|^{2}=\lim_{n\to\infty}h_{\mathrm{Ar}}(\alpha_{n})\geq\frac{1}{2}\log(2). A straightforward computation shows that λstd2=log(2)\|\lambda_{\mathrm{std}}\|^{2}=\log(2); see Proposition 6.2 for a more general statement. Lastly, if μ2=log(2)\|\mu\|^{2}=\log(2) then hAr(αn)12log(2)h_{\mathrm{Ar}}(\alpha_{n})\to\frac{1}{2}\log(2). It is known that this implies [αn]vλstd,v[\alpha_{n}]_{v}\to\lambda_{\mathrm{std},v} weakly at each place of KK; see Example 6.5 of [Gil+19]. On the other hand, Théorème 2 of [FR06] implies [αn]v[\alpha_{n}]_{v} converges weakly to μv\mu_{v} at each place. So μ=λstd\mu=\lambda_{\mathrm{std}}. ∎

6. Examples

6.1. Chebyshev Polynomials

Let TnT_{n} be the nthn^{th} Chebyshev polynomial. We adopt the convention that T2(z)=z22T_{2}(z)=z^{2}-2 so that T2T_{2} (and consequently TnT_{n}) has good reduction at all finite places. In general, the (Archimedean) canonical measure of a polynomial is the equilbrium measure of the Julia set, a result due to Brolin [Bro65]. It is well known that the complex Julia set of TnT_{n} is the interval [2,2][-2,2]. The map ϕ(z)=z+z1\phi(z)=z+z^{-1} is a conformal mapping from 1(){|z|1}{\mathbb{P}}^{1}({\mathbb{C}})\setminus\{|z|\leq 1\} onto 1()[2,2]{\mathbb{P}}^{1}({\mathbb{C}})\setminus[-2,2]. By potential theory, this implies that μTn,\mu_{T_{n},\infty} is the push forward by ϕ\phi of the Haar measure on the unit circle; see Theorem 4.4.4 of [Ran95] for an equivalent statement using Green’s functions. With this explicit description for the canonical measure of TnT_{n}, it is possible to compute the norm of μTn\mu_{T_{n}} exactly.

Proposition 6.1.

Let μTn\mu_{T_{n}} be the canonical adelic measure of TnT_{n}. Then μTn2=log3+52\|\mu_{T_{n}}\|^{2}=\log\frac{3+\sqrt{5}}{2}.

Proof.

Proposition 3.6 implies that μTn2=2vMUTn,v()\|\mu_{T_{n}}\|^{2}=2\sum_{v\in M_{\mathbb{Q}}}U_{T_{n},v}(\infty). Since TnT_{n} has good reduction at all finite places, then μTn,v=δζGauss\mu_{T_{n},v}=\delta_{\zeta_{\mathrm{Gauss}}} for vv\nmid\infty; consequently UTn,v()=0U_{T_{n},v}(\infty)=0 when vv\nmid\infty. So

μTn2=2UTn,()=log(1+|z|2)𝑑μTn,(z)=02πlog(1+|eit+eit|2)dt2π.\|\mu_{T_{n}}\|^{2}=2U_{T_{n},\infty}(\infty)=\int\log(1+|z|^{2})\;d\mu_{T_{n},\infty}(z)=\int_{0}^{2\pi}\log\left(1+|e^{it}+e^{-it}|^{2}\right)\;\dfrac{dt}{2\pi}.

Now 1+|eit+eit|2=|reit+r1eit|21+|e^{it}+e^{-it}|^{2}=|re^{it}+r^{-1}e^{-it}|^{2}, where r2=3+52r^{2}=\frac{3+\sqrt{5}}{2}. Therefore

μTn2=02πlog|reit|2|e2it+r2|2dt2π=logr2+02πlog|e2it+r2|2dt2π.\|\mu_{T_{n}}\|^{2}=\int_{0}^{2\pi}\log|re^{-it}|^{2}|e^{2it}+r^{-2}|^{2}\;\dfrac{dt}{2\pi}=\log r^{2}+\int_{0}^{2\pi}\log|e^{2it}+r^{-2}|^{2}\;\dfrac{dt}{2\pi}.

By Jensen’s formula, this final integral vanishes. So μTn2=logr2\|\mu_{T_{n}}\|^{2}=\log r^{2}.

