Computing distances on Riemann surfaces (2024)

Huck Stepanyantsstepanyants.j@northeastern.eduDepartment of Physics, Northeastern University, Boston, Massachusetts 02115, USANetwork Science Institute, Northeastern University, Boston, Massachusetts 02115, USA  Alan BeardonDepartment of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge CB3 0WB, UK  Jeremy PatonDepartment of Physics, Northeastern University, Boston, Massachusetts 02115, USANetwork Science Institute, Northeastern University, Boston, Massachusetts 02115, USA  Dmitri KrioukovDepartment of Physics, Northeastern University, Boston, Massachusetts 02115, USANetwork Science Institute, Northeastern University, Boston, Massachusetts 02115, USADepartment of Mathematics, Northeastern University, Boston, Massachusetts 02115, USADepartment of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts 02115, USA

Abstract

Riemann surfaces are among the simplest and most basic geometric objects. They appear as key players in many branches of physics, mathematics, and other sciences. Despite their widespread significance, how to compute distances between pairs of points on compact Riemann surfaces is surprisingly unknown, unless the surface is a sphere or a torus. This is because on higher-genus surfaces, the distance formula involves an infimum over infinitely many terms, so it cannot be evaluated in practice. Here we derive a computable distance formula for a broad class of Riemann surfaces. The formula reduces the infimum to a minimum over an explicit set consisting of finitely many terms. We also develop a distance computation algorithm, which cannot be expressed as a formula, but which is more computationally efficient on surfaces with high genuses. We illustrate both the formula and the algorithm in application to generalized Bolza surfaces, which are a particular class of highly symmetric compact Riemann surfaces of any genus greater than1.

I Introduction

Riemann surfacesForster (1981) are one of the simplest geometric objects, with widespreadapplications in physics, mathematics, network science, and other areas. In physics, Riemann surfaces appear naturallyin dynamical systems. The simplest example is billiardsMasur (1986); Gutkin (2012), i.e.,a freely moving ball confined to a polygon-shaped table, and bouncing off its sides.This system is equivalently formulated as a particlemoving along a straight line on a compact Riemann surface. In particular, a particle moving on the Bolzasurface, a compact Riemann surface of genusg=2𝑔2{g=2}italic_g = 2, is one of the simplest and earliest chaotic systemsstudied in physicsHadamard (1898).

Riemann surfaces also appear in integrable systemsBabelonetal. (2003); Gieres (1993).The trajectory of such a system in its parameter space is effectively confined to a Riemann surface.Elsewhere in mathematical physics, Riemann surfaces are a part of string theoryKimetal. (2018); Bonellietal. (2000),potential theoryGustafssonandTkachev (2009); Chirka (2018), and approximation theoryKomlovetal. (2017); Aptekarevetal. (2014); AptekarevandLysov (2010).In quantum physics, Riemann surfaces appear in the study of fractional quantum Hall statesWenandNiu (1990),spin liquidsWen (1991), and quantum gravityAldrovandiandTakhtajan (1997); DistlerandKawai (1989).

In network science, Riemann surfaces have been used as latent spaces in some models of networks.For example, networks embedded in hyperbolic spaces are one of the first models that reproduce acollection of the most basic properties common to many real-world networksKrioukovetal. (2010).Yet our main motivation for this paper comes fromvander Hoornetal. (2021); Hoornetal. (2023), where the convergence of theOllivier curvatureOllivier (2007) of random geometric graphsPenrose (2003); DallandChristensen (2002) to the Ricci curvature of theirunderlying Riemannian manifolds was proven. Vertices in such graphs are random points in a Riemannianmanifold, and pairs of vertices are connected by edges if the distance between the two vertices in themanifold is below a fixed threshold. To build a random geometric graph in a manifold, one thus needs tobe able to compute distances between pairs of points in it.

Computing distances on Riemann surfaces (1)

Compact Riemann surfaces are two-dimensional Riemannian manifolds. They can be equippedwith a metric which defines the distance between a pair of points on the surface.Genusg=0𝑔0{g=0}italic_g = 0 (sphere),g=1𝑔1{g=1}italic_g = 1 (torus), andg2𝑔2{g\geq 2}italic_g ≥ 2 surfaces admit the spherical, euclidean, andhyperbolic metrics, respectively. While computing distances on the first two of these surfacesis trivial, the task is much more difficult on a hyperbolic Riemann surface,where the distance is given as an infimum over a countably infinite number of geodesics,i.e., locally minimal paths. There are no formulas for the distance between pointson any genusg2𝑔2{g\geq 2}italic_g ≥ 2 surface which are computable in finite time. To be precise, while it is knownthat the mentioned infimum is actually a minimum since only a finite set of geodesics needs to beconsidered (Prop.2.1,LuandMeng (2020)), it is not known what this set actually is foranyg2𝑔2{g\geq 2}italic_g ≥ 2 surface, which is surprising since distance plays a crucial role inmany applications of these surfaces mentioned above.

Here we compute distances on Riemann surfaces obtained by pairingthe sides of a convex hyperbolic polygon. We obtain an expression for a finite set of geodesicswhose minimum gives the correct distance between any two points on these surfaces. This leads to a distance formulawhich can be evaluated in finite time. We also develop a fast algorithm for computing distances on thesesurfaces using a different set of ideas. For illustrative purposes, we show how the formula and the algorithm can be appliedto computing distances on generalized Bolza surfacesEbbensetal. (2022). These are highly symmetric hyperbolic Riemann surfacesof any genusg2𝑔2{g\geq 2}italic_g ≥ 2. We prove that the time required to evaluate the formula in this case isO(gαlogg)𝑂superscript𝑔𝛼𝑔{O\left(g^{\alpha\log g}\right)}italic_O ( italic_g start_POSTSUPERSCRIPT italic_α roman_log italic_g end_POSTSUPERSCRIPT ),whereα1.52𝛼1.52{\alpha\approx 1.52}italic_α ≈ 1.52, and show experimentally that the time required to run the algorithm isO(g4)𝑂superscript𝑔4{O\left(g^{4}\right)}italic_O ( italic_g start_POSTSUPERSCRIPT 4 end_POSTSUPERSCRIPT ).

In Sec.II, we provide necessary background information on Riemann surfaces, and a detailed introduction to the distance problem.In Sec.III andIV, we present and discuss our results, a formula and an algorithm, respectively,for computing distances on Riemann surfaces. In Sec.V, we apply our results togeneralized Bolza surfaces, and evaluate the resulting running times.

II Background and definitions

The distance between two points in a space is the length of the shortest geodesic, or locally minimal path,that connects them in the space. If the space is a compact Riemann surface, then the number of geodesics connecting a given pair of points dependson its genus, which is the number of holes the surface has. Given two points on the genus00{0} sphere (Fig.1(a)), there arealways two geodesics between them, and thus the distance is simply a minimum of two lengths. In contrast, the number of geodesics between twopoints on the torus2/2superscript2superscript2{\mathbb{R}^{2}/\mathbb{Z}^{2}}blackboard_R start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT / blackboard_Z start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT is infinite (four are shown in Fig.1(b)),which could make computingdistances on the torus difficult. Nevertheless, due to its symmetry, the distanced𝑑{d}italic_d on the torus is given by the simple formula:

d2=(12|12|x1x2||)2+(12|12|y1y2||)2,superscript𝑑2superscript1212subscript𝑥1subscript𝑥22superscript1212subscript𝑦1subscript𝑦22\displaystyle\begin{split}d^{2}=&\left(\frac{1}{2}-\Big{\lvert}\frac{1}{2}-|x_%{1}-x_{2}|\Big{\rvert}\right)^{2}\\+&\left(\frac{1}{2}-\Big{\lvert}\frac{1}{2}-|y_{1}-y_{2}|\Big{\rvert}\right)^{%2},\end{split}start_ROW start_CELL italic_d start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT = end_CELL start_CELL ( divide start_ARG 1 end_ARG start_ARG 2 end_ARG - | divide start_ARG 1 end_ARG start_ARG 2 end_ARG - | italic_x start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT - italic_x start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT | | ) start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT end_CELL end_ROW start_ROW start_CELL + end_CELL start_CELL ( divide start_ARG 1 end_ARG start_ARG 2 end_ARG - | divide start_ARG 1 end_ARG start_ARG 2 end_ARG - | italic_y start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT - italic_y start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT | | ) start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT , end_CELL end_ROW(1)

where(x1,y1)subscript𝑥1subscript𝑦1{(x_{1},y_{1})}( italic_x start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT , italic_y start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT ) and(x2,y2)[1/2,+1/2]2subscript𝑥2subscript𝑦2superscript12122{(x_{2},y_{2})\in\left[-1/2,+1/2\right]^{2}}( italic_x start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT , italic_y start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT ) ∈ [ - 1 / 2 , + 1 / 2 ] start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT are the coordinates of the representatives of two points on the torus, whichis the unit square with vertices at(±1/2,±1/2)plus-or-minus12plus-or-minus12{(\pm 1/2,\pm 1/2)}( ± 1 / 2 , ± 1 / 2 ) whose opposite sides are paired, Fig.1(c). For genusg>1𝑔1{g>1}italic_g > 1 (hyperbolic) surfaces,the number of geodesic paths connecting two points is also infinite. Yet there are no closed-form distanceformulas analogous to Eq.(1) for any of these surfaces.

