A Tentative Classification of Bijective Polygonal Piecewise Isometries

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A Tentative Classification of Bijective PolygonalPiecewise IsometriesX. Bressaud a & G. Poggiaspalla ba Institut de Mathématiques de Luminy, Case 907, 163, avenue de Luminy, 13288 MarseilleCedex 9, Franceb Office B14 School of Mathematical Science, Queen Mary University of London, Mile EndRoad, E14NS London UKPublished online: 30 Jan 2011.

To cite this article: X. Bressaud & G. Poggiaspalla (2007) A Tentative Classification of Bijective Polygonal PiecewiseIsometries, Experimental Mathematics, 16:1, 77-99, DOI: 10.1080/10586458.2007.10128987

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A Tentative Classification of Bijective PolygonalPiecewise IsometriesX. Bressaud and G. Poggiaspalla

CONTENTS

1. Introduction2. Notation and Definitions3. Triangulation by Bisection and Combinatorial Types4. Types of Maps5. First Computations6. PerspectivesAcknowledgmentsReferences

2000 AMS Subject Classification: Primary 37E99

Keywords: Dynamical systems, piecewise isometries

We aim to give a classification of Euclidian bijective polygonalpiecewise isometries with a finite number of compact polygonalatoms. We rely on a specific type of triangulation process thatenables us to describe a notion of combinatorial type similarto its one-dimensional counterpart for interval exchange maps.Moreover, it is possible to handle all the possible piecewiseisometries, given two combinatorial types. We show that mostof the examples treated in the literature of piecewise isometriescan be retrieved by systematic computations. The computationsyield new examples with apparently interesting behavior, butthey still have to be studied in more detail. We also exhibit anew class of maps, the piecewise similarities, which fit nicelyin this framework and whose behavior is shown to be highlynontrivial.

1. INTRODUCTION

Piecewise isometries (PWIs) are simply defined objectsconsisting of a partition of a domain of Rd with an isom-etry attached to each piece. Such simple maps may yieldsophisticated dynamics though of zero entropy [Buzzi 01].Of particular interest is the case in which the map is bi-jective, i.e., the partition is mapped onto another parti-tion (perhaps up to the boundaries of the atoms). Inone dimension, we have the interval translation mapsand interval exchange maps (IEMs), which have been in-tensively studied [Boshernitzan and Kornfeld 95, Rauzy79], with heavy use of renormalization techniques. Withhigher-dimensional domains, the situation is much morecomplicated for several reasons.

First, there is obviously much more freedom in thechoice of the partitions than in the one-dimensional case.We will restrict our investigation to the two-dimensionalcases with polygonal partitions. Then the isometry groupis bigger, and in contrast to the one-dimensional case, wehave rotations. A translation of the torus is an easy ex-ample of a PWI of higher dimension and has been exten-sively studied. Still, this example does not involve anyrotations.

c© A K Peters, Ltd.1058-6458/2007 $ 0.50 per page

Experimental Mathematics 16:1, page 77

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78 Experimental Mathematics, Vol. 16 (2007), No. 1

To our knowledge, the first examples involving bothtranslations and rotations appeared in engineering prob-lems related to overflow in digital filters [Chua and Lin88]. Starting from these observations, Adler, Kitchens,and Tresser [Adler et al. 01] introduced a one-parameterfamily of PWIs of the rhombus. An interesting featureof these maps is the coexistence of numerous “periodicislands” and minimal dynamics. For a few values of theparameter they were able to exhibit self-similarity andhence to describe the dynamics.

For all other values, though, they provided more ques-tions than answers. Independently, Goetz and Bosher-nitzan tackled the case of two half-planes and devel-oped the fruitful idea of self-similarity in other examples(see [Goetz and Sammis 01]). Poggiaspalla and Goetz[Goetz and Poggiaspalla 04] constructed and studied yetanother family of examples (towers) and found partialself-similarity. PWIs also appeared naturally in a morearithmetic context after work by Vivaldi and Lowenstein[Lowenstein et al. 97, Lowenstein and Vivaldi 98, Koup-stov et al. 03] on discretized rotations.

One of the difficulties in understanding the phenomenaof importance is related to the lack of large interestingclasses and the relatively poor number of “typical” exam-ples. This is especially true for bijective PWIs. Indeed,even in the polygonal case, it is not easy to find bijectivePWIs. Whether, given a set of polygons, it is possibleto arrange them in two distinct ways to draw the samefigure (as in a tangram) is in itself a nice combinatorialproblem.

A first classification of PWIs was proposed by Ashwinand Fu [Ashwin and Fu 02] but there was no attemptat being systematic. We propose a systematic way todescribe all the PWIs with polygonal domains and parti-tions. PWIs are naturally embedded in the larger class ofpiecewise similarities (PWSs). To our knowledge, thosemaps have not been studied, although they are a possi-ble generalization of the so-called affine interval exchangemaps (see, for example, [Camelier and Gutierrez 97]). Weprovide an algorithmic and geometric description of theset of PWSs.

The point of view we have adopted mimics theroadmap followed for IEMs. We try to distinguish the“combinatorial” aspect and the “real-parameter” aspect.To be more specific, recall that an IEM is easily describedby the permutation of the intervals and the lengths of theintervals.

For any permutation, each set of lengths yields anIEM. This point of view is fruitful as soon as we dealwith renormalization. Induction on a well-chosen inter-

val yields a new IEM (i.e., a new permutation and a newset of lengths). The dynamics of this renormalizationare interesting from the combinatorial point of view (e.g.,Rauzy classes; see [Rauzy 79]) and more generally since itis closely related to generalizations of continued-fractionalgorithms.

In two dimensions, the first difficulty is to decide whatshould play the role of the “combinatorial type” (i.e., ofthe permutation). It is not a restriction to limit the anal-ysis to triangulations of a triangular domain. But still, itis not obvious how one is to decide what a combinatorialtype should be.

To overcome this difficulty, we introduce a specifictype of triangulation, namely, triangulations by bisec-tions (so-called nice triangulations). They are “nice” be-cause all bijective PWIs with polygonal domain and par-tition can be defined using such partitions (see Proposi-tion 3.3), and they prove relatively easy to manipulate.Each such partition is described by a set of combinatorialdata, which we call the combinatorial type, and a set ofcontinuous parameters. Notice that it is fairly simple toenumerate all the combinatorial types. It is thus possi-ble to describe by linear equations all the bijective PWSs,and thus recover all the PWIs compatible with a givenpair of partition types.

The paper will be structured as follows:In Section 2, we introduce the notation and definitions

used to manipulate partitions and PWI.In Section 3, we propose a framework using the idea

of triangulation by successive bisections. The idea is thefollowing. We start with an initial triangle with unspeci-fied angles. Then we choose one of its three vertices andcut the triangle from this vertex to the opposite side. Theconstruction itself is associated with a continuous (three-

z

x y

FIGURE 1. By splitting a triangle from a vertex, weare led to a system with three degrees of freedom: x,y, and z in the figure.

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Bressaud and Poggiaspalla: A Tentative Classification of Bijective Polygonal Piecewise Isometries 79

dimensional) family of parameters, namely the angles ofthe two triangles given by the splitting. These parame-ters are not all independent of one another. We have twodegrees of freedom for the triangle itself and one morefor the bisector; see Figure 1.

Since the two atoms of the new partition are triangles,the procedure can be iterated in each atom. Finally, atype of partition is described by a sequence (or a tree)of bisections. Roughly speaking, it is a way to organizea triangular partition. We give a formal definition andexplain how to make intuitive use of it through lists oftriangles. We also stress the fact that this object is nota partition of a triangle; it describes a continuous familyof partitions (for n triangles we have n+ 1 parameters).If most partitions are of only one type, it can happenthat a partition belongs to several types. An alterna-tive way to specify completely a partition of a given typeis to give the angles of all the triangles under consis-tency constraints. Indeed, to a type with n triangles wecan associate an (n+ 1)-dimensional simplex in R3n (cf.Lemma 3.8).

In Section 4, we consider two types of partition withthe same number of triangles and a combinatorial de-scription of how the two partitions should be sent oneonto the other, that is, which triangle to which trian-gle, and for each triangle, which vertex on which vertex.From that, we derive the linear system of equations thatthe angles must satisfy in order for the map to be a PWS.We investigate the form of the solutions and try to givehints for a rough classification.

We naturally distinguish PWIs among the PWSs, andit is simple to decide from the combinatorial data whetherthe solution will preserve orientation. Another importantfeature of a solution is whether it is isolated in the pa-rameter space. In this case, arithmetic properties arenatural to consider; we have rational angles. Notice thatconversely, if the angles of a partition are not rational,then the PWI is included in a continuous family (thisanswers a question formulated by A. Goetz). Finally, ifthe solution is not isolated, we stress the dimension ofthe simplex.