6.2. The Squaring Map After an Affine Change of Variables

In this section we compute the norm of the canonical measure associated to the map Pdϕ=ϕ1PdϕP_{d}^{\phi}=\phi^{-1}\circ P_{d}\circ\phi, where Pd:zzdP_{d}:z\mapsto z^{d} is the dthd^{th} power map (|d|2|d|\ \geq 2) and where ϕ:zaz+b\phi:z\mapsto az+b is an affine change of variables defined over KK. In general, the canonical measure of a rational map ff of degree dd after conjugation by ϕPGL2(K)\phi\in\mathrm{PGL}_{2}(K) can be found via the formula

(6.1) ϕμf,v=μfϕ,v.\phi^{*}\mu_{f,v}=\mu_{f^{\phi},v}.

To see this, note that (fϕ)=ϕf(ϕ1)(f^{\phi})^{*}=\phi^{*}f^{*}(\phi^{-1})^{*}, and also that (ϕ1)=ϕ(\phi^{-1})^{*}=\phi_{*}, as ϕ\phi is invertible. So

(fϕ)(ϕμf,v)=ϕf(ϕϕμf,v)=ϕfμf=dϕμf,v.(f^{\phi})^{*}(\phi^{*}\mu_{f,v})=\phi^{*}f^{*}(\phi_{*}\phi^{*}\mu_{f,v})=\phi^{*}f^{*}\mu_{f}=d\phi^{*}\mu_{f,v}.

This and the fact that the canonical measure is characterized by the identity (fϕ)μfϕ,v=dμfϕ(f^{\phi})^{*}\mu_{f^{\phi},v}=d\mu_{f^{\phi}} shows (6.1). As remarked above, the canonical adelic measure of a power map is λstd\lambda_{\mathrm{std}}; this adelic measure is simple enough to admit a direct computation of μPdϕ2=ϕλstd2\|\mu_{P_{d}^{\phi}}\|^{2}=\|\phi^{*}\lambda_{\mathrm{std}}\|^{2}.

Proposition 6.2.

Let ϕ(z)=az+b\phi(z)=az+b with aK{0}a\in K\setminus\{0\} and bKb\in K and let Pd(z)=zdP_{d}(z)=z^{d} (|d|2)\;(|d|\geq 2). Then

μPdϕ2=log2+vMK0rvlogmax(1,|a|v2,|b|v2)+vMKrvlogηv(a,b),\|\mu_{P_{d}^{\phi}}\|^{2}=-\log 2+\sum_{v\in M_{K}^{0}}r_{v}\log\max(1,|a|^{2}_{v},|b|^{2}_{v})+\sum_{v\in M_{K}^{\infty}}r_{v}\log\eta_{v}(a,b),

where ηv(a,b)=1+|a|v2+|b|v2+(|a|v2+(1|b|v)2)(|a|v2+(1+|b|v)2)\eta_{v}(a,b)=1+|a|_{v}^{2}+|b|_{v}^{2}+\sqrt{(|a|_{v}^{2}+(1-|b|_{v})^{2})(|a|_{v}^{2}+(1+|b|_{v})^{2})}.

Proof.

From Proposition 3.6, 2vMKrvUμ,v()=μPdϕ22\sum_{v\in M_{K}}r_{v}U_{\mu,v}(\infty)=\|\mu_{P_{d}^{\phi}}\|^{2}. So we compute 2UPdϕ,v()2U_{P_{d}^{\phi},v}(\infty) at each place. For non-Archimedean vv, (6.1) implies

UPdϕ,v()=log+|z|vdϕδζGauss=log+|ϕ1(z)|vdδζGauss(z),U_{{P_{d}^{\phi}},v}(\infty)=\int\log^{+}|z|_{v}\;d\phi^{*}\delta_{\zeta_{\mathrm{Gauss}}}=\int\log^{+}|\phi^{-1}(z)|_{v}\;d\delta_{\zeta_{\mathrm{Gauss}}}(z),

where, as in Section 5, ||v|\cdot|_{v} is the continuous extension of the absolute value from v{\mathbb{C}}_{v} to 𝐀v1\mathbf{A}_{v}^{1}. Thus |ϕ1(ζGauss)|v=supzv|z|v1|(zb)/a|v=max(|a|v1,|b/a|v)|\phi^{-1}(\zeta_{\mathrm{Gauss}})|_{v}=\sup_{\begin{subarray}{c}z\in{\mathbb{C}}_{v}\\ |z|_{v}\leq 1\end{subarray}}|(z-b)/a|_{v}=\max(|a|_{v}^{-1},|b/a|_{v}) and so

(6.2) 2UPdϕ,v()=logmax(1,|a|v2,|b/a|v2).2U_{{P_{d}^{\phi}},v}(\infty)=\log\max(1,|a|_{v}^{-2},|b/a|^{2}_{v}).