Here, we address the distance problem for the hyperbolic Riemann surfaces known as quotient surfaces.A quotient surface is constructed by taking the quotient of the hyperbolic plane2superscript2{\mathbb{H}^{2}}blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT with respect to a discretesubgroup of its isometries, or distance-preserving transformations, called a Fuchsian group, which we describe next.

We will use the Poincaré disk model of2superscript2{\mathbb{H}^{2}}blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT, which is thecomplex unit disk equipped with the metric

ds2=4dzdz¯(1|z|2)2.𝑑superscript𝑠24𝑑𝑧𝑑¯𝑧superscript1superscript𝑧22\displaystyle ds^{2}=\frac{4dzd\bar{z}}{(1-|z|^{2})^{2}}.italic_d italic_s start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT = divide start_ARG 4 italic_d italic_z italic_d over¯ start_ARG italic_z end_ARG end_ARG start_ARG ( 1 - | italic_z | start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT ) start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT end_ARG .(2)

The group of orientation-preserving isometries of the Poincaré disk is the projective specialunitary groupPSU(1,1)PSU11{\text{PSU}(1,1)}PSU ( 1 , 1 ), the quotient of the special unitary groupSU(1,1)SU11{\text{SU}(1,1)}SU ( 1 , 1 ) byits center{I,I}𝐼𝐼{\{I,-I\}}{ italic_I , - italic_I }. In matrix form, these isometries are

γ=[ac¯ca¯],a,c:|a|2|c|2=1,:formulae-sequence𝛾delimited-[]matrix𝑎¯𝑐𝑐¯𝑎for-all𝑎𝑐superscript𝑎2superscript𝑐21\gamma=\left[\begin{matrix}a&\overline{c}\\c&\overline{a}\end{matrix}\right],\quad\forall a,c\in\mathbb{C}~{}:~{}\lvert a%\rvert^{2}-\lvert c\rvert^{2}=1,italic_γ = [ start_ARG start_ROW start_CELL italic_a end_CELL start_CELL over¯ start_ARG italic_c end_ARG end_CELL end_ROW start_ROW start_CELL italic_c end_CELL start_CELL over¯ start_ARG italic_a end_ARG end_CELL end_ROW end_ARG ] , ∀ italic_a , italic_c ∈ blackboard_C : | italic_a | start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT - | italic_c | start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT = 1 ,(3)

which act on pointsz𝑧{z\in\mathbb{C}}italic_z ∈ blackboard_C via fractional linear transformations,

[ac¯ca¯](z)=az+c¯cz+a¯.delimited-[]matrix𝑎¯𝑐𝑐¯𝑎𝑧𝑎𝑧¯𝑐𝑐𝑧¯𝑎\left[\begin{matrix}a&\overline{c}\\c&\overline{a}\end{matrix}\right](z)=\frac{az+\overline{c}}{cz+\overline{a}}.[ start_ARG start_ROW start_CELL italic_a end_CELL start_CELL over¯ start_ARG italic_c end_ARG end_CELL end_ROW start_ROW start_CELL italic_c end_CELL start_CELL over¯ start_ARG italic_a end_ARG end_CELL end_ROW end_ARG ] ( italic_z ) = divide start_ARG italic_a italic_z + over¯ start_ARG italic_c end_ARG end_ARG start_ARG italic_c italic_z + over¯ start_ARG italic_a end_ARG end_ARG .(4)
Computing distances on Riemann surfaces (2)

A subgroupΓΓ{\Gamma}roman_Γ of the isometry groupPSU(1,1)PSU11{\text{PSU}(1,1)}PSU ( 1 , 1 )is called Fuchsian if it acts discontinuouslyon2superscript2{\mathbb{H}^{2}}blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT. This means that for any pointz𝑧{z}italic_z, the orbitΓzΓ𝑧{\Gamma z}roman_Γ italic_z has no accumulationpointsw,|w|<1𝑤𝑤1{w,~{}|w|<1}italic_w , | italic_w | < 1. An accumulation pointw𝑤{w}italic_w is one for which there are elements ofΓzΓ𝑧{\Gamma z}roman_Γ italic_zin any arbitrarily small punctured disk aroundw𝑤{w}italic_w. Every Fuchsian group defines a quotientsurface,

S=2/Γ.𝑆superscript2Γ\displaystyle S=\mathbb{H}^{2}\big{/}\Gamma.italic_S = blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT / roman_Γ .(5)

Points[z]delimited-[]𝑧{[z]}[ italic_z ] onS𝑆{S}italic_S are orbits of pointsz𝑧{z}italic_z in2superscript2{\mathbb{H}^{2}}blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT under actions byΓΓ{\Gamma}roman_Γ,

[z]=Γz.delimited-[]𝑧Γ𝑧\displaystyle[z]=\Gamma z.[ italic_z ] = roman_Γ italic_z .(6)

The distanceδ(z,w)superscript𝛿𝑧𝑤{\delta^{\star}(z,w)}italic_δ start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ( italic_z , italic_w ) between two points[z]delimited-[]𝑧{[z]}[ italic_z ] and[w]delimited-[]𝑤{[w]}[ italic_w ] onS𝑆{S}italic_S isa distance between orbitsΓzΓ𝑧{\Gamma z}roman_Γ italic_z andΓwΓ𝑤{\Gamma w}roman_Γ italic_w in2superscript2{\mathbb{H}^{2}}blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT. It is given by

δ(z,w)=infγ1,γ2Γδ(γ1z,γ2w)=infγΓδ(z,γw),superscript𝛿𝑧𝑤subscriptinfimumsubscript𝛾1subscript𝛾2Γ𝛿subscript𝛾1𝑧subscript𝛾2𝑤subscriptinfimum𝛾Γ𝛿𝑧𝛾𝑤\displaystyle\begin{split}\delta^{\star}(z,w)&=\inf_{\gamma_{1},\gamma_{2}\in%\Gamma}\delta(\gamma_{1}z,\gamma_{2}w)\\&=\inf_{\gamma\in\Gamma}\delta(z,\gamma w),\end{split}start_ROW start_CELL italic_δ start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ( italic_z , italic_w ) end_CELL start_CELL = roman_inf start_POSTSUBSCRIPT italic_γ start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT , italic_γ start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT ∈ roman_Γ end_POSTSUBSCRIPT italic_δ ( italic_γ start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT italic_z , italic_γ start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT italic_w ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL = roman_inf start_POSTSUBSCRIPT italic_γ ∈ roman_Γ end_POSTSUBSCRIPT italic_δ ( italic_z , italic_γ italic_w ) , end_CELL end_ROW(7)

whereδ𝛿{\delta}italic_δ is the distance in2superscript2{\mathbb{H}^{2}}blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT.This formula cannot be directly evaluated, sinceΓΓ{\Gamma}roman_Γ has infinitely manyelements. To findδ(z,w)superscript𝛿𝑧𝑤{\delta^{\star}(z,w)}italic_δ start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ( italic_z , italic_w ), one must consider infinitely many geodesics fromz𝑧{z}italic_ztoγw𝛾𝑤{\gamma w}italic_γ italic_w. Every such geodesic corresponds to a different minimal path between thesame pair of points onS𝑆{S}italic_S, like those illustrated in Fig.1 for the sphere and torus,or in Fig.6 for the Bolza surface.

Here we will focus on surfacesS𝑆{S}italic_S whose Fuchsian groupsΓΓ{\Gamma}roman_Γ are finitely generated andof the first kind. The latter means that any point on the boundary of the unit disk, which is theboundary at infinity of the hyperbolic plane2superscript2{\mathbb{H}^{2}}blackboard_H start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT, is an accumulation point of some orbitofΓΓ{\Gamma}roman_Γ. This guarantees thatS𝑆{S}italic_S is a compact surface, and byTheorem10.1.2 inBeardon (2012),S𝑆{S}italic_Shas a convex fundamental polygonP𝑃{P}italic_P with a finite number of sides.A fundamental polygon is one that containsexactly one representative of each point onS𝑆{S}italic_S, see Fig.2. It is knownBeardon (2012) thatin such settings, the generators of the groupΓΓ{\Gamma}roman_Γ pair sides ofP𝑃{P}italic_P by mapping itto its edge-adjacent neighbors, shown in light grayin Fig.2. We will further assume thatP𝑃{P}italic_P does not have any vertices at infinity.

Using the geometry ofP𝑃{P}italic_P, we develop two methods for computing distances onS𝑆{S}italic_S.In the next Sec.III, we present a distance formula which reduces theinfinities in Eq.(7) to finite sets. Then in Sec.IV, we developa more efficient algorithmic approach to the problem.

Computing distances on Riemann surfaces (3)

III Distance formula

LetS𝑆{S}italic_S be a quotient surface obtained by pairing the sides of a convex fundamentalpolygonP𝑃{P}italic_P, and letΓΓ{\Gamma}roman_Γ denote its Fuchsian group. Letz𝑧{z}italic_z andw𝑤{w}italic_w berepresentatives of two points on the surface. In this section we obtain acomputable version of Eq.(7), where instead of minimizingδ(z,γw)𝛿𝑧𝛾𝑤{\delta(z,\gamma w)}italic_δ ( italic_z , italic_γ italic_w )over allγΓ𝛾Γ{\gamma\in\Gamma}italic_γ ∈ roman_Γ, we minimize over a finite subsetΓ0ΓsubscriptΓ0Γ{\Gamma_{0}\subset\Gamma}roman_Γ start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT ⊂ roman_Γ.We will derive a formula forΓ0subscriptΓ0{\Gamma_{0}}roman_Γ start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT using the geometry ofP𝑃{P}italic_P.