In Section 5, we illustrate this formalism with explicitcomputations for partitions with two and three trian-gles. Even for such low numbers of atoms, the numberof solutions is amazingly high, and a huge amount ofnontrivial behavior arises. In fact, our method appearsto be a valuable source of new examples. We decided(see Section 5.1) to do an exhaustive study of the two-triangle cases. The result is that nothing really surprisingarises. Then (Section 5.2) we selected some cases with

three triangles, among which appear “old friends” andnew examples. The analysis carried out in this section iscomputationally intensive and requires the use of a com-puter. We chose the computer algebra software Mathe-matica, release 5, to help us. A tool box of Mathematicafunctions was developed in order to handle most of theprocess. For the sake of conciseness, we will not includethe listings of the functions, but the interested readermay find the Mathematica notebook at [Bressaud andPoggiaspalla 06].

Finally, in Section 6, we give a few hints for furtherinvestigations.

2. NOTATION AND DEFINITIONS

We denote by R2 the Euclidean plane. Given three pointsa, b, and c, the segment [ab] is the convex hull of {a, b};the triangle [abc] is the convex hull of {a, b, c}. We denoteby (abc) the interior of [abc]. The boundary of the trian-gle [abc] is the set ∂[abc] = [abc]\ (abc) = [ab]∪ [bc]∪ [ca].

Definition 2.1. A polygonal domain (or polygon) P is acompact subset of R2 whose boundary is a finite union ofsegments. For simplicity, we will always assume that it issimply connected and that it is the closure of its interior.We will write (P ) to denote the interior of P .

Let P = (P1, . . . , Pn) be a finite collection of polygons.We say that it is an essential partition of the polygon Pif P =

⋃ni=1 Pi and for all i �= j, (Pi)∩ (Pj) = ∅. We say

that it is a triangulation if for all i, Pi is a triangle.As a consequence, the intersections Pi∩Pj ⊂ ∂Pi∩∂Pj

are finite unions of segments. We denote by Seg(P)the minimal list of segments such that

⋃s∈Seg(P) s =⋃n

i=1 ∂Pi. We denote by |P| the number of polygonsin the collection and by s(P) the number of segments inSeg(P).

Let P = (P1, . . . , Pn) be an essential partition of apolygon. If they have a segment in common, we can gluetwo elements Pi and Pj to obtain a new partition:

P = (P1, . . . , Pi−1, Pi+1, . . . , Pj−1, Pj+1, . . . , Pn, Pi ∪Pj).

If (Q1, . . . , Qm) is an essential partition of Pi,then we can cut Pi to obtain a new partition,(P1, . . . , Pi−1, Q1, . . . , Qm, Pi+1, . . . , Pn). Both oper-ations preserve the property of being an essentialpartition.

Definition 2.2. A piecewise isometry (respectively, simi-larity, affine map) of a polygon P is a map f from P to P

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such that there is an essential partition P = (P1, . . . , Pn)of P into polygons, called atoms, and a list (f1, . . . , fn)of isometries (similarities, affine maps) such that for alli = 1, . . . , n, the restriction of f to the interior of Pi isfi, i.e.,

f|(Pi) = fi.

Standard definitions of piecewise isometries (see, forexample, [Adler et al. 01, Goetz 98, Goetz and Poggia-spalla 04]) usually include the boundaries of the atoms.In the present work, we will not be interested in the be-havior of the map on the boundary segments. The dy-namics on the images of the singular set have shown veryinteresting behavior, though, but our aim is, at least asa starting point, to consider concepts that are as globalas possible in an attempt to classify the maps themselvesrather than to give a detailed study of each of them.

Definition 2.3. We say that a polygonal piecewise isom-etry (or similarity) is essentially bijective if the image ofthe initial partition is itself an essential partition.

We denote by S the set of all the essentially bijectivepolygonal piecewise similarities, and I the subset of allthe essentially bijective polygonal piecewise isometries.

Moreover, if for f ∈ S and i �= j, fi = fj and Pi ∩ Pj

contains a segment, we could glue Pi and Pj withoutchanging the map. In the following, we may or may notmake the identification, depending on the context.

The aim of this paper is to give an algorithmic way toclassify the elements of the set S. In order to do so, wewill switch to a formalism whereby all the polygons aretriangles, given by a specific triangulation scheme.

3. TRIANGULATION BY BISECTION ANDCOMBINATORIAL TYPES

3.1 Triangulation by Bisection

To tackle the problem of the classification of polygo-nal piecewise similarities in a computationally reasonableway, we consider only triangulations, and moreover a spe-cific type of triangulation.

Definition 3.1. A nice triangulation P of a triangle Tinto n triangles has the following property: There is asequence of triangulations (Pi)i=0,...,n such that P0 =(T ), Pn = P, and for all 0 ≤ i < n, Pi is obtained fromPi+1 by gluing two elements along a common side.

Notice that the point is that at each step, all the el-ements of the partition remain triangles. Two trianglesthat are glued in the sequence will sometimes be calledtwins in the sequel.

Definition 3.2. A sequence of triangulations (Pn, . . . ,P0)in which Pn is a nice triangulation is called a gluing pathor a gluing chain.

To build a nice triangulation, one can also follow thesteps of a gluing chain in reverse order, starting from theoriginal triangle (T ), each time cutting one of the trian-gles into two triangular pieces, i.e., along a bisector. Thereversed sequence (P0, . . .Pn) will be called a bisectionpath. Figure 2 shows some gluing paths if we start fromthe top partitions, and it shows bisection paths if we startfrom the bottom partitions. Figure 2 also shows that anice triangulation may have several gluing paths.

We call ST (respectively, IT ) the sets of polygonalpiecewise similarities (isometries) such that the initialpartitions and their images are nice triangulations in thesense given above.

Any polygonal partition obviously has a refinementthat is a nice triangulation. The delicate point in theproof of the following result is that we must find a re-finement of the partition that is a nice triangulation andwhose image is also a nice triangulation.

The following result ensures that we have no loss ofgenerality in considering nice triangulations.

Proposition 3.3. We have S = ST .

This result holds, provided that we naturally glue to-gether two contiguous atoms if the same map is definedon both.

Proof: Notice first that a polygon can always be includedin a triangle and that any partition can be triangulated.We will need the following lemma.

Lemma 3.4. For every family S of segments in a triangleT there is an essential partition by bisections (i.e., a nicetriangulation) P such that S ⊂ Seg(P).

Proof: We proceed by induction on the number of seg-ments. Given a segment, we can prolong it until we reachthe boundary of T . If it lands on a vertex, we are done.Otherwise, we have to draw a segment from the oppositevertex to the landing point of the prolonged segment andcover the latter.

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FIGURE 2. Unlike the first triangulation on the left, in the triangulation on the right, which illustrates the triangle list((1, 2, 4)(1, 4, 5)(1, 5, 3)), we see that we have two possible gluing paths to recover the initial triangle. Each gluing isdepicted in the figures as dashed lines.

Now let us suppose we have N + 1 segments and thatthe statement is true for N . Then, let s be one of theseN+1 segments. Either we can prolong s to reach a vertexof the triangle T or we cannot. If we can, then we areleft with two triangles containing at most N segments,and the induction applies.

If the prolonged segment lands on the point x0 on aside of T , then we split T by joining x0 to the oppositevertex. We are led to two triangles each containing atmost N + 1 segments. If both triangles contain fewerthan N + 1 segments, we are done.

Only the triangle containing s could have N + 1 seg-ments. If that is the case, we know that s can be con-tinued to reach a vertex of the triangle, and thus theabove argument applies, which completes the proof ofthe lemma.

We return to the proof of the proposition. Now weknow that any polygonal partition can be refined to be-come a nice triangulation. Thus, any polygonal piecewisesimilarity can be viewed as defined on a nice triangula-

tion, by cutting atoms and adding redundancy. But theimage of such a partition may not be nice.

Let P be the polygonal partition of a polygonalpiecewise similarity f and let Q be its image. Let P ′

be a refinement of P such that P ′ is nice; by the lemma,we can always find such a partition. Then the imageQ′ of P ′ is a triangular partition refining Q. It maynot be nice, but we can find a nice partition Q′′ refin-ing Q′.

Then the preimage P ′′ of the partition Q′′ is triangularand refines the nice partition P ′. Let P ′

i be an atom ofP ′; it is partitioned into triangles, and this subpartitionGi is in correspondence up to only one similarity fi witha subpartition of an atom of Q′.