For Archimedean vv, we are led to consider integrals of the form 02πlog(1+|αeiθ+β|2)dθ2π\int_{0}^{2\pi}\log(1+|\alpha e^{i\theta}+\beta|^{2})\frac{d\theta}{2\pi}, where α\alpha and β\beta are complex numbers. We claim that

(6.3) 02πlog(1+|αeiθ+β|2)dθ2π=log(1+α2+β2+(1+(αβ)2)(1+(α+β)2))log2.\int_{0}^{2\pi}\log\left(1+|\alpha e^{i\theta}+\beta|^{2}\right)\;\frac{d\theta}{2\pi}=\log\left(1+\alpha^{2}+\beta^{2}+\sqrt{(1+(\alpha-\beta)^{2})(1+(\alpha+\beta)^{2})}\right)-\log 2.

Assuming (6.3) is true, then (6.1) implies

2UPdϕ,v()\displaystyle 2U_{{P_{d}^{\phi}},v}(\infty) =02πlog(1+|ϕ1(eiθ)|v2)dθ2π\displaystyle=\int_{0}^{2\pi}\log(1+|\phi^{-1}(e^{i\theta})|_{v}^{2})\;\frac{d\theta}{2\pi}
=02πlog(1+|(eiθb)/a|v2)dθ2π\displaystyle=\int_{0}^{2\pi}\log(1+|(e^{i\theta}-b)/a|_{v}^{2})\frac{d\theta}{2\pi}
=log(1+|a|v2+|b/a|v2+(1+(|a|v1|b/a|v)2)(1+(|a|v1+|b/a|v)2))log2.\displaystyle=\log\left(1+|a|_{v}^{-2}+|b/a|_{v}^{2}+\sqrt{(1+(|a|_{v}^{-1}-|b/a|_{v})^{2})(1+(|a|_{v}^{-1}+|b/a|_{v})^{2})}\right)-\log 2.

This, (6.2), and the product formula imply

μPdϕ2\displaystyle\|\mu_{P_{d}^{\phi}}\|^{2} =2vMKrvUPdϕ,v()\displaystyle=2\sum_{v\in M_{K}}r_{v}U_{{P_{d}^{\phi}},v}(\infty)
=vMKrvlog|a|v2+2vMKrvUPdϕ,v()\displaystyle=\sum_{v\in M_{K}}r_{v}\log|a|_{v}^{2}+2\sum_{v\in M_{K}}r_{v}U_{{P_{d}^{\phi}},v}(\infty)
=vMK0rvlogmax(1,|a|v2,|b|v2)+vMKrv(logηv(a,b)log2),\displaystyle=\sum_{v\in M_{K}^{0}}r_{v}\log\max(1,|a|^{2}_{v},|b|^{2}_{v})+\sum_{v\in M_{K}^{\infty}}r_{v}(\log\eta_{v}(a,b)-\log 2),

where ηv(a,b)=1+|a|v2+|b|v2+(|a|v2+(1|b|v)2)(|a|v2+(1+|b|v)2)\eta_{v}(a,b)=1+|a|_{v}^{2}+|b|_{v}^{2}+\sqrt{(|a|_{v}^{2}+(1-|b|_{v})^{2})(|a|_{v}^{2}+(1+|b|_{v})^{2})}. Applying the fact that vMKrv(log2)=log2\sum_{v\in M_{K}^{\infty}}r_{v}(-\log 2)=-\log 2 yields the proposition. We therefore turn to proving (6.3). Note that the integral in (6.3) is unchanged if α\alpha and β\beta are replaced by αeiθ\alpha e^{i\theta^{\prime}} and βeiθ′′\beta e^{i\theta^{\prime\prime}} with θ,θ′′[0,2π]\theta^{\prime},\theta^{\prime\prime}\in[0,2\pi]. So assume without loss of generality that α=|α|\alpha=|\alpha| and β=|β|\beta=|\beta|. It is convenient to define the quantities

A=1+(αβ)22andB=1+(α+β)22,A=\sqrt{\frac{1+(\alpha-\beta)^{2}}{2}}\operatorname{\;\;\text{and}\;\;}B=\sqrt{\frac{1+(\alpha+\beta)^{2}}{2}},

and

r=12(A+B)2ands=B2A2(A+B)2.r=\frac{1}{2}\left(A+B\right)^{2}\operatorname{\;\;\text{and}\;\;}s=\frac{B^{2}-A^{2}}{(A+B)^{2}}.