Let us call a pair of images ofP𝑃{P}italic_P neighbors if they share either a common edge or a common vertex.LetTΓ𝑇Γ{T\subset\Gamma}italic_T ⊂ roman_Γ denote the subset of isometries from the Fuchsian group which mapP𝑃{P}italic_Pto all of its neighbors and itself. Then we define thekthsuperscript𝑘th{k^{\text{th}}}italic_k start_POSTSUPERSCRIPT th end_POSTSUPERSCRIPTshellLksubscript𝐿𝑘{L_{k}}italic_L start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT,fork1𝑘1{k\geq 1}italic_k ≥ 1, to be the difference

γTkγP\γTk1γP,subscript𝛾superscript𝑇𝑘\𝛾𝑃subscript𝛾superscript𝑇𝑘1𝛾𝑃\displaystyle\bigcup_{\gamma\in T^{k}}\gamma P\bigg{\backslash}\bigcup_{\gamma%\in T^{k-1}}\gamma P,⋃ start_POSTSUBSCRIPT italic_γ ∈ italic_T start_POSTSUPERSCRIPT italic_k end_POSTSUPERSCRIPT end_POSTSUBSCRIPT italic_γ italic_P \ ⋃ start_POSTSUBSCRIPT italic_γ ∈ italic_T start_POSTSUPERSCRIPT italic_k - 1 end_POSTSUPERSCRIPT end_POSTSUBSCRIPT italic_γ italic_P ,(8)

and fork=0𝑘0{k=0}italic_k = 0, we defineL0=Psubscript𝐿0𝑃{L_{0}=P}italic_L start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT = italic_P, as illustrated in Fig.3.

We next compute an upper bound on the minimum value ofk𝑘{k}italic_k,kminsubscript𝑘{k_{\min}}italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT, for which the correct valueof the distanceδ(z,w)superscript𝛿𝑧𝑤{\delta^{\star}(z,w)}italic_δ start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ( italic_z , italic_w ) is obtained by minimizingδ(z,γw)𝛿𝑧𝛾𝑤{\delta(z,\gamma w)}italic_δ ( italic_z , italic_γ italic_w )overγTkfor-all𝛾superscript𝑇𝑘{\forall\gamma\in T^{k}}∀ italic_γ ∈ italic_T start_POSTSUPERSCRIPT italic_k end_POSTSUPERSCRIPT. Thuskminsubscript𝑘{k_{\min}}italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT is the minimum positive integerk𝑘{k}italic_k satisfying

δ(z,w)=minγTkδ(z,γw)superscript𝛿𝑧𝑤subscript𝛾superscript𝑇𝑘𝛿𝑧𝛾𝑤\displaystyle\delta^{\star}(z,w)=\min_{\gamma\in T^{k}}\delta(z,\gamma w)italic_δ start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ( italic_z , italic_w ) = roman_min start_POSTSUBSCRIPT italic_γ ∈ italic_T start_POSTSUPERSCRIPT italic_k end_POSTSUPERSCRIPT end_POSTSUBSCRIPT italic_δ ( italic_z , italic_γ italic_w )(9)

for allz𝑧{z}italic_z andw𝑤{w}italic_w. In other words, the finite subsetΓ0ΓsubscriptΓ0Γ{\Gamma_{0}\subset\Gamma}roman_Γ start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT ⊂ roman_Γ mentioned abovecan be taken to be

Γ0=Tkmin.subscriptΓ0superscript𝑇subscript𝑘\displaystyle\Gamma_{0}=T^{k_{\min}}.roman_Γ start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT = italic_T start_POSTSUPERSCRIPT italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT end_POSTSUPERSCRIPT .(10)

We boundkminsubscript𝑘{k_{\min}}italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT for an arbitrary surface by the ratio of two distances: the surfacediameter𝒟𝒟{\mathscr{D}}script_D, i.e., the maximum possible distance between two points on the surface, andthe minimal distance𝒯𝒯{\mathscr{T}}script_T required to traverse a shell.To traverse here means to cross from the outer boundary ofLksubscript𝐿𝑘{L_{k}}italic_L start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT to the outerboundary ofLk+1subscript𝐿𝑘1{L_{k+1}}italic_L start_POSTSUBSCRIPT italic_k + 1 end_POSTSUBSCRIPT fork0𝑘0{k\geq 0}italic_k ≥ 0. In AppendixA, we show that this distance does not dependonk𝑘{k}italic_k, and satisfies the inequality

𝒯min(δ,2ϵ),𝒯𝛿2italic-ϵ\displaystyle\mathscr{T}\geq\min(\delta,2\epsilon),script_T ≥ roman_min ( italic_δ , 2 italic_ϵ ) ,(11)

whereδ𝛿{\delta}italic_δ is the minimum distance between any pair of non-adjacent sides ofP𝑃{P}italic_P, andϵitalic-ϵ{\epsilon}italic_ϵ isthe minimum distance from the midpoint of an side to any adjacent side as illustrated inFig.4.

Computing distances on Riemann surfaces (4)

Then the distance required to cross from a starting point inL0=Psubscript𝐿0𝑃{L_{0}=P}italic_L start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT = italic_P to a pointinLksubscript𝐿𝑘{L_{k}}italic_L start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT is lower-bounded by(k1)𝒯𝑘1𝒯{(k-1)\mathscr{T}}( italic_k - 1 ) script_T. Since𝒟𝒟{\mathscr{D}}script_D is the surface diameter,thenkminsubscript𝑘{k_{\min}}italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT must satisfy the inequality

(kmin1)𝒯<𝒟.subscript𝑘1𝒯𝒟\displaystyle(k_{\min}-1)\mathscr{T}<\mathscr{D}.( italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT - 1 ) script_T < script_D .(12)

But the surface diameter𝒟𝒟{\mathscr{D}}script_D is trivially upper bounded by the diameterof its fundamental polygonP𝑃{P}italic_P,diam(P)diam𝑃{\text{diam}(P)}diam ( italic_P ):

𝒟diam(P)=maxijδ(vi,vj),𝒟diam𝑃subscript𝑖𝑗𝛿subscript𝑣𝑖subscript𝑣𝑗\displaystyle\mathscr{D}\leq\text{diam}(P)=\max_{ij}\delta(v_{i},v_{j}),script_D ≤ diam ( italic_P ) = roman_max start_POSTSUBSCRIPT italic_i italic_j end_POSTSUBSCRIPT italic_δ ( italic_v start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT , italic_v start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT ) ,(13)

where thevisubscript𝑣𝑖{v_{i}}italic_v start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT are the vertices ofP𝑃{P}italic_P.Combining Eqs.(11),(12), and(13) leadsto an upper bound onkminsubscript𝑘{k_{\min}}italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT in terms of geometric properties ofP𝑃{P}italic_P, which we denoteksuperscript𝑘{k^{\star}}italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT:

kmink=1+maxijδ(vi,vj)min(δ,2ϵ).subscript𝑘superscript𝑘1subscript𝑖𝑗𝛿subscript𝑣𝑖subscript𝑣𝑗𝛿2italic-ϵ\displaystyle k_{\min}\leq k^{\star}=\Bigg{\lfloor}1+\frac{\max_{ij}\delta(v_{%i},v_{j})}{\min(\delta,2\epsilon)}\Bigg{\rfloor}.italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT ≤ italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT = ⌊ 1 + divide start_ARG roman_max start_POSTSUBSCRIPT italic_i italic_j end_POSTSUBSCRIPT italic_δ ( italic_v start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT , italic_v start_POSTSUBSCRIPT italic_j end_POSTSUBSCRIPT ) end_ARG start_ARG roman_min ( italic_δ , 2 italic_ϵ ) end_ARG ⌋ .(14)

Substituting this bound in Eq.(9) yields an explicit computable formula for the distance betweena pair of points on the surface:

δ(z,w)=minγTkδ(z,γw).superscript𝛿𝑧𝑤subscript𝛾superscript𝑇superscript𝑘𝛿𝑧𝛾𝑤\displaystyle\delta^{\star}(z,w)=\min_{\gamma\in T^{k^{\star}}}\delta(z,\gammaw).italic_δ start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ( italic_z , italic_w ) = roman_min start_POSTSUBSCRIPT italic_γ ∈ italic_T start_POSTSUPERSCRIPT italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT end_POSTSUPERSCRIPT end_POSTSUBSCRIPT italic_δ ( italic_z , italic_γ italic_w ) .(15)

IV Distance algorithm

In this section, we present an algorithm to computeδ(z,w)superscript𝛿𝑧𝑤{\delta^{\star}(z,w)}italic_δ start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ( italic_z , italic_w )by minimizingδ(z,γw)𝛿𝑧𝛾𝑤{\delta(z,\gamma w)}italic_δ ( italic_z , italic_γ italic_w ) over an even smaller subset ofΓΓ{\Gamma}roman_Γ. This subset depends on the locationofz𝑧{z}italic_z and is unknown a priori—instead, it is constructed via a search over thepolygon tessellation. As we will see in Sec.V, this method is generally more computationallyefficient than evaluating the distance formula in Sec.III.