This latter atom was partitioned when Q′′ was chosenin such a way that fi(Gi) is nice. Hence Gi is nice. Theargument holds for all possible Gi, and we conclude thatP ′′ is nice, since it is a refinement of a nice partition P ′

obtained by refining all the triangles in a nice way. Themap f extended on P ′′ remains essentially the same butmaps a nice triangulation onto a nice triangulation.

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Remark 3.5. Notice that it is possible to give a bound onthe number of triangles needed in the nice triangulationin terms of the number of segments needed to describethe initial partition.

3.2 Combinatorial Types

Given a gluing path now consider not only a specific par-tition given by this path but all the possible partitionsthat can be constructed with combinatorially equivalentpaths. From now on, all the triangles will be orientedcounterclockwise, and for the sake of clarity, we name(1, 2, 3) the vertices of the initial triangle. With no lossof generality, we can assume that the vertices 1 and 2are, respectively, the points (0, 0) and (1, 0) of the realplane, the point 3 remaining free in the upper half-plane.

Let us look at a simple example, the triangle labeled(1, 2, 3), bisected by a segment starting from the vertex 1and landing on the opposite side, thus creating a fourthvertex, which we call 4. Then, we choose to bisect thetriangle (1, 4, 3) with a segment starting at 4 and landingon the side (13). We would like to stress the fact thatthis description is “combinatorial.” We did not mentionthe continuous information needed actually to describe apartition of a triangle. In other words, there is a continu-ous family of partitions associated with this description.

In order to describe a particular one we would haveto specify the initial triangle (i.e., the position of thepoint labeled 3, or the angles at the points 1 and 2), theangle between the segments (12) and (14), and finally theangles between the segments (43) and (45).

Note that the list ((1, 2, 4)(1, 4, 5)(5, 4, 3)) provides allthe information needed to trace the gluing path of thetriangles (the underlines show the common sides):

(1, 2, 4), (1, 4, 5), (5, 4, 3)→ (1, 2, 4), (1, 4, 3),

(1, 2, 4), (4, 3, 1)→ (1, 2, 3).

The list thus corresponds to a continuous family of par-titions. Note also that we can choose a different set ofparameters, for instance the nine angles linked by a linearsystem of equations.

We will now formalize this notion. We want toget rid of the continuous parameters. We will thenwork with “combinatorial triangles,” which are merelylists of vertices. A bisection of a triangle (1, 2, 3) canbe described by a list of two triangles. If we call 4the “new” vertex, we have three cases, depending onwhether 4 belongs to (13), (12), or (23). The list willbe respectively ((2, 3, 4), (4, 1, 2)), ((3, 1, 4), (4, 2, 3)), or((1, 2, 4), (4, 3, 1)).

A bisection path of a partition of a triangle (1, 2, 3)corresponds to a growing list of triangles. At each stage,we have the names of the triangles in Pi, where the newvertex created at stage i is called i + 3. A sequence ofn+1 bisections provides a list of n triangles, the names ofthe vertices ranging from 1 to n+ 2. Given the final listof triangles, it is easy to recover the path by gluing thetwo triangles containing the vertex with highest index,and so on, as seen in the example above.

We will say that two bisections paths are combinato-rially the same if they produce the same sequence of lists(Pi)i=0,...,n, or equivalently, if they produce the same fi-nal list.

To a combinatorial bisection path yielding n trian-gles we associate a map t from An = {1, 2, . . . , 3n} ontoVn = {1, 2, 3, 4, . . . , n+ 2} that describes the final list oftriangles:((t(1), t(2), t(3)), . . . , (t(3n− 2), t(3n− 1), t(3n))

).

It will be convenient to identify a combinatorial bisectionpath with such a map. Notice that not all such mapscorrespond to a bisection path. A map will be calledadmissible if that is the case.

Remark 3.6. The number of bisection paths yielding n

triangles is bounded by 3n(n− 1)!. Indeed, at each step,the next bisection is determined by the choice of the tri-angle and of one of its vertices.

We will say that two bisection paths are equivalent ifthey correspond to the same partitions when the continu-ous parameters vary. More precisely, they are equivalentif for each partition obtained with the first path and afixed set of parameters, it is possible to choose the pa-rameters of the other one to obtain the same partition.

This equivalence relation, which we will denote by R,takes into account two technical points. Firstly, if duringthe sequences of bisections we get two nonoverlappingtriangles (T ′) and (T ′′), we can bisect them separately inany order. Different orders will lead to final lists with thesame structure: only the names of the vertices depend onthe order in which these bisections are done. Secondly,if a triangle is cut twice (or more) from the same vertex,then the order in which the splitting is done does notmatter. Nonetheless, it will change the names of the ver-tices and may also affect the order in which the trianglesare listed.

Definition 3.7. A combinatorial type of partition is anequivalence class (for R) of combinatorial bisection paths.

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FIGURE 3. The partition on the left can be given by any of the two combinatorial types on the right.

In τ we choose once for all a representative list map de-noted by tτ . We will denote by |τ | the number of trianglesdescribed by the list tτ .

If t is an admissible map corresponding to a bisectionpath of type τ , we may write t ∈ τ , but for conciseness,we may also call the map associated to any representa-tive of a combinatorial type and preferably the selectedrepresentative tτ a “partition of combinatorial type.”

Hence, a partition type may have several glu-ing paths. An easy example is given by the list((1, 2, 4)(1, 4, 5)(1, 5, 3)). We can choose to glue the twoupper triangles first and then the remaining one, or wecan glue the two lower triangles first. Both gluing pathsare valid and lead to the same type; see Figure 2.

It is also worth noticing that a partition may be givenby more than one combinatorial type, as shown in Fig-ure 3. (Figure 10 provides an exhaustive list of combina-torial types with three triangles.)

In the description of a combinatorial type through aformal list of triangles, the names of the vertices (except1, 2, and 3) and the order in which the triangles are listeddo not matter. It is not very difficult to check that givensuch a list it is possible to recover a bisection path. Ateach stage we glue two triangles that have two commonvertices, one of them being distinct from 1, 2, and 3 andappearing in no other triangle of the list. In the following,it will be convenient for us to associate to each type τa particular list of triangles written in the order givenby tτ .

3.3 Alternative Description

The number of combinatorial types with n triangles isbounded from above by the number of combinatorial bi-section paths, i.e., 3n(n− 1)!. To enumerate all the com-binatorial types, it is certainly more efficient to use thepoint of view described below, which will not, however,be needed in the sequel.

Let T be the set of finite planar rooted trees G withset of vertices V , set of edges E, and root r ∈ V . As arooted tree, G has no vertex of degree 2, and its root rhas degree more than 1. Call L ⊂ V the subset of leaves(i.e., vertices with degree 1) and set n = |L|. We say thatG is a labeled tree if it comes with a map that associatesa value in {1, 2, 3} to the root and a value in {−1,+1}to each vertex in V \ (L ∪ {r}).

We claim that there is a bijection between the combi-natorial types with n triangles and the labeled trees withn leaves. This representation is simply a way to avoidthe redundancy described by the equivalence relation in-troduced above.

However, we do not want to enter into the details here.Let us just say that, roughly speaking, the root representsthe triangle (1, 2, 3); the label of the root tells us fromwhich vertex of the triangle the first bisection is done.Each edge starting from the root goes to a vertex thatrepresents a triangle. There can be more than two edgeswhen the triangle is cut into more than two triangles fromthe same vertex.

Then starting from the triangle associated to a vertex,descending edges starting from this vertex describe how

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the triangle is cut. Notice that at each vertex except theroot we can decide to do the next bisection from onlytwo of the three vertices, since it is not allowed to usethe same vertex again. For the purposes of this paper, itis not necessary to develop this formalism any further.

To summarize, we have three different objects thatcan be considered as abstraction layers of an intuitiveconcept:

• We consider a nice triangulation of a triangle called(1, 2, 3) up to similarities. However, we decided, forthe sake of clarity, to assume that 1 and 2 are fixedand that 3 is in the upper half-plane.

• Then we consider a combinatorial type of the bi-section path generating the nice triangulation. Itis represented by a list map, which formalizes anequivalence up to a set of continuous parameters (forinstance, the angles).

• Finally, since a given partition can be described bydifferent bisection paths, we have another equiva-lence relation among the bisection paths, and a com-binatorial type is represented by one of the abovelists (or alternatively by a labeled tree).

3.4 Partitions in a Combinatorial Type

Since by the definition of a type, for a given combinato-rial type τ , the set of partitions following this type doesnot depend on the bisection path chosen, it can be pa-rameterized by the angles of the n = |τ | triangles. Thereare n triangles and hence 3n angles, under linear con-straints. Given a partition, we can consider the anglevector A ∈ ]0, π[3|τ |. Its coordinates are ordered accord-ing to the map t ∈ τ , since the order of the list providesan order on the vertices and hence on the angles. Thechoice of the order is in itself unimportant, but it must bemade once and for all before any further computations.