We have the following identities:

1+α2+β2=A2+B2,  2αβ=B2A2,and1+s2=2A2+B2(A+B)2.1+\alpha^{2}+\beta^{2}=A^{2}+B^{2},\;\;2\alpha\beta=B^{2}-A^{2},\operatorname{\;\;\text{and}\;\;}1+s^{2}=2\frac{A^{2}+B^{2}}{(A+B)^{2}}.

It follows from these equations that 1+|αeiθ+b|2=r|1+seiθ|21+|\alpha e^{i\theta}+b|^{2}=r|1+se^{i\theta}|^{2} for all θ[0,2π]\theta\in[0,2\pi]. Consequently

02πlog(1+|αeiθ+β|2)dθ2π=logr+02πlog|1+seiθ|2dθ2π.\int_{0}^{2\pi}\log(1+|\alpha e^{i\theta}+\beta|^{2})\;\frac{d\theta}{2\pi}=\log r+\int_{0}^{2\pi}\log|1+se^{i\theta}|^{2}\;\frac{d\theta}{2\pi}.

This final integral is zero by Jensen’s formula:

02πlog|1+seiθ|2dθ2π=log|s|2+log+|1/s|2=log+|s|2=0.\int_{0}^{2\pi}\log|1+se^{i\theta}|^{2}\;\frac{d\theta}{2\pi}=\log|s|^{2}+\log^{+}|1/s|^{2}=\log^{+}|s|^{2}=0.

So the integral in (6.3) is equal to logr\log r. Expressing rr in terms of α\alpha and β\beta gives the claim. ∎

6.3. A Family of Lattès Maps

Following [PST12], we consider the elliptic curves

Ea,b:y2=P(x)=x(xa)(x+b),E_{a,b}:\;y^{2}=P(x)=x(x-a)(x+b),

where aa and bb are positive integers. The Lattès map associated to Ea,bE_{a,b} is then

(6.4) fa,b(x)=(x2+ab)24x(xa)(x+b).f_{a,b}(x)=\frac{(x^{2}+ab)^{2}}{4x(x-a)(x+b)}.

This is the rational map fa,b:11f_{a,b}:{\mathbb{P}}^{1}\to{\mathbb{P}}^{1} which is semi-conjugate via the xx-coordinate function to the doubling map on Ea,bE_{a,b}. That is, if PP is a point on Ea,bE_{a,b} and [2]:Ea,bEa,b[2]:E_{a,b}\to E_{a,b} is the duplication map, then fa,b(x(P))=x([2]P)f_{a,b}(x(P))=x([2]P). Proposition 20 of [PST12] states that

12log(ab)(fa,b,z2)AZ12log(ab)+C\frac{1}{2}\log(ab)\leq(f_{a,b},z^{2})_{\mathrm{AZ}}\leq\frac{1}{2}\log(ab)+C

where CC is some absolute positive constant. Proposition 3.2 and (3.6) imply that (fa,b,z2)AZ=12μfa,b2+O(1)(f_{a,b},z^{2})_{\mathrm{AZ}}=\frac{1}{2}\|\mu_{f_{a,b}}\|^{2}+O(1). Therefore

(6.5) 12μfa,b2=12log(ab)+O(1)\frac{1}{2}\|\mu_{f_{a,b}}\|^{2}=\frac{1}{2}\log(ab)+O(1)

An inspection of (6.4) reveals that the naive Weil height of the coefficients of fa,bf_{a,b} is log(a2b2)\log(a^{2}b^{2}) for aa and bb sufficiently large (for instance, when ab4ab\geq 4). So (6.5) can be rephrased as 2μfa,b2=h(fa,b)+O(1)2\|\mu_{f_{a,b}}\|^{2}=h(f_{a,b})+O(1). This provides an example of an infinite family of rational maps for which deg(f)2μf2=h(f)+O(1)\frac{\deg(f)}{2}\|\mu_{f}\|^{2}=h(f)+O(1), which is a stronger statement than that of Theorem 1.3. This suggests that it is possible that Theorem 1.3 could be strengthened to show the estimate deg(f)2μf2=h(f)+O(1)\frac{\deg(f)}{2}\|\mu_{f}\|^{2}=h(f)+O(1) holds for rational maps, and not just monic polynomials.

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