LetN𝑁{N}italic_N be the number of sides ofP𝑃{P}italic_P, andgi,i=1,2,,N,formulae-sequencesubscript𝑔𝑖𝑖12𝑁{g_{i},~{}i=1,2,\dots,N,}italic_g start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT , italic_i = 1 , 2 , … , italic_N , be the generators ofΓΓ{\Gamma}roman_Γand their inverses. With these notations, the algorithm is:

Δ{1}Δ1{\Delta\leftarrow\{1\}}roman_Δ ← { 1 },γmin1subscript𝛾1{\gamma_{\min}\leftarrow 1}italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT ← 1

while|Δ|>0Δ0{|\Delta|>0}| roman_Δ | > 0do

γpop(Δ)𝛾popΔ{\gamma\leftarrow\text{pop}(\Delta)}italic_γ ← pop ( roman_Δ )

ifδ(z,γw)<δ(z,γminw)𝛿𝑧𝛾𝑤𝛿𝑧subscript𝛾𝑤{\delta(z,\gamma w)<\delta(z,\gamma_{\min}w)}italic_δ ( italic_z , italic_γ italic_w ) < italic_δ ( italic_z , italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT italic_w )then

γminγsubscript𝛾𝛾{\gamma_{\min}\leftarrow\gamma}italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT ← italic_γ

endif

fori=1:N:𝑖1𝑁{i=1:N}italic_i = 1 : italic_Ndo

ifδ(z,γP)<δ(z,γgiP)<diam(P)𝛿𝑧𝛾𝑃𝛿𝑧𝛾subscript𝑔𝑖𝑃diam𝑃{\delta(z,\gamma P)<\delta(z,\gamma g_{i}P)<\text{diam}(P)}italic_δ ( italic_z , italic_γ italic_P ) < italic_δ ( italic_z , italic_γ italic_g start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT italic_P ) < diam ( italic_P )then

Δpush(γgi)Δpush𝛾subscript𝑔𝑖{\Delta\leftarrow\text{push}~{}(\gamma g_{i})}roman_Δ ← push ( italic_γ italic_g start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT )

endif

endfor

endwhile

returnγminsubscript𝛾{\gamma_{\min}}italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT

This algorithm is a depth-first search for an imageγw𝛾𝑤{\gamma w}italic_γ italic_w ofw𝑤{w}italic_w,γΓ𝛾Γ{\gamma\in\Gamma}italic_γ ∈ roman_Γ, that minimizesδ(z,γw)𝛿𝑧𝛾𝑤{\delta(z,\gamma w)}italic_δ ( italic_z , italic_γ italic_w ), in the polygon tessellationΓPΓ𝑃{\Gamma P}roman_Γ italic_Pillustrated in Fig.5.We keep track of two variables: the list of isometriesΔΓΔΓ{\Delta\subset\Gamma}roman_Δ ⊂ roman_Γ correspondingto the polygons to be searched next, and the current best solutionγminsubscript𝛾{\gamma_{\min}}italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPTthat minimizesδ(z,γw)𝛿𝑧𝛾𝑤{\delta(z,\gamma w)}italic_δ ( italic_z , italic_γ italic_w ) across allγ𝛾{\gamma}italic_γ searched so far.BothΔΔ{\Delta}roman_Δ andγminsubscript𝛾{\gamma_{\min}}italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT are initialized to theidentity:Δ={1},γmin=1formulae-sequenceΔ1subscript𝛾1{\Delta=\{1\},\gamma_{\min}=1}roman_Δ = { 1 } , italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT = 1, corresponding toP𝑃{P}italic_P itself.

Computing distances on Riemann surfaces (5)

At every step of the search, we setγ𝛾{\gamma}italic_γ to be the last elementofΔΔ{\Delta}roman_Δ, and remove it fromΔΔ{\Delta}roman_Δ.Ifδ(z,γw)<δ(z,γminw)𝛿𝑧𝛾𝑤𝛿𝑧subscript𝛾𝑤{\delta(z,\gamma w)<\delta(z,\gamma_{\min}w)}italic_δ ( italic_z , italic_γ italic_w ) < italic_δ ( italic_z , italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT italic_w ), we updateγminsubscript𝛾{\gamma_{\min}}italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPTtoγ𝛾{\gamma}italic_γ. We then append toΔΔ{\Delta}roman_Δ the group elementsγgi𝛾subscript𝑔𝑖{\gamma g_{i}}italic_γ italic_g start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT,1iN1𝑖𝑁{1\leq i\leq N}1 ≤ italic_i ≤ italic_N,corresponding to polygons that are edge-adjacent to the currently searched polygon, but only if theyare at a greater distance fromz𝑧{z}italic_z:

δ(z,γP)<δ(z,γgiP)<diam(P).𝛿𝑧𝛾𝑃𝛿𝑧𝛾subscript𝑔𝑖𝑃diam𝑃\displaystyle\delta(z,\gamma P)<\delta(z,\gamma g_{i}P)<\text{diam}(P).italic_δ ( italic_z , italic_γ italic_P ) < italic_δ ( italic_z , italic_γ italic_g start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT italic_P ) < diam ( italic_P ) .(16)

Here, the distancesδ(z,γP)𝛿𝑧𝛾𝑃{\delta(z,\gamma P)}italic_δ ( italic_z , italic_γ italic_P ) andδ(z,γgiP)𝛿𝑧𝛾subscript𝑔𝑖𝑃{\delta(z,\gamma g_{i}P)}italic_δ ( italic_z , italic_γ italic_g start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT italic_P ) fromz𝑧{z}italic_zto the polygonsγP𝛾𝑃{\gamma P}italic_γ italic_P andγgiP𝛾subscript𝑔𝑖𝑃{\gamma g_{i}P}italic_γ italic_g start_POSTSUBSCRIPT italic_i end_POSTSUBSCRIPT italic_P are defined to be the minimum distancefromz𝑧{z}italic_z to one of their sides, with the exceptionδ(z,P)=0𝛿𝑧𝑃0{\delta(z,P)=0}italic_δ ( italic_z , italic_P ) = 0.

The reason to consider only those polygons that increase the distance fromz𝑧{z}italic_z is as follows.Consider the shortest path fromz𝑧{z}italic_z toγP𝛾𝑃{\gamma P}italic_γ italic_P, whereγ1𝛾1{\gamma\neq 1}italic_γ ≠ 1. It intersects an edge-adjacentpolygon ofγP𝛾𝑃{\gamma P}italic_γ italic_P. This edge-adjacent polygon is closer toz𝑧{z}italic_z thanγP𝛾𝑃{\gamma P}italic_γ italic_P. Continuing inthis way, we construct a chain of edge-adjacent polygons leading fromγP𝛾𝑃{\gamma P}italic_γ italic_P toP𝑃{P}italic_P along which thedistance toz𝑧{z}italic_z is decreasing, which guarantees thatγP𝛾𝑃{\gamma P}italic_γ italic_P will be reached in the search.

The reason not to search the polygonsγP𝛾𝑃{\gamma P}italic_γ italic_P forwhichδ(z,γP)𝛿𝑧𝛾𝑃{\delta(z,\gamma P)}italic_δ ( italic_z , italic_γ italic_P ) exceedsdiam(P)diam𝑃{\text{diam}(P)}diam ( italic_P ) is this:

δ(z,γminP)δ(z,γminw)𝒟diam(P),𝛿𝑧subscript𝛾𝑃𝛿𝑧subscript𝛾𝑤𝒟diam𝑃\displaystyle\begin{split}\delta(z,\gamma_{\min}P)&\leq\delta(z,\gamma_{\min}w%)\\&\leq\mathscr{D}\\&\leq\text{diam}(P),\end{split}start_ROW start_CELL italic_δ ( italic_z , italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT italic_P ) end_CELL start_CELL ≤ italic_δ ( italic_z , italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT italic_w ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL ≤ script_D end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL ≤ diam ( italic_P ) , end_CELL end_ROW(17)

whereγminsubscript𝛾{\gamma_{\min}}italic_γ start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT is the group element we are looking for, i.e., the one thatminimizesδ(z,γw)𝛿𝑧𝛾𝑤{\delta(z,\gamma w)}italic_δ ( italic_z , italic_γ italic_w ), and𝒟𝒟{\mathscr{D}}script_D is the surface diameter.

Computing distances on Riemann surfaces (6)

Finally, the condition in Eq.(16) ensures that the search terminatesafter a finite time. To see this, letM𝑀{M}italic_M denote the number of polygons within thedistancediam(P)diam𝑃{\text{diam}(P)}diam ( italic_P ) fromz𝑧{z}italic_z. Note that the number of branches of the searchcannot exceed the number of sequences of such polygons ordered by increasing distance, whichis2Msuperscript2𝑀{2^{M}}2 start_POSTSUPERSCRIPT italic_M end_POSTSUPERSCRIPT. Therefore, the number of polygons searched does not exceedM2M𝑀superscript2𝑀{M\cdot 2^{M}}italic_M ⋅ 2 start_POSTSUPERSCRIPT italic_M end_POSTSUPERSCRIPT.We also consider a total ofN𝑁{N}italic_N nearest neighbors ofγP𝛾𝑃{\gamma P}italic_γ italic_P at every search step, eventhough not all of these neighbors are added toΔΔ{\Delta}roman_Δ. Therefore the total number of steps in thealgorithm isO(NM2M)𝑂𝑁𝑀superscript2𝑀{O(NM\cdot 2^{M})}italic_O ( italic_N italic_M ⋅ 2 start_POSTSUPERSCRIPT italic_M end_POSTSUPERSCRIPT ). In practice, however, we find that the number of stepsisO(NM)𝑂𝑁𝑀{O(NM)}italic_O ( italic_N italic_M ), implying that most polygons are searched onlyO(1)𝑂1{O(1)}italic_O ( 1 ) times, as discussed in the nextsection.