Given a list map t ∈ τ , we call A(τ) the subset of]0, π[3|τ | of the angles attained by all the partitions fol-lowing t. We have the following lemma:

Lemma 3.8. A(τ) is a convex subset of ]0, π[3|τ | of di-mension |τ |+ 1.

Proof: This proof is easily done by induction. We putn = |τ |. If we have only one triangle, we need two pa-rameters to describe it. Now suppose we have n trianglesand by the induction hypothesis n + 1 parameters. Toadd one more triangle, we have to split one of the existingones. Thus, we let all the n+ 1 parameters be fixed and

choose one triangle to bisect. When we cut a triangle,we have only one degree of freedom, which is the posi-tion of the landing point of the bisector. We then haven + 1 triangles and n + 2 parameters, which completesthe induction.

We now write all the equations that the angles have tosatisfy. First, we have the following consistency conditionfor each of the n triangles: For all j = 0, . . . , n− 1, if wecall α3j+k the angle at the vertex k in the triangle j, wehave

3∑

k=1

α3j+k = π, j ∈ {0, . . . , n− 1}. (3–1)

All these equations are clearly independent, since eachdeals with a separate set of angles. Moreover, each cre-ated vertex v lies on a side, and so the sum of the anglesaround it must be π:

∑

i:t(i)=v

αi = π, v ∈ {4, . . . , n+ 2}. (3–2)

The equations of this set are independent as well. Eachinvolves a separate set of two angles. If two angles are inan equation, then they cannot be in another one, since adifferent equation deals with a different point.

We express these conditions using matrices. Condition(3–1) is expressed by the (n+ 1)× 3n matrix C(n):

Ci,j(n) =

{1 if j = 3i− 2, 3i− 1, 3i,0 otherwise.

(3–3)

The (n−1)×3n matrix V (τ) will express condition (3–2):

Vi,j(τ) =

{1 if t(i) = j + 3, j ∈ {1, . . . , n− 1},0 otherwise.

(3–4)It is easy to see that no row of the matrix (3–3), which al-ways has three contiguous 1’s, can be expressed in termsof a combination of rows of the matrix (3–4). Indeed,each row of the latter contains two 1’s, and the matrixnever has two 1’s in the same column (that is, each angleis used only once). We thus have 2n − 1 independentequations. By the lemma, this is enough to describe thesystem.

We can write the constraints in the compact form

A > 0, CA = π1, and V A = π1.

In the following, we will need to ensure that the exte-rior triangle (1, 2, 3) remains unchanged by the PWS. If

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we call its angles (α, β, γ), then certainly

α =∑

i:t(i)=1

αi, β =∑

i:t(i)=2

αi, γ =∑

i:t(i)=3

αi. (3–5)

We introduce an additional matrix E giving two ofthese angles. Indeed, the consistency of the triangle(1, 2, 3) being already encoded in the matrix C, the thirdangle of (1, 2, 3) does not give any information. The ma-trix E is of dimension 2× 3n and is defined by

Ei,j(τ) =

{1 if t(i) = j, j ∈ {1, 2},0 otherwise.

Thus (αβ

)= EA.

Finally, we remark that taking any other t′ in the classτ would result only in permutations of the rows of thematrices.

A pair (τ,A), where τ is a combinatorial type andA ∈ A(τ), is all we need in order to determine a nicetriangulation of the triangle (1, 2, 3). The vertex 3 isdetermined by the angles EA. We will use the followingnotation.

Definition 3.9. We will denote by (τ,A) the partitionof the triangle (1, 2, 3), the vertices 1 and 2 being fixedand its angles determined by EA. The partition is con-structed by the bisection process described by τ .

4. TYPES OF MAPS

We want to enumerate the bijective piecewise similari-ties with a given number of triangles. We suppose thepartitions to be nice in the sense of Definition 3.1, andwe associate to each of them a combinatorial type. Apiecewise similarity maps each vertex of each triangle ofthe first partition to a vertex of a corresponding triangleof the target partition.

From the point of view of combinatorial types, themap is a permutation on the vertices. Not all possi-ble permutations are allowed, though the triangles them-selves can be permuted as well as the vertices inside atriangle. But a triple of vertices forming a triangle muststill correspond to a triangle after the permutation. Wewill say that a permutation Σ ∈ S3n is admissible if thereare (σ, s1, . . . , sn) ∈ Sn × Sn

3 such that Σ can be writtenin the form

Σ(3i+ k) = 3(σ(i)− 1) + si(k), 1 ≤ i ≤ n, 1 ≤ k ≤ 3.

We denote by Sn ⊂ S3n the subset of admissible permu-tations on 3n elements. If Σ ∈ Sn, we also denote by Σits 3n×3n permutation matrix. Notice that |Sn| = n!6n.

Given two combinatorial types τ and τ ′ with |τ | = |τ ′|,two angle vectors A and A′, and an admissible permu-tation Σ, we consider the piecewise affine map fΣ map-ping the triangles of (τ,A) onto the triangles of (τ ′, A′)in the order prescribed by Σ. Precisely, for t ∈ τ andt′ ∈ τ ′ we have for all 1 ≤ i ≤ n that the imageof the triangle (t(3i)t(3i + 1)t(3i + 2)) is the triangle(t′(Σ(3i))t′(Σ(3i+ 1))t′(Σ(3i+ 2)).

Remark 4.1. Notice that the identity permutation in S3n

may yield a nontrivial map if the types are distinct.

An affine map is a similarity if and only if it preservesthe angles of a nondegenerate triangle. Hence the mapfΣ is a PWS if and only if A′ = ΣA. According toSection 3, the triangles partitioned by (τ,A) and (τ ′, A′)are the same if and only if E(τ)A = E(τ ′)A′. It is thennatural to make the following definition.

Definition 4.2. For every integer n, all combinatorialtypes τ, τ ′ with |τ | = |τ ′| = n, and every admissiblepermutation Σ ∈ Sn, we denote by A(τ, τ ′,Σ) the set ofsolutions in A ∈ ]0, π[3n of the equations

E(τ)A = E(τ ′)ΣA,

C(n)A = C(n)ΣA = π, (4–1)

V (τ)A = V (τ ′)ΣA = π,

where E(τ), V (τ), C(n) are the matrices defined above.

We see that given τ , τ ′, and Σ, the angle vectorsA ∈ A(τ, τ ′,Σ) are such that A and ΣA describe twopartitions with similar triangles. It is then easy to findthe piecewise similarity corresponding to this transfor-mation.

Conversely, we can always consider any given piece-wise similarity f to be defined on nice triangulations; cf.Proposition 3.3. Both partitions, possibly up to a simi-larity, can be described by two combinatorial types τ andτ ′ and two angle vectors. As discussed above, the mapcorresponds to some permutations Σ of the angles. Thencertainly f is included in the set of PWSs given by thesolutions A(τ, τ ′,Σ). We shall also use the same notationA(τ, τ ′,Σ) to denote the set of the corresponding maps.We summarize this remark in the following proposition.

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4

1 2 1 2

4

3

4

21 4 2

33

3

FIGURE 4. The top plot shows the type of pair under consideration. The bottom plot shows the same type but up to acounterclockwise rotation of π/3 applied to both triangles. We recognize the swapped pair of Section 5.1.1.

Proposition 4.3. We have

S =⋃

τ,τ ′,Σ

A(τ, τ ′,Σ),

where τ and τ ′ are two combinatorial types with the samenumber of triangles and Σ ∈ S|τ |.

It can happen that two different pairs of types lead tothe same map (possibly up to a similarity). For instance,the top and bottom pairs of combinatorial types picturedin Figure 4 are “equivalent” and will give the same mapsup to a similarity.

We will say that two pairs (τ1, τ2) and (τ ′1, τ′2) are

equivalent if there exists a similarity S such that for allpartitions (P1, P2) and (P ′

1, P′2) following these types we

have(P1, P2) = (SP ′

1, SP′2).

These partitions are nondegenerate, i.e., all their atomshave nonempty interiors. This equivalence can be ex-pressed combinatorially in terms of permutations of thevertices of the initial triangles (1, 2, 3):

Definition 4.4. Two pairs (τ1, τ2) and (τ ′1, τ′2) are equiv-

alent if there exists σ ∈ S3 such that τ ′1 = τ1 ◦ σ andτ ′2 = τ2 ◦ σ, where σ(i) = σ(i) for i ≤ 3 and σ(i) = i

for i > 3.

We remark that the bijectivity of the PWSs impliesthat there is a symmetry between the pair (τ1, τ2) andthe pair (τ2, τ1). The inverse map of a similarity is asimilarity. More formally, A(τ1, τ2,Σ) = A(τ2, τ1,Σ−1).

