Computer Algebra for Lattice Path Combinatorics Alin Bostan

Computer Algebra for Lattice path Combinatorics Alin Bostan To cite this version: Alin Bostan. Computer Algebra for Lattice path Combinatorics. Symbolic Computation [cs.SC]. Université Paris 13, 2017. tel-01660300 HAL Id: tel-01660300 https://hal.archives-ouvertes.fr/tel-01660300 Submitted on 12 Dec 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Université Paris 13 Laboratoire d’Informatique de Paris Nord Habilitation à Diriger des Recherches Spécialité : Sciences Calcul Formel pour la Combinatoire des Marches Soutenue le 15 décembre 2017 par Alin Bostan (Inria) devant le jury composé de : Mme. Frédérique Bassino Université Paris 13, Villetaneuse M. Olivier Bodini Université Paris 13, Villetaneuse Mme. Mireille Bousquet-Mélou CNRS, Université de Bordeaux Mme. Lucia Di Vizio CNRS, Université de Versailles M. Mark Giesbrecht Université de Waterloo, Canada (rapporteur) M. Florent Hivert Université Paris 11, Orsay M. Christian