V Application to Generalized Bolza Surfaces

In this section, we apply our general results to the generalized Bolza surfacesEbbensetal. (2022),highly symmetric surfaces of any genusg2𝑔2{g\geq 2}italic_g ≥ 2. We denote them bySgsubscript𝑆𝑔{S_{g}}italic_S start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT.S2subscript𝑆2{S_{2}}italic_S start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT is known as the Bolza surfaceBolza (1887).

The generalized Bolza surfaceSgsubscript𝑆𝑔{S_{g}}italic_S start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT has as its fundamental polygonP𝑃{P}italic_P the regular4g4𝑔{4g}4 italic_g-gon withinterior anglesπ/2g𝜋2𝑔{\pi/2g}italic_π / 2 italic_g and vertices

vk=tanh(R/2)exp((k12)πi2g),k=0,1,,4g1,formulae-sequencesubscript𝑣𝑘𝑅2𝑘12𝜋𝑖2𝑔𝑘014𝑔1\displaystyle\begin{split}v_{k}&=\tanh(R/2)\exp\left(\left(k-\frac{1}{2}\right%)\frac{\pi i}{2g}\right),\\k&=0,1,\dots,4g-1,\end{split}start_ROW start_CELL italic_v start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT end_CELL start_CELL = roman_tanh ( italic_R / 2 ) roman_exp ( ( italic_k - divide start_ARG 1 end_ARG start_ARG 2 end_ARG ) divide start_ARG italic_π italic_i end_ARG start_ARG 2 italic_g end_ARG ) , end_CELL end_ROW start_ROW start_CELL italic_k end_CELL start_CELL = 0 , 1 , … , 4 italic_g - 1 , end_CELL end_ROW(18)

whereR𝑅{R}italic_R is the radius ofP𝑃{P}italic_P, which satisfies

coshR=cot2(π4g).𝑅superscript2𝜋4𝑔\displaystyle\cosh R=\cot^{2}\left(\frac{\pi}{4g}\right).roman_cosh italic_R = roman_cot start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT ( divide start_ARG italic_π end_ARG start_ARG 4 italic_g end_ARG ) .(19)

The Fuchsian groupΓgsubscriptΓ𝑔{\Gamma_{g}}roman_Γ start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT ofSgsubscript𝑆𝑔{S_{g}}italic_S start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT is generated by the following2g2𝑔{2g}2 italic_g isometries(Fig.6), which pair opposite sides of the fundamental polygon:

γk=[1tanh(s2)ekπi2gtanh(s2)ekπi2g1],k=0,1,,2g1,formulae-sequencesubscript𝛾𝑘delimited-[]matrix1𝑠2superscript𝑒𝑘𝜋𝑖2𝑔𝑠2superscript𝑒𝑘𝜋𝑖2𝑔1𝑘012𝑔1\displaystyle\begin{split}\gamma_{k}&=\left[\begin{matrix}1&\tanh\left(\frac{s%}{2}\right)e^{\frac{k\pi i}{2g}}\\\tanh\left(\frac{s}{2}\right)e^{-\frac{k\pi i}{2g}}&1\end{matrix}\right],\\k&=0,1,\dots,2g-1,\end{split}start_ROW start_CELL italic_γ start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT end_CELL start_CELL = [ start_ARG start_ROW start_CELL 1 end_CELL start_CELL roman_tanh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) italic_e start_POSTSUPERSCRIPT divide start_ARG italic_k italic_π italic_i end_ARG start_ARG 2 italic_g end_ARG end_POSTSUPERSCRIPT end_CELL end_ROW start_ROW start_CELL roman_tanh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) italic_e start_POSTSUPERSCRIPT - divide start_ARG italic_k italic_π italic_i end_ARG start_ARG 2 italic_g end_ARG end_POSTSUPERSCRIPT end_CELL start_CELL 1 end_CELL end_ROW end_ARG ] , end_CELL end_ROW start_ROW start_CELL italic_k end_CELL start_CELL = 0 , 1 , … , 2 italic_g - 1 , end_CELL end_ROW(20)

wheres𝑠{s}italic_s is the length of a side ofP𝑃{P}italic_P, which satisfies

cosh(s2)=cot(π4g).𝑠2𝜋4𝑔\displaystyle\cosh\left(\frac{s}{2}\right)=\cot\left(\frac{\pi}{4g}\right).roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) = roman_cot ( divide start_ARG italic_π end_ARG start_ARG 4 italic_g end_ARG ) .(21)

Applying the distance formula to these surfaces, we observe thatδ<2ϵ𝛿2italic-ϵ{\delta<2\epsilon}italic_δ < 2 italic_ϵ(cf. Fig.4), and then upper boundδ𝛿{\delta}italic_δusing hyperbolic trigonometry to obtain

min{δ,2ϵ}=δ<arccosh(2cos(π2g)).𝛿2italic-ϵ𝛿arccosh2𝜋2𝑔\displaystyle\min\{\delta,2\epsilon\}=\delta<\text{arccosh}\left(2\cos\left(%\frac{\pi}{2g}\right)\right).roman_min { italic_δ , 2 italic_ϵ } = italic_δ < arccosh ( 2 roman_cos ( divide start_ARG italic_π end_ARG start_ARG 2 italic_g end_ARG ) ) .(22)

The diameter𝒟gsubscript𝒟𝑔{\mathscr{D}_{g}}script_D start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT ofSgsubscript𝑆𝑔{S_{g}}italic_S start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT is knownStepanyantsetal. (2024),

𝒟g=arccosh(cot(π4g)),subscript𝒟𝑔arccosh𝜋4𝑔\displaystyle\mathscr{D}_{g}=\text{arccosh}\left(\cot\left(\frac{\pi}{4g}%\right)\right),script_D start_POSTSUBSCRIPT italic_g end_POSTSUBSCRIPT = arccosh ( roman_cot ( divide start_ARG italic_π end_ARG start_ARG 4 italic_g end_ARG ) ) ,(23)

and therefore we can substitute the actual diameter, instead the upper bound inEq.(13), into Eq.(14) forksuperscript𝑘{k^{\star}}italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT to obtain

k=1+arccosh(cot(π4g))arccosh(2cos(π2g)).superscript𝑘1arccosh𝜋4𝑔arccosh2𝜋2𝑔\displaystyle k^{\star}=\Bigg{\lfloor}1+\frac{\text{arccosh}\left(\cot\left(%\frac{\pi}{4g}\right)\right)}{\text{arccosh}\left(2\cos\left(\frac{\pi}{2g}%\right)\right)}\Bigg{\rfloor}.italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT = ⌊ 1 + divide start_ARG arccosh ( roman_cot ( divide start_ARG italic_π end_ARG start_ARG 4 italic_g end_ARG ) ) end_ARG start_ARG arccosh ( 2 roman_cos ( divide start_ARG italic_π end_ARG start_ARG 2 italic_g end_ARG ) ) end_ARG ⌋ .(24)

The number of polygons inTksuperscript𝑇superscript𝑘{T^{k^{\star}}}italic_T start_POSTSUPERSCRIPT italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT end_POSTSUPERSCRIPT is upper bounded by the number of sequences of2k2superscript𝑘{2k^{\star}}2 italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPTgenerators,

|Tk|<(4g)2k,superscript𝑇superscript𝑘superscript4𝑔2superscript𝑘\displaystyle|T^{k^{\star}}|<(4g)^{2k^{\star}},| italic_T start_POSTSUPERSCRIPT italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT end_POSTSUPERSCRIPT | < ( 4 italic_g ) start_POSTSUPERSCRIPT 2 italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT end_POSTSUPERSCRIPT ,(25)

and sinceklogg/arccosh2superscript𝑘𝑔arccosh2{k^{\star}\approx\log g/\text{arccosh}~{}2}italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT ≈ roman_log italic_g / arccosh 2 for largeg𝑔{g}italic_g, the time required to evaluate the distanceformula isO(gαlogg)𝑂superscript𝑔𝛼𝑔{O\left(g^{\alpha\log g}\right)}italic_O ( italic_g start_POSTSUPERSCRIPT italic_α roman_log italic_g end_POSTSUPERSCRIPT ),whereα=2/arccosh21.52𝛼2arccosh21.52{\alpha=2/\text{arccosh}~{}2\approx 1.52}italic_α = 2 / arccosh 2 ≈ 1.52.