We are now ready to enumerate the piecewise similar-ities. For every integer n, we can enumerate the com-binatorial types of partitions with n triangles using Sec-tion 3. Then for each pair of such combinatorial types(τ, τ ′) and each admissible permutation Σ we can solvethe linear system (4–1) to determine the angle vectorsin A(τ, τ ′,Σ). We call this set a solution. A solutionis then an intersection of two n-dimensional simplices.The intersection may be empty, leading to no solution atall, or it may be again a simplex. If it is nonempty,then (τ, τ ′,Σ) may be called the (combinatorial) typeof the corresponding PWS. For n triangles, the num-ber of possible types of PWSs is bounded from aboveby n!6n(3n(n − 1)!)2 = 54nn!(n − 1)!2. This bound is abit crude, but a better estimation would involve tediouscomputations unnecessary for our purpose.

Let us now mention a few relevant properties of thesesolutions.

Definition 4.5. For brevity, the dimension of a solutionwill be the dimension of the simplex A(τ, τ ′,Σ).

The dimension-zero solutions consist of only one pointand will often be called isolated in the sequel.

For such an isolated solution a = (α1, . . . , α3n) withn triangles, all the angles will clearly be rational multi-ples of π. Moreover, they have the same denominator upto possible simplifications with the numerator. In otherwords, all the denominators of the angles must be divi-sors of the same integer: There exists an integer q suchthat a ∈ ( 1

q Zπ)3n.

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x

xx

x

FIGURE 5. The only solution giving piecewise similarities encountered so far; the angles are (π/2 − x, x, π/2, π/2, π/2 −x, x), for 0 < x < π/2. The plots show four examples in the family with four increasing values of x. We note thatthe upper-right figure displays piecewise isometry, thus illustrating the fact that a simplicial solution can contain bothpiecewise similarities and piecewise isometries.

Since we deal only with maps of the Euclidian plane,we can use the complex numbers to express the verticesof the triangles and the maps themselves. All these quan-tities can be computed by performing operations in thenumber field Q(eiα1 , . . . , eiα3n). Since there exists a q

such that αi = piπ/q for every i, the number field isfinitely generated. Its dimension over Q is the degreeof the cyclotomic polynomial of order 2q, that is, φ(2q),where φ is the Euler function.

Definition 4.6. We define the degree of an isolated solu-tion (α1, . . . , α3n) to be the dimension of the cyclotomicnumber field Q(eiα1 , . . . , eiα3n).

A solution with dimension greater than zero will becalled a simplicial solution. If the dimension of the setof solutions is p, the solutions of the system can be ex-pressed as a function f of p parameters, defined on a do-main of Rp, and valued in R3n, whose coordinates havethe following form:

fi(x1, . . . , xp) = dπ +p∑

j=1

ajxj , (ai, d) ∈(

1q

Z

)2

,

for i ∈ 1, . . . , 3n and a unique integer q. The parametersxi range in intervals whose bounds are of the same formas above.

The following definition is also natural.

Definition 4.7. We say that a solution is direct if allthe associated transformations have positive determi-nant. We say that a solution is reverse if all the asso-

ciated transformations have negative determinant, andthat it is mixed otherwise.

Since the triangles in our lists are oriented, it is clearthat if the permutation of the vertices of a given tri-angle is even, then the resulting similarity will preserveorientation. Thus, if we limit the investigation to directpiecewise similarities, we have n!3n allowed permutationsinstead of n!6n, which can save us a significant amountof computational time.

Given an angle vector in a solution and the permuta-tion attached to it, we know all the angles of both parti-tions. Once we have constructed them, since we know bythe permutations which triangle in the first partition issupposed to be mapped onto which one of the second, wecan compute the transformations. They are similarities,since they preserve angles and can possibly be isometries.A solution is a PWI if and only if all the associated trans-formations on all its atoms have their determinants equalto 1 or −1. We cannot say that a simplicial solution hasa definite type. In general, it can contain both piece-wise similarities and piecewise isometries; see Figure 5.Notice that we still do not have a nice algorithmic wayto discriminate PWIs in a simplicial solution containingPWSs.

To avoid some redundancy in the solutions, we willintroduce the following definition:

Definition 4.8. We will say that a piecewise similarityis irreducible if given any pair of twin triangles, each ofthem bears a different similarity.

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1 2

3

4

1 2 2

3 3 3

2

4

4 41 1FIGURE 6. The two pairs depicted are equivalent up to a cyclic permutation of the vertices.

Simply stated, this means that the map has the min-imum number of atoms. It cannot be reduced by gluingtwo or more elements to a piecewise similarity on a nicetriangulation with fewer triangles.

To find all the piecewise similarities on n triangles, wewill first determine all possible combinatorial types onn atoms. There are finitely many of them, indeed fewerthan (n − 1)!3n−1; cf. Section 3. Then we pick all thepairs of combinatorial types and list all the solutions forall admissible permutations.

Clearly, the amount of computation grows dramati-cally with the number of triangles. In the following sec-tions we will perform an exhaustive enumeration for thecases with two triangles. We will also have a look at somethree-triangle cases.

5. FIRST COMPUTATIONS

5.1 Two Triangles

We start with the simplest case, in which we have onlytwo atoms. By the construction described above, givenour reference triangle (1, 2, 3) we have three possible bi-sections. For each of them, the new vertex 4 will land on adifferent side. Since we must specify a pair of partitions,we are led to nine possible pairs, many of them equiva-lent. For instance, the pairs of Figure 6 are clearly equiv-alent. In fact, each pair can be “rotated” three times, andthus we have only three cases to consider; cf. Figure 7.In the following, we will make an extensive explorationof them.

5.1.1 The “Tower” Case. The first case we will in-vestigate has a structure already encountered in otherreferences. A two-triangle case involving this bisectionscheme has been extensively studied in [Goetz 98], wherethe author shows one of the first examples of self-similardynamics encountered in the field of piecewise isometries.Generalizations to more than two triangles of this struc-ture in the form of “towers of triangles” have been consid-ered subsequently in [Goetz and Poggiaspalla 04]. Such

towers, originally found “by hand,” can be retrieved bysystematic computations.

In this section and the following, the phase space willbe a triangle labeled (1, 2, 3), with 1 the lower-left cor-ner. All the triangles will be oriented counterclockwise.The bisections of the triangles correspond to the lists((1, 2, 4)(1, 4, 3)) and ((1, 2, 4)(4, 2, 3)), as shown in Fig-ure 7 (top triangle).

For this model, the computer checked all admissi-ble permutations of the vertices between the two tri-angles. The solutions are in the six-dimensional opencube I = ]0, π[6, one dimension for each of the sixangles. Their order is based on the list of triangles;that is, for the list ((1, 2, 4), (1, 4, 3)), each component(a1, a2, a3, a4, a5, a6) ∈ I corresponds to the respectiveangles

(124), (412), (241), (143), (314), (431).

3

4

1 2

3

1

1

1

4

4

4 2

2

2

3

3

FIGURE 7. The three cases to consider.

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Solution Permutation Angles

1 (231645) (2π/5, π/5, 2π/5, 3π/5, π/5, π/5)

2 (312645) (3π/7, 2π/7, 2π/7, 5π/7, π/7, π/7)

TABLE 1. Isolated solutions for the “Tower” case.

We are thus led to solve the following equations underthe constraints of staying in I and for every allowed per-mutation matrix Σ:

⎛

⎝1 1 1 0 0 00 0 0 1 1 10 0 1 1 0 0

⎞

⎠

⎛

⎜⎜⎜⎜⎜⎜⎝

a1

a2

a3

a4

a5

a6

⎞

⎟⎟⎟⎟⎟⎟⎠=

⎛

⎝πππ

⎞

⎠

and

⎛

⎝1 1 1 0 0 00 0 0 1 1 10 0 1 0 1 0

⎞

⎠Σ

⎛

⎜⎜⎜⎜⎜⎜⎝

a1

a2

a3

a4

a5

a6

⎞

⎟⎟⎟⎟⎟⎟⎠=

⎛

⎝πππ

⎞

⎠ .

And moreover, to ensure that the exterior angles coin-cide,

(0 1 0 0 1 01 0 0 0 0 0

)

⎛

⎜⎜⎜⎜⎜⎜⎝

a1

a2

a3

a4

a5

a6

⎞

⎟⎟⎟⎟⎟⎟⎠

=(

0 1 0 0 0 01 0 0 1 0 0

)Σ

⎛

⎜⎜⎜⎜⎜⎜⎝

a1

a2

a3

a4

a5

a6

⎞

⎟⎟⎟⎟⎟⎟⎠.