For the Bolza surfaceS2subscript𝑆2{S_{2}}italic_S start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT, evaluating Eq.(24) yieldsk=2superscript𝑘2{k^{\star}=2}italic_k start_POSTSUPERSCRIPT ⋆ end_POSTSUPERSCRIPT = 2, but in AppendixBwe computekminsubscript𝑘{k_{\min}}italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT exactly using different methods:

kmin=1.subscript𝑘1\displaystyle k_{\min}=1.italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT = 1 .(26)

Therefore, the number ofP𝑃{P}italic_P’s images one must search through to compute the distanceis|Tkmin|=49superscript𝑇subscript𝑘49{|T^{k_{\min}}|=49}| italic_T start_POSTSUPERSCRIPT italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT end_POSTSUPERSCRIPT | = 49, corresponding to all polygons adjacent toP𝑃{P}italic_P via either aside or a vertex.

To apply the distance algorithm, we substitute the diameter of the surface fordiam(P)diam𝑃{\text{diam}(P)}diam ( italic_P )in Algorithm1, and find experimentally in Fig.7 that the algorithmrunning time isO(g4)𝑂superscript𝑔4{O(g^{4})}italic_O ( italic_g start_POSTSUPERSCRIPT 4 end_POSTSUPERSCRIPT ). We cannotprove this observation because we cannot estimate the overcount—the average number of times the samepolygon is searched. However, we can show that a maximum ofO(g4)𝑂superscript𝑔4{O(g^{4})}italic_O ( italic_g start_POSTSUPERSCRIPT 4 end_POSTSUPERSCRIPT )polygons can intersect a hyperbolic circle of radiusR𝑅{R}italic_R. Therefore, Fig.7suggests that each polygon is searchedO(1)𝑂1{O(1)}italic_O ( 1 ) times, so overcounting appears to be minimal.

Computing distances on Riemann surfaces (7)

Appendix A Lower bound on𝒯𝒯{\mathscr{T}}script_T

In this section, we prove an upper bound on the shell-crossing distance𝒯𝒯{\mathscr{T}}script_Tfor any quotient surfaceS𝑆{S}italic_S obtained by pairing the sides of a convex polygonP𝑃{P}italic_P.

This distance is

𝒯=min{δ(Tn(P),Tn+1(P)),n0},𝒯𝛿superscript𝑇𝑛𝑃superscript𝑇𝑛1𝑃𝑛0\displaystyle\mathscr{T}=\min\bigg{\{}\delta\left(\partial T^{n}(P),\partial T%^{n+1}(P)\right),\quad n\geq 0\bigg{\}},script_T = roman_min { italic_δ ( ∂ italic_T start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT ( italic_P ) , ∂ italic_T start_POSTSUPERSCRIPT italic_n + 1 end_POSTSUPERSCRIPT ( italic_P ) ) , italic_n ≥ 0 } ,

whereLn=Tn(P)subscript𝐿𝑛superscript𝑇𝑛𝑃{L_{n}=T^{n}(P)}italic_L start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT = italic_T start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT ( italic_P ) is thenthsuperscript𝑛th{n^{\text{th}}}italic_n start_POSTSUPERSCRIPT th end_POSTSUPERSCRIPT shell,TΓ𝑇Γ{T\subseteq\Gamma}italic_T ⊆ roman_Γ is the set consisting of all maps fromP𝑃{P}italic_P toan edge- or vertex-adjacent polygon and the identity, andLnsubscript𝐿𝑛{\partial L_{n}}∂ italic_L start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT is the boundary ofLnsubscript𝐿𝑛{L_{n}}italic_L start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT.

First, observe that forγTn𝛾superscript𝑇𝑛{\gamma\in T^{n}}italic_γ ∈ italic_T start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT we have

γ(P)γT(P)Ln+1.𝛾𝑃𝛾𝑇𝑃subscript𝐿𝑛1\displaystyle\gamma(P)\subseteq\gamma T(P)\subseteq L_{n+1}.italic_γ ( italic_P ) ⊆ italic_γ italic_T ( italic_P ) ⊆ italic_L start_POSTSUBSCRIPT italic_n + 1 end_POSTSUBSCRIPT .

Hence,

δ(γ(P),(γT(P)))δ(γ(P),Ln+1).𝛿𝛾𝑃𝛾𝑇𝑃𝛿𝛾𝑃subscript𝐿𝑛1\displaystyle\delta\Bigl{(}\partial\gamma(P),\partial\left(\gamma T(P)\right)%\Bigr{)}\leq\delta\Bigl{(}\partial\gamma(P),\partial L_{n+1}\Bigr{)}.italic_δ ( ∂ italic_γ ( italic_P ) , ∂ ( italic_γ italic_T ( italic_P ) ) ) ≤ italic_δ ( ∂ italic_γ ( italic_P ) , ∂ italic_L start_POSTSUBSCRIPT italic_n + 1 end_POSTSUBSCRIPT ) .

Since𝒯𝒯{\mathscr{T}}script_T is the minimum of the right hand side over alln0𝑛0{n\geq 0}italic_n ≥ 0 andγTn𝛾superscript𝑇𝑛{\gamma\in T^{n}}italic_γ ∈ italic_T start_POSTSUPERSCRIPT italic_n end_POSTSUPERSCRIPT, and the left hand side isequal toδ(P,(T(P)))𝛿𝑃𝑇𝑃{\delta\Bigl{(}\partial P,\partial\left(T(P)\right)\Bigr{)}}italic_δ ( ∂ italic_P , ∂ ( italic_T ( italic_P ) ) ), which is𝒯absent𝒯{\geq\mathscr{T}}≥ script_T by definition of𝒯𝒯{\mathscr{T}}script_T,we conclude that

𝒯=δ(P,(T(P))).𝒯𝛿𝑃𝑇𝑃\displaystyle\mathscr{T}=\delta\Bigl{(}\partial P,\partial\left(T(P)\right)%\Bigr{)}.script_T = italic_δ ( ∂ italic_P , ∂ ( italic_T ( italic_P ) ) ) .
Computing distances on Riemann surfaces (8)

Next, we introduce edge labels, which are positive integers modulo the numberN𝑁{N}italic_Nof distinct (in the quotient sense) sides ofL0subscript𝐿0{L_{0}}italic_L start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT. First, the label11{1}1 is assignedto an edge ofL0subscript𝐿0{L_{0}}italic_L start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT without loss of generality. Then, theN1𝑁1{N-1}italic_N - 1 edges to the left ofthis edge are labeled2,3,,N123𝑁1{2,3,\dots,N-1}2 , 3 , … , italic_N - 1 (Fig.8). Finally, these labels are copied onto allimages ofL0subscript𝐿0{L_{0}}italic_L start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT via the elements of the Fuchsian group{\mathscr{F}}script_F. Thus, edges are distinct inthe quotient sense if and only if they have different labels. The process of filling in labels, whichwe call label chasing, will be useful later.

Now we will prove the main result of this section:

𝒯min({δij,|ij|0,1}{2ϵk}),\displaystyle\mathscr{T}\geq\min\left(\big{\{}\delta_{ij},~{}|i-j|\neq 0,1\big%{\}}\bigcup\big{\{}2\epsilon_{k}\big{\}}\right),script_T ≥ roman_min ( { italic_δ start_POSTSUBSCRIPT italic_i italic_j end_POSTSUBSCRIPT , | italic_i - italic_j | ≠ 0 , 1 } ⋃ { 2 italic_ϵ start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT } ) ,(27)

whereδijsubscript𝛿𝑖𝑗{\delta_{ij}}italic_δ start_POSTSUBSCRIPT italic_i italic_j end_POSTSUBSCRIPT denotes the distance between edgesi𝑖{i}italic_i andj𝑗{j}italic_j which are distinct andnonadjacent, andϵksubscriptitalic-ϵ𝑘{\epsilon_{k}}italic_ϵ start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT denotes theminimal distance from the midpoint of edgek𝑘{k}italic_k to either of the adjacent edgesk±1plus-or-minus𝑘1{k\pm 1}italic_k ± 1.

Computing distances on Riemann surfaces (9)

Starting once more with arbitrary pointspL0𝑝subscript𝐿0{p\in\partial L_{0}}italic_p ∈ ∂ italic_L start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT andqL1𝑞subscript𝐿1{q\in\partial L_{1}}italic_q ∈ ∂ italic_L start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT, webreakpq¯¯𝑝𝑞{\overline{pq}}over¯ start_ARG italic_p italic_q end_ARG into smaller segments so that each segment is contained in a polygonγ(P)𝛾𝑃{\gamma(P)}italic_γ ( italic_P )and has both endpoints on its boundary. For such a segment, suppose the endpoints lie on edges withlabelsi,j𝑖𝑗{i,j}italic_i , italic_j. We categorize a segment (see Fig.8) as

  1. 1.

    type I ifij=1𝑖𝑗1{i-j=1}italic_i - italic_j = 1,

  2. 2.

    type II ifji=1𝑗𝑖1{j-i=1}italic_j - italic_i = 1, and

  3. 3.

    type III if|ij|>1𝑖𝑗1{|i-j|>1}| italic_i - italic_j | > 1.

The segments cannot be all typeI, since this would imply thatpq¯¯𝑝𝑞{\overline{pq}}over¯ start_ARG italic_p italic_q end_ARG circles around avertex indefinitely without ever reachingL1subscript𝐿1{\partial L_{1}}∂ italic_L start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT, which cannot happen. Similarly,the segments cannot all be typeII. This leaves two cases: there is either (1) aconsecutive pair of typeI and typeII segments in either order, or (2) a typeIII segment.In the first case, we can show using elementary geometry thata lower bound on the combined length of the typeI and typeII segments, yielding a lower boundon𝒯𝒯{\mathscr{T}}script_T, is

𝒯min{2ϵk}.𝒯2subscriptitalic-ϵ𝑘\displaystyle\mathscr{T}\geq\min\big{\{}2\epsilon_{k}\big{\}}.script_T ≥ roman_min { 2 italic_ϵ start_POSTSUBSCRIPT italic_k end_POSTSUBSCRIPT } .(28)

In the second case,𝒯𝒯{\mathscr{T}}script_T is lower bounded by the minimum length of a typeIII segment,

𝒯min{δij,|ij|0,1}.𝒯subscript𝛿𝑖𝑗𝑖𝑗01\displaystyle\mathscr{T}\geq\min\big{\{}\delta_{ij},~{}|i-j|\neq 0,1\big{\}}.script_T ≥ roman_min { italic_δ start_POSTSUBSCRIPT italic_i italic_j end_POSTSUBSCRIPT , | italic_i - italic_j | ≠ 0 , 1 } .(29)

Therefore, in either case, Eq.(27) holds.

Appendix B kmin=1subscript𝑘1k_{\min}=1italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT = 1 for the Bolza surface

In this section, we prove thatkmin=1subscript𝑘1{k_{\min}=1}italic_k start_POSTSUBSCRIPT roman_min end_POSTSUBSCRIPT = 1 for the Bolza surface.

For an arbitrary pointzP𝑧𝑃{z\in P}italic_z ∈ italic_P, it suffices to show that for any pointw𝑤{w}italic_w not in thefirst shellL1subscript𝐿1{L_{1}}italic_L start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT, defined in Sec.III, thereexists a group elementγ𝛾{\gamma}italic_γ such thatδ(z,γw)<δ(z,w)𝛿𝑧𝛾𝑤𝛿𝑧𝑤{\delta(z,\gamma w)<\delta(z,w)}italic_δ ( italic_z , italic_γ italic_w ) < italic_δ ( italic_z , italic_w ). Equivalently, this meansthat the Dirichlet polygon ofz𝑧{z}italic_z is contained insideL1subscript𝐿1{L_{1}}italic_L start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT.

We prove this by contradiction.Assume that there exist pointszP,wL1formulae-sequence𝑧𝑃𝑤subscript𝐿1{z\in P,w\notin L_{1}}italic_z ∈ italic_P , italic_w ∉ italic_L start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT that contradict the aboveassertion:δ(z,w)δ(z,γw)𝛿𝑧𝑤𝛿𝑧𝛾𝑤{\delta(z,w)\leq\delta(z,\gamma w)}italic_δ ( italic_z , italic_w ) ≤ italic_δ ( italic_z , italic_γ italic_w ) for allγ𝛾{\gamma}italic_γ. This meansthatw𝑤{w}italic_w is either inside the Dirichlet polygon ofz𝑧{z}italic_z or on its boundary.Using the argument from AppendixA, thegeodesiczw¯¯𝑧𝑤{\overline{zw}}over¯ start_ARG italic_z italic_w end_ARG must contain either

  • Case (1):

    a segment composed of a pair of typeI and typeII segments in either order, or

  • Case (2):

    a typeIII segment.

Denote the endpoints of this segmentp,q𝑝𝑞{p,q}italic_p , italic_q such thatz𝑧{z}italic_z is closer top𝑝{p}italic_pthan toq𝑞{q}italic_q. Since the Dirichlet polygon ofz𝑧{z}italic_z is convex, containsz𝑧{z}italic_z andw𝑤{w}italic_w,andz,p,q,w𝑧𝑝𝑞𝑤{z,p,q,w}italic_z , italic_p , italic_q , italic_w are on a line,q𝑞{q}italic_q must bein the interior of the Dirichlet polygon ofz𝑧{z}italic_z. This implies thatz𝑧{z}italic_z is in the interiorof the Dirichlet polygon ofq𝑞{q}italic_q, and so by the same argumentp𝑝{p}italic_p must lie in the interior ofthe Dirichlet polygon ofq𝑞{q}italic_q. This means that

δ(p,q)<δ(p,γq)forγ1.𝛿𝑝𝑞𝛿𝑝𝛾𝑞forfor-all𝛾1\displaystyle\delta(p,q)<\delta(p,\gamma q)~{}\text{for}~{}\forall\gamma\neq 1.italic_δ ( italic_p , italic_q ) < italic_δ ( italic_p , italic_γ italic_q ) for ∀ italic_γ ≠ 1 .(30)
Computing distances on Riemann surfaces (10)

Consider now case(1) above, wherep𝑝{p}italic_p andq𝑞{q}italic_q are endpoints of a typeI segment joined to a typeIIsegment (Fig.9). Assume without loss of generality thatq𝑞{q}italic_q is on side11{1}1. Leta=δ(q,v2)𝑎𝛿𝑞subscript𝑣2{a=\delta(q,v_{2})}italic_a = italic_δ ( italic_q , italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT )andb=δ(p,v1)𝑏𝛿𝑝subscript𝑣1{b=\delta(p,v_{1})}italic_b = italic_δ ( italic_p , italic_v start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT ). Label-chasing, we find that there must be an imageqsuperscript𝑞{q^{\prime}}italic_q start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT ofq𝑞{q}italic_qlocated on the same side asp𝑝{p}italic_p. Applying the triangleinequality to trianglesv1Ipsubscript𝑣1𝐼𝑝{\triangle v_{1}Ip}△ italic_v start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT italic_I italic_p andv2Iqsubscript𝑣2𝐼𝑞{\triangle v_{2}Iq}△ italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT italic_I italic_q, whereI𝐼{I}italic_Iis the intersection betweenpq¯¯𝑝𝑞{\overline{pq}}over¯ start_ARG italic_p italic_q end_ARG andv1v2¯¯subscript𝑣1subscript𝑣2{\overline{v_{1}v_{2}}}over¯ start_ARG italic_v start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT end_ARG, gives

δ(p,q)=δ(p,I)+δ(q,I)|δ(v1,I)b|+|δ(v2,I)a||δ(v1,I)b+δ(v2,I)a|=|sab|=δ(p,q),𝛿𝑝𝑞𝛿𝑝𝐼𝛿𝑞𝐼𝛿subscript𝑣1𝐼𝑏𝛿subscript𝑣2𝐼𝑎𝛿subscript𝑣1𝐼𝑏𝛿subscript𝑣2𝐼𝑎𝑠𝑎𝑏𝛿𝑝superscript𝑞\displaystyle\begin{split}\delta(p,q)&=\delta(p,I)+\delta(q,I)\\&\geq|\delta(v_{1},I)-b|+|\delta(v_{2},I)-a|\\&\geq|\delta(v_{1},I)-b+\delta(v_{2},I)-a|\\&=|s-a-b|\\&=\delta(p,q^{\prime}),\end{split}start_ROW start_CELL italic_δ ( italic_p , italic_q ) end_CELL start_CELL = italic_δ ( italic_p , italic_I ) + italic_δ ( italic_q , italic_I ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL ≥ | italic_δ ( italic_v start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT , italic_I ) - italic_b | + | italic_δ ( italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT , italic_I ) - italic_a | end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL ≥ | italic_δ ( italic_v start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT , italic_I ) - italic_b + italic_δ ( italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT , italic_I ) - italic_a | end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL = | italic_s - italic_a - italic_b | end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL = italic_δ ( italic_p , italic_q start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT ) , end_CELL end_ROW(31)

which is a contradiction with Eq.(30).

In case(2), points p𝑝{p}italic_p andq𝑞{q}italic_q are endpoints of a typeIII segment, so they lie on sides of the samepolygon. Consider the imagesp,qsuperscript𝑝superscript𝑞{p^{\prime},q^{\prime}}italic_p start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT , italic_q start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPTofp,q𝑝𝑞{p,q}italic_p , italic_q located on the opposite sides of the polygon, and draw the perpendicular bisectorsofpp¯¯𝑝superscript𝑝{\overline{pp^{\prime}}}over¯ start_ARG italic_p italic_p start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT end_ARG andqq¯¯𝑞superscript𝑞{\overline{qq^{\prime}}}over¯ start_ARG italic_q italic_q start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT end_ARG (Fig.10).Observe thatq𝑞{q}italic_q must be closer top𝑝{p}italic_p than topsuperscript𝑝{p^{\prime}}italic_p start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT (on the same side of the vertical perpendicularbisector asp𝑝{p}italic_p), andp𝑝{p}italic_p must be closer toq𝑞{q}italic_q than toqsuperscript𝑞{q^{\prime}}italic_q start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT (on the same side of the horizontalperpendicular bisector asq𝑞{q}italic_q). This is only possible whenp𝑝{p}italic_p andq𝑞{q}italic_q are exactly 2 edges apart and lie inthe same quarter-polygon, as shown in Fig.10.