There is a total of eight solutions, of which two are iso-lated and direct, and they correspond to two piecewiseisometries. The first one is of degree 4, and the secondone of degree 6. In the following we will list only the irre-ducible cases. The isolated solutions are listed in Table 1,while the simplicial solutions are listed in Table 2.

The first solution listed in Table 1 is well known. Itis the case extensively studied in [Goetz 98]. The second

and only other isolated solution has also been investi-gated by the same author and his collaborator in [Goetzand Sammis 01]. These solutions have proven very in-teresting and have intricate behavior. With regard tothe other solutions, we have conducted an automatedinvestigation, and their behaviors appear to be nearlytrivial. All consist of a reflection on one of the atomsand a rotation about the other one, leading to periodicor quasiperiodic motions. Thus, the only cases of inter-est in that configuration are the isolated solutions listedabove.

Let us recall that a first idea of the dynamics of sucha map is given by the mosaic of the map, i.e., the unionof the backward and forward images of the discontinuitylines (for more details about standard tools for the studyof the dynamics of PWIs, see, for example, [Poggiaspalla03]).

5.1.2 The “Symmetric” Case. In our attempt to listall the possible piecewise isometries, and even all possiblepiecewise similarities, we mentioned three different pairsof combinatorial types. This section deals with the sec-ond case in Figure 7, “symmetric pair” ((1, 2, 4)(1, 4, 3))and ((1, 2, 4)(1, 4, 3)). Following the same process as be-fore, we will compute all the possible solutions given byall the admissible permutations of the vertices. Thistime, there is a total of twenty-seven solutions, of whichfive are direct. We have six isolated solutions, all of thempiecewise isometries. The first four are of degree 2 andleave their atoms invariant; thus only the remaining so-lutions, of degree 4, will be listed in Table 3.

Solutions 3 and 4 do have nontrivial dynamics, butthey are topologically conjugate to the well-known dy-namics of the case explored by [Goetz 98] already en-countered in the previous section. See Figure 8 for themosaics of their cells.

There are many simplicial solutions, but most of them,Solutions 7 to 21, leave their atoms invariant. Also, So-lution 27 is not irreducible. Among the remaining so-lutions, Solutions 23 to 26 consist of a rotation and areflection, leading to only periodic or pseudoperiodic or-bits, that is, the orbits that densely fill a circle or a finitenumber of circles. The last case to consider, Solution22, is a family of piecewise similarities. Its partitions for

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Solution 4

Permutation (213564)

Angles(

π3− x3

3, x3,

2π3

− 2x33

, π3

+ 2x33

, π3− 4x3

3, π

3+ 2x3

3

)

Constraints 0 < x3 < π/4

Solution 5


Angles(

π3

+ x33

, x3,2π3

− 4x33

, π3

+ 4x33

, π3− 2x3

3, π

3− 2x3

3

)


Solution 6


Angles(

π2− x3

2, x3,

π2− x3

2, π

2+ x3

2, π

2− 3x3

2, x3

)


Solution 7

Permutation (312546)Angles (π − 2x3, x3, x3, π − x3, π − 3x3, − π + 4x3)

Constraints π/4 < x3 < π/3

TABLE 2. Simplicial solutions for the Section 5.1.1 case.

Solution Permutation Angles

3 (564231) (2π/5, π/5, 2π/5, π/5, 3π/5, π/5)

4 (645312) (3π/5, π/5, π/5, π/5, 2π/5, 2π/5)

TABLE 3. Isolated irreducible solutions for the Section 5.1.2 case.

FIGURE 8. Left: mosaic for Solution 3. Right: mosaic for Solution 4. Both are conjugate to Solution 1 of Section 5.1.1.

some value of the parameter are shown in Figure 5. Wesee that this family contains mostly piecewise similari-ties, in fact, in every case except for x = π/4. However,the dynamics of this solution appear to be trivial as well:They consist merely of the exchange of the two atoms.

To conclude, this pair of combinatorial type does notbring anything new, since the only nontrivial solutionsare conjugates of some of the solutions from the previoussection.

5.1.3 Third Case. The third case to consider, asshown in Figure 7 and given by the lists of triangles((1, 2, 4)(1, 4, 3)) and ((1, 4, 3)(4, 2, 3)), can be viewed asthe inverse of the “tower case” investigated above. Up toa rotation, this is clear, as can be seen in Figure 4.

Since all the solutions must be essentially bijective, weexpect the solutions in this section to be the inverses ofthe solutions of Section 5.1.1. This case thus requiresno further investigation, since it brings nothing new interms of dynamics.

FIGURE 9. Left: mosaic for Solution 1; Right: mosaicfor Solution 2.

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1 2 3 4 5

6

11

7

12

8

13

9

14

10

15

FIGURE 10. The 15 different combinatorial types with three triangles.

From all these computations, we can say that the onlynontrivial piecewise isometric dynamics on two trianglesare those to be found in Figure 9, both of which arealready known in the literature.

5.2 Three Triangles

While the number of cases and the number of solutionsin the two-triangle investigation remained relatively low,this is no longer the case with three triangles. First,we have 15 different combinatorial types with three tri-angles. They are shown in Figure 10. Then there are152 = 225 pairs. We can as above put an equivalencerelation on the pairs to avoid the cases that can be de-duced from others by a rotation or a flip. For instance,we have (1, 2) ∼ (6, 9) and (4, 3) ∼ (7, 10).

We are then led to 75 cases. Moreover, we ignore theswapping of combinatorial types inside a pair. Indeed,for example, the pair (1, 2) will lead to maps that arethe inverses of the maps found for (2, 1). This way, weeliminate 20 cases, and only 55 cases are left to consider;they are as follows:

(1, 1), (1, 6), (1, 7), (1, 8), (1, 9), (1, 10), (1, 11), (1, 12), (1, 13),

(1, 14), (1, 15), (2, 2), (2, 6), (2, 7), (2, 8), (2, 9), (2, 10), (2, 11),

(2, 12), (2, 13), (2, 14), (2, 15), (3, 3), (3, 6), (3, 7), (3, 8), (3, 9),

(3, 10), (3, 11), (3, 12), (3, 13), (3, 14), (3, 15), (4, 4), (4, 6),

(4, 7), (4, 8), (4, 9), (4, 10), (4, 11), (4, 12), (4, 13), (4, 14),

(4, 15), (5, 5), (5, 6), (5, 7), (5, 8), (5, 9), (5, 10), (5, 11), (5, 12),

(5, 13), (5, 14), (5, 15).

The 3089 solutions took about twenty minutes to com-pute on a 3-GHz desktop PC using the notebook Com-plete3TriLt (available as an electronic supplement [Bres-saud and Poggiaspalla 06]). The number of solutions fora given pair can vary greatly, from 9 up to 297. We have449 direct solutions and 810 isolated solutions. Table 4gives the number of isolated solutions by degree.

Degree 2 4 6 8 10 12

Number of Solutions 130 328 258 6 56 32

TABLE 4. Number of isolated solutions by degree.

Among these solutions we can spot some known cases.For example, the case studied in [Goetz and Poggiaspalla04] belongs (up to a rotation) to the set of solutions givenby the pair (3, 15). Similarly, the cases (in fact theirinverses) studied in [Adler et al. 01] belong to the set ofsolutions of the pair (2, 8). Since it is impossible to reviewsystematically such a vast number of cases in the presentpaper, we will focus on only two pairs, which offer a fairnumber of interesting solutions. The complete listing ofall the solutions with a preliminary analysis is availablein the electronic supplement [Bressaud and Poggiaspalla06] to this paper.

Although the choice we made may seem arbitrary, wehope that the great number of solutions it provides as wellas the variety of them makes it suitable for our illustrativepurpose.5.2.1 Tower Case Again. In this section, we willbe interested in the pair (3, 15). We have been

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FIGURE 11. The mosaics for Solutions 11, 13, and 34. We clearly see the attracting points in Solutions 11 and 13.Solution 34 has two attracting points and thus slightly more complicated dynamics.

FIGURE 12. The cases from [Goetz and Poggiaspalla04], found among the solutions given the pairs (3, 15).

working with the lists ((1, 5, 4)(5, 2, 4)(1, 4, 3)) and((4, 2, 5)(4, 5, 3)(3, 1, 4)). Among its 45 isolated and 86simplices of solutions, we find, up to a rotation, the casestudied in [Goetz and Poggiaspalla 04], displayed in Fig-ure 12.

As we said, there are 45 isolated solutions, and someof them have highly nontrivial behavior. Table 5 givestheir distribution by degree.