Computing distances on Riemann surfaces (11)

Next, assume without loss of generality thatq𝑞{q}italic_q is on side11{1}1 (Fig.11), and uselabel-chasing to determine the location of another image ofq𝑞{q}italic_q, denotedq′′superscript𝑞′′{q^{\prime\prime}}italic_q start_POSTSUPERSCRIPT ′ ′ end_POSTSUPERSCRIPT.Leta=δ(q,v1)𝑎𝛿𝑞subscript𝑣1{a=\delta(q,v_{1})}italic_a = italic_δ ( italic_q , italic_v start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT ) andb=δ(p,v2)𝑏𝛿𝑝subscript𝑣2{b=\delta(p,v_{2})}italic_b = italic_δ ( italic_p , italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT ). From Fig.10, we have0<{a,b}<s/20𝑎𝑏𝑠2{0<\{a,b\}<s/2}0 < { italic_a , italic_b } < italic_s / 2.Applying hyperbolic trigonometry to quadrilateralpqv1v2𝑝𝑞subscript𝑣1subscript𝑣2{pqv_{1}v_{2}}italic_p italic_q italic_v start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT and righttrianglepv2q′′𝑝subscript𝑣2superscript𝑞′′{\triangle pv_{2}q^{\prime\prime}}△ italic_p italic_v start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT italic_q start_POSTSUPERSCRIPT ′ ′ end_POSTSUPERSCRIPT, one can show that

cosh(δ(p,q))=cosh2(s2)cosh(s2b)×cosh(s2a)sinh(s2)sinh(sab),𝛿𝑝𝑞superscript2𝑠2𝑠2𝑏𝑠2𝑎𝑠2𝑠𝑎𝑏\displaystyle\begin{split}\cosh(\delta(p,q))&=\cosh^{2}\left(\frac{s}{2}\right%)\cosh\left(\frac{s}{2}-b\right)\\&\times\cosh\left(\frac{s}{2}-a\right)\\&-\sinh\left(\frac{s}{2}\right)\sinh(s-a-b),\end{split}start_ROW start_CELL roman_cosh ( italic_δ ( italic_p , italic_q ) ) end_CELL start_CELL = roman_cosh start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_b ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL × roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_a ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL - roman_sinh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_sinh ( italic_s - italic_a - italic_b ) , end_CELL end_ROW(32)
cosh(δ(p,q′′))𝛿𝑝superscript𝑞′′\displaystyle\cosh(\delta(p,q^{\prime\prime}))roman_cosh ( italic_δ ( italic_p , italic_q start_POSTSUPERSCRIPT ′ ′ end_POSTSUPERSCRIPT ) )=coshacoshb.absent𝑎𝑏\displaystyle=\cosh a\cosh b.= roman_cosh italic_a roman_cosh italic_b .(33)

Rearranging the first equation gives

cosh(δ(p,q))coshb=𝛿𝑝𝑞𝑏absent\displaystyle\frac{\cosh(\delta(p,q))}{\cosh b}=divide start_ARG roman_cosh ( italic_δ ( italic_p , italic_q ) ) end_ARG start_ARG roman_cosh italic_b end_ARG =sinh(s2)cosh(s2a)𝑠2𝑠2𝑎\displaystyle\sinh\left(\frac{s}{2}\right)\cosh\left(\frac{s}{2}-a\right)roman_sinh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_a )
×[sinh(s2)tanh(s2a)\displaystyle\times\bigg{[}\sinh\left(\frac{s}{2}\right)\tanh\left(\frac{s}{2}%-a\right)× [ roman_sinh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_tanh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_a )
+cosh(s2)cosh2(s2)]tanhb\displaystyle+\cosh\left(\frac{s}{2}\right)-\cosh^{2}\left(\frac{s}{2}\right)%\bigg{]}\tanh b+ roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) - roman_cosh start_POSTSUPERSCRIPT 2 end_POSTSUPERSCRIPT ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) ] roman_tanh italic_b
+C,𝐶\displaystyle+C,+ italic_C ,(34)

whereC𝐶{C}italic_C is a function ofs𝑠{s}italic_s anda𝑎{a}italic_a only. The coefficient in front oftanhb𝑏{\tanh b}roman_tanh italic_b is a decreasing functionofa𝑎{a}italic_a and is negative ata=0𝑎0{a=0}italic_a = 0. It is therefore negative forall0as/20𝑎𝑠2{0\leq a\leq s/2}0 ≤ italic_a ≤ italic_s / 2. It follows that as a function ofb𝑏{b}italic_b,cosh(δ(p,q))/coshb𝛿𝑝𝑞𝑏{\cosh(\delta(p,q))/\cosh b}roman_cosh ( italic_δ ( italic_p , italic_q ) ) / roman_cosh italic_bis minimized atb=s/2𝑏𝑠2{b=s/2}italic_b = italic_s / 2. It also follows from Eq.(33) that cosh(δ(p,q′′))/coshb𝛿𝑝superscript𝑞′′𝑏{\cosh(\delta(p,q^{\prime\prime}))/\cosh b}roman_cosh ( italic_δ ( italic_p , italic_q start_POSTSUPERSCRIPT ′ ′ end_POSTSUPERSCRIPT ) ) / roman_cosh italic_b does notdepend onb𝑏{b}italic_b. To obtain a contradiction, it therefore suffices to show that

cosh(δ(p,q))coshbcosh(δ(p,q′′))coshb𝛿𝑝𝑞𝑏𝛿𝑝superscript𝑞′′𝑏\displaystyle\frac{\cosh(\delta(p,q))}{\cosh b}\geq\frac{\cosh(\delta(p,q^{%\prime\prime}))}{\cosh b}divide start_ARG roman_cosh ( italic_δ ( italic_p , italic_q ) ) end_ARG start_ARG roman_cosh italic_b end_ARG ≥ divide start_ARG roman_cosh ( italic_δ ( italic_p , italic_q start_POSTSUPERSCRIPT ′ ′ end_POSTSUPERSCRIPT ) ) end_ARG start_ARG roman_cosh italic_b end_ARG(35)

for0as/20𝑎𝑠2{0\leq a\leq s/2}0 ≤ italic_a ≤ italic_s / 2 andb=s/2𝑏𝑠2{b=s/2}italic_b = italic_s / 2. Pluggingb=s/2𝑏𝑠2{b=s/2}italic_b = italic_s / 2 into Eq.(32) gives

cosh(δ(p,q))cosh(s/2)=cosh(s2)cosh(s2a)tanh(s2)sinh(s2a).𝛿𝑝𝑞𝑠2𝑠2𝑠2𝑎𝑠2𝑠2𝑎\displaystyle\begin{split}\frac{\cosh(\delta(p,q))}{\cosh(s/2)}&=\cosh\left(%\frac{s}{2}\right)\cosh\left(\frac{s}{2}-a\right)\\&-\tanh\left(\frac{s}{2}\right)\sinh\left(\frac{s}{2}-a\right).\end{split}start_ROW start_CELL divide start_ARG roman_cosh ( italic_δ ( italic_p , italic_q ) ) end_ARG start_ARG roman_cosh ( italic_s / 2 ) end_ARG end_CELL start_CELL = roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_a ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL - roman_tanh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_sinh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_a ) . end_CELL end_ROW(36)

Usingcosh(s/2)>1𝑠21{\cosh(s/2)>1}roman_cosh ( italic_s / 2 ) > 1 in the last equation, we get

cosh(δ(p,q))cosh(s/2)cosh(s2)cosh(s2a)sinh(s2)sinh(s2a)=cosha=cosh(δ(p,q′′))cosh(s/2),𝛿𝑝𝑞𝑠2𝑠2𝑠2𝑎𝑠2𝑠2𝑎𝑎𝛿𝑝superscript𝑞′′𝑠2\displaystyle\begin{split}\frac{\cosh(\delta(p,q))}{\cosh(s/2)}&\geq\cosh\left%(\frac{s}{2}\right)\cosh\left(\frac{s}{2}-a\right)\\&-\sinh\left(\frac{s}{2}\right)\sinh\left(\frac{s}{2}-a\right)\\&=\cosh a\\&=\frac{\cosh(\delta(p,q^{\prime\prime}))}{\cosh(s/2)},\end{split}start_ROW start_CELL divide start_ARG roman_cosh ( italic_δ ( italic_p , italic_q ) ) end_ARG start_ARG roman_cosh ( italic_s / 2 ) end_ARG end_CELL start_CELL ≥ roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_cosh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_a ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL - roman_sinh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG ) roman_sinh ( divide start_ARG italic_s end_ARG start_ARG 2 end_ARG - italic_a ) end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL = roman_cosh italic_a end_CELL end_ROW start_ROW start_CELL end_CELL start_CELL = divide start_ARG roman_cosh ( italic_δ ( italic_p , italic_q start_POSTSUPERSCRIPT ′ ′ end_POSTSUPERSCRIPT ) ) end_ARG start_ARG roman_cosh ( italic_s / 2 ) end_ARG , end_CELL end_ROW(37)

which is a contradiction completing the proof.

Acknowledgements.

We thank Florent Balacheff, Maxime Fortier Bourque, Antonio Costa,Benson Farb, Svetlana Katok, Gabor Lippner, Marissa Loving, Curtis McMullen,Hugo Parlier, John Ratcliffe, and Chaitanya Tappu foruseful discussions and suggestions. This work was supported by NSF grantNos.IIS-1741355 andCCF-2311160.

References

Computing distances on Riemann surfaces (2024)

References

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