Only 27 of them are piecewise isometries, the rest be-ing piecewise similarities. These solutions display a fairvariety of behaviors. Some seem to have nearly trivialbehavior, that is, their mosaics of n-cells stabilize at acertain level to a finite partition. Many of them, how-ever, have highly nontrivial behavior. A detailed studyof these cases would be impossible here for obvious spacereasons and would also be beyond the scope of the pa-per. Instead, we will merely list the nontrivial cases anddisplay some of the most interesting of them.

Degree 2 4 6 8 10 12

Number of Solutions 2 26 15 0 1 1

TABLE 5. Behavior of the 45 isolated solutions by degree.

We split the list according to the degree of the solu-tions. We have two degree-2 solutions, both of whichhave finite mosaics. Among the 26 degree-4 solutions, 10have finite mosaics. Among the PWS solutions of degree4, six have a finite number of attracting points, as in theexamples of Figure 11, and yield uninteresting dynamics.Table 6 lists the remaining solutions. All these solutionshave nontrivial behaviors. Two of them are closely sim-ilar to the case studied in [Goetz 98]. In fact, a simpleinduction leads to the same map.

Looking at Table 6, we notice that an angle vectorcan appear several times, attached to a different permu-tation and thus leading to several different dynamics. Aninteresting example of this phenomenon is given by So-lutions 27 and 43, whose mosaics are both displayed inFigure 13. Solution 43 is especially interesting, since itdisplays unusual features. Indeed, its mosaics seem to bedense and, at least according to the initial conditions wetried, the dynamics seem to be minimal. Such amazingproperties would more than justify further investigationsin forthcoming works.

We have 15 degree-6 solutions, shown in Table 7. Allof them are PWSs, and seven of them lead to simpledynamics. Among the nontrivial cases, Solution 22 is(up to a rotation) precisely the case studied in [Goetzand Poggiaspalla 04]. Solution 20 is interesting becauseit is a case of a “fake” PWS. Indeed, as we shall see inthe next section, inducting on a well-chosen set yieldsa piecewise isometry, which is enough to describe thewhole dynamics. Figure 14 shows three nontrivial casesof piecewise similarities.

We only have two solutions of higher degree. Solutions23 and 25 have degree 10 and 12, respectively. They arepresented in Table 8. Both of them display highly non-trivial dynamics; cf. Figure 15. We will not present anysimplicial solutions here. Instead, after a remark on the

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Nb Angles Permutation Type Remark

9 (3π/5, π/5, π/5, π/5, 2π/5, 2π/5, 2π/5, π/5, 2π/5) (231798546) PWI conjugate[Goetz 98]10 (3π/5, π/5, π/5, π/5, 2π/5, 2π/5, 2π/5, π/5, 2π/5) (231798645) PWI 1 reflection21 (π/3, π/3, π/3, π/6, 2π/3, π/6, π/2, π/12, 5π/12) (645213987) PWI 2 reflection24 (2π/5, π/5, 2π/5, π/5, 3π/5, π/5, 2π/5, π/5, 2π/5) (645312789) PWI conjugate[Goetz 98]26 (π/3, π/3, π/3, π/6, 2π/3, π/6, π/2, π/12, 5π/12) (645321987) PWI 2 reflection27 (2π/5, π/5, 2π/5, π/5, 3π/5, π/5, 2π/5, π/5, 3π/5) (645798123) PWI 1 reflection28 (2π/5, π/5, 2π/5, π/5, 3π/5, π/5, 2π/5, π/5, 2π/5) (645798321) PWI conjugate[Goetz 98]30 (2π/5, π/5, 2π/5, π/5, 3π/5, π/5, 2π/5, π/5, 2π/5) (645978321) PWI 1 reflection31 (2π/5, π/10, π/2, π/5, 3π/5, π/5, 3π/10, 3π/10, 2π/5) (645987123) PWS 1 attracting point37 (2π/5, π/5, 2π/5, π/5, 3π/5, π/5, 2π/5, π/5, 2π/5) (879564321) PWI 2 reflection43 (2π/5, π/5, 2π/5, π/5, 3π/5, π/5, 2π/5, π/5, 2π/5) (897564321) PWI 1 reflection

TABLE 6. Table of degree-4 solutions.

Nb Angles Permutation Type Remark

14 (3π/7, 3π/7, π/7, π/7, 4π/7, 2π/7, 4π/7, π/7, 2π/7) (312798546) PWS17 (4π/7, π/7, 2π/7, 2π/7, 3π/7, 2π/7, 3π/7, π/7, 3π/7) (321978465) PWS20 (4π/7, π/7, 2π/7, 3π/7, 3π/7, π/7, 4π/7, π/7, 2π/7) (564798321) PWS conjugate PWI22 (2π/7, 2π/7, 3π/7, π/7, 5π/7, π/7, 3π/7, π/7, 3π/7) (645231789) PWI cf. [Goetz and Poggiaspalla 04]38 (4π/7, π/7, 2π/7, π/7, 3π/7, 3π/7, 2π/7, π/7, 4π/7) (879645321) PWS41 (3π/7, 3π/7, π/7, π/7, 4π/7, 2π/7, 4π/7, π/7, 2π/7) (897213546) PWS44 (7π/9, π/9, π/9, π/3, 2π/9, 4π/9, 4π/9, 2π/9, π/3) (978123456) PWS45 (3π/7, π/7, 3π/7, 2π/7, 4π/7, π/7, 3π/7, 2π/7, 2π/7) (987546123) PWS

TABLE 7. Degree-6 solutions.

FIGURE 13. The mosaics for Solutions 27 and 43. Though the angles are the same, different permutations yield differentdynamics.

behavior of a particular piecewise similarity solution inthe next section, we will present a simplicial family be-longing to a different pair of types and whose dynamicswill be strongly reminiscent of another well-known dy-namical family, namely the maps from [Adler et al. 01].

5.2.2 An Example of a “Fake” Piecewise Similarity.Each of the isolated solutions mentioned above wouldrequire a long and detailed study, which we have not

done. They would go far beyond the scope of this paper.However, in this section, we are going to present a pre-liminary study of a piecewise similarity, namely case 11,which is displayed in Figure 16. We call it T , defined onthe atoms P1, P2, P3.

The first interesting feature of this map is that in fact,though clearly nonisometric on two of its three atoms,it can be completely described in terms of a standardpiecewise isometry. Indeed, ρP3 , the first return map in

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Nb Angles Permutation Type

23 (2π/11, 2π/11, 7π/11, π/11, 9π/11, π/11, 3π/11, 3π/11, 5π/11) (645231978) PWI25 (6π/13, π/13, 6π/13, 3π/13, 7π/13, 3π/13, 4π/13, 4π/13, 5π/13) (645312978) PWI

TABLE 8. Solutions of degrees 10 and 12.

FIGURE 14. Two nontrivial piecewise similarities corresponding to the cases 20 and 44.

FIGURE 15. Mosaic of Solutions 23 and 25, of order 10 and 12 respectively.

the atom P3 in the bottom-right corner of Figure 16 (left),is a piecewise isometry, displayed in Figure 17. Moreover,the orbits of all the atoms of the return map cover thewhole phase space, except for a finite number of periodiccells, as displayed in Figure 17 (right). Thus, to describethe dynamics of the whole map, it is enough to describethe dynamics of the piecewise isometry ρP3 .

We already encountered such a feature in the exampledisplayed in Figure 5, but the map was too simple. In-deed, the return map was the identity map. We haven’tbeen able to establish a similar property for other piece-wise similarities.

Also based on angles that are multiples of π/7,this map exhibits some properties reminiscent of the

case from [Goetz and Poggiaspalla 04]. It displaysnonuniformly bounded return time. Inducting onthe lower-right-corner triangular set, highlighted inFigure 18, we are led to the map displayed at the topof the same figure. This map is reminiscent of the un-bounded return map encountered in [Goetz and Poggia-spalla 04].

5.2.3 A.K.T.-Like Maps. One of the first (and one ofthe few) examples of piecewise isometries that have beenrigorously studied and whose dynamics are fully under-stood is found in the work by R. Adler, B. Kitchens,and C. Tresser [Adler et al. 01] (and subsequently byB. Kahng in [Kahng 02]). They describe a continuousone-parameter family of maps consisting of a rotation on

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FIGURE 16. Solution 11. It is clear that this is not a piecewise isometry.

FIGURE 17. On the left, the first return map in the atom P3 of Solution 11 (Figure 16). On the right, the orbits of itsatoms; we can see that the phase space is completely tiled, up to a finite number of periodic cells.

FIGURE 18. The mosaic of Solution 20, with a blowup of the region on which the first return is made. On the lower-right-hand triangle, an induction gives a piecewise isometry with a self-similar partition, which has been already encounteredin [Goetz and Poggiaspalla 04].

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v

P

P

Pθ π−θ

θΟ

1

0

1

FIGURE 19. On the left, the rhombus has its sides identified to turn it into a torus. The map is then the rotation aboutthe origin with angle −θ. It translates into a piecewise isometry on atoms P−1, P0, and P1. On the right, use is madeof the symmetry of the dynamics to draw the so-called dart figure on which, essentially, all of the dynamics takes place.The small triangle is rotated by −θ about the origin of the rhombus, while the big one is rotated about its own centerby the angle π − θ.

4

43π

π

FIGURE 20. The map illustrated on the left is composed of two rotations. The top one, by π/4, has for fixed point thecenter of the rhombus, as described in the text. The bottom one has angle 3π/4 and fixed point the center of the bottomtriangle. The remaining triangle, below the dashed line, has only reflection defined on it. On the right, we recognize thewell-known mosaic of cells that was one of the first to be proven exactly self-similar.

a “tilted” two-dimensional torus, which is equivalent to apiecewise isometry on a rhombus; cf. Figure 19 (left). Itsdynamics are described when the rotation angle is equalto π/4, π/5, and 2π/5.

The case π/4 in particular has been extensively stud-ied. This map, and sometimes the whole family, is fre-quently referred to as the “A.K.T.” map (or, shuffling theletters, the “K.A.T” map, by analogy with the Arnold“cat” map).

Regardless of the angle, the dynamics are always sym-metric with respect to the center of the rhombus. Thus,using this symmetry we define a new map on a dart-shaped figure (cf. Figure 19 (right)). This shape can beconstructed with two bisections of a big triangle. Thecombinatorial type associated with the dart shape willhave three triangles; type 12 in Figure 10 is suitable.The type of the image partition will then be type 5 ofFigure 10.

Equations for the pair (12, 5) give a total of 96 solu-tions, 16 of which are isolated, and 80 simplicial. Wehave been working with the lists ((1, 5, 3)(1, 4, 5)(4, 2, 3))and ((1, 5, 3)(5, 4, 3)(1, 2, 4)). Among the isolated solu-tions, six are PWIs. Among the simplicial ones, Solution35 will particularly focus our interest:(

5π6− 2x

3,π

6− x

3, x,

2π3− 4x

3,π

6+

2x3,π

6+

2x3,

π

3− 2x

3,π

3+

4x3,π

3− 2x

3

), 0 < x <

π

2,

attached to the angle permutation (132456978). Whenx = π/8, the map given by the angles is a PWI and it isprecisely the case extensively studied in [Adler et al. 01]up to a flip. It is displayed in Figure 20.

Changing the angle of the rhombus gives birth to acontinuous family of piecewise isometries, some of whichhave been studied in this context [Adler et al. 01, Kahng

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FIGURE 21. From top to bottom and from left to right, 12 mosaics of cells for 12 increasing values of x, their shapes arefamiliar; they match closely those of [Adler et al. 01] when we change the angles of the rhombus.

02, Kahng 04a, Kahng 04b] or for closely related maps[Lowenstein and Vivaldi 98, Koupstov et al. 03]. Thisdegree of freedom corresponds to the parameter x. Fig-ure 21 shows 12 mosaics for 12 values of x, ranging fromπ/10 to π/3. These plots are quite familiar. Among themwe can recognize in particular at the second position ofthe second row, the case in which the rotation angle isbased on π/5, which has also been described in [Adler etal. 01] (and subsequently in [Kahng 04a]). The mosaicis not exactly the same, however, because of the extratriangle needed in our context to ensure the consistencyof the bisection process.

6. PERSPECTIVES

There remains a great deal of work if one is to obtain abetter understanding of the underlying geometry of theset of PWSs. Notice that this set, for n triangles, can beviewed as the union of “self-intersections” of an (n+ 1)-dimensional complex embedded in R3n.

By self-intersection we mean intersections of distinctfaces of the complex, which is, roughly speaking, theunion of the simplices corresponding to the types up toallowed permutations. Self-intersections correspond tonice partitions that can be rearranged to form anothernice partition (possibly of a different triangle).

Notice that if we take the closure of the faces, then thisset is connected. Moreover, the complex should have asomewhat recursive structure, since its shape for n + 1triangles is based on the shape for n triangles. However,up to now we have not been able to extract useful in-formation from these considerations. Nevertheless, theconcept is nice and could yield new ideas.

An important point for future research is to under-stand the “boundaries” of the simplices. In terms ofpartition types, a boundary corresponds to some anglesbeing zero or π. In particular, the number of trianglesin the type is decreasing when some parameters attain aboundary. If the maps in the simplex are all piecewiseisometries, we should still have piecewise isometries on

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the boundary. This is false when the maps are strictlypiecewise similarities.

It might be interesting as well to work with the lengthsof the sides of the triangles instead of their angles. Thedifficulty is that the equations linking the parameterswould then have polynomial form and hence would betrickier to deal with. The interest, though, would be todiscriminate directly the PWIs among the PWSs, espe-cially in the case that the solution is a simplex.

It seems possible to generalize this construction tomore than two dimensions. In the tetrahedron we candefine a notion corresponding to a partition by bisection.Given a nice triangulation (Pi)1≤i≤n of one face oppositea vertex indexed by k of the tetrahedron, consider thepartition of the tetrahedron with tetrahedra of base Pi

and vertices k. Since the elements of this partition aretetrahedra, it makes sense to iterate the process as doneabove.

Another direction for generalizations suggested by ourpoint of view is PWIs in non-Euclidian spaces. The hy-perbolic plane and the the sphere have nice isometrygroups, and the notion of partitions by bisection makessense. Some work in this direction is in progress andseems promising.

Our formalism also provides a reasonable context inwhich to ask whether a given behavior is typical for bi-jective PWIs. For instance, we have in mind the ques-tion raised by Buzzi and Hubert (during the confer-ence Porq’roll 2002) about the genericity of periodic is-lands among PWIs. Notice that from this point of view,Solution 43 of Section 5.2.1 is striking. If it is truethat it has no periodic island, as suggested by the mosaicof Figure 13, it would be highly interesting to understandwhy.

We have not said anything about the behavior of theboundaries of the triangles of the partitions, althoughthey carry an important part of the dynamics (accord-ing to the literature). In particular, it is not even clearwhether essentially bijective maps can be extended to theboundaries in a bijective way.

A real breakthrough would be to use this descriptionto induct in a systematic way. Notice that it is by nomeans clear that it is possible. Indeed, in general, if thepartition of T is nice, the partition of T 2 is not. However,we think that there is some hope to find classes of mapsfor which induction would behave well. If this idea wereto prove fruitful, the parameterization of the space ofPWSs would give dynamical information on the mapsthemselves.

ACKNOWLEDGMENTS

One of the authors (G.P.) was supported by the Queen MaryUniversity of London, EPSRC grant GR/562802/01. The au-thors want to thank J. Cassaigne and F. Vivaldi for theirsupport.

REFERENCES

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[Buzzi 01] J. Buzzi. “Piecewise Isometries Have Zero Topo-logical Entropy.” Erg. Th. Dyn. Sys. 21 (2001), 1371–1377.

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[Kahng 02] B. Kahng. “Dynamics of Symplectic PiecewiseAffine Elliptic Rotation Maps on Tori.” Erg. Th. Dyn. Sys.22 (2002), 483–505.

[Kahng 04a] Byungik Kahng. “The Unique Ergodic Measureof the Symmetric Piecewise Toral Isometry of Rotation An-gle θ = kπ/5 Is the Hausdorff Measure of Its Singular Set.”Dyn. Syst. 19:3 (2004), 245–264.

[Kahng 04b] Byungik Kahng. “Dynamics of KaleidoscopicMaps.” Adv. Math. 185:1 (2004), 178–205.

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[Koupstov et al. 03] K. L. Koupstov, J. H. Lowenstein, andF. Vivaldi. “Quadratic Rational Rotation of the Torus andDual Lattice Maps.” Preprint, 2003.

[Koupstov et al. 04] K. L. Koupstov, J. H. Lowenstein, andF. Vivaldi. “Recursive Tiling and Geometry of PiecewiseRotation by π/7.” Nonlinearity 17:2 (2004), 371–395.

[Lowenstein and Vivaldi 98] J. H. Lowenstein and F. Vivaldi.“Anomalous Transport in a Model of Hamiltonian Round-Off Errors.” Nonlinearity 11 (1998), 1321–1350.

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Xavier Bressaud, Institut de Mathematiques de Luminy, Case 907, 163, avenue de Luminy, 13288 Marseille Cedex 9, France([email protected])

Guillaume Poggiaspalla, Office B14 School of Mathematical Science, Queen Mary University of London, Mile End Road,E14NS London UK ([email protected])

Received September 5, 2005; accepted March 9, 2006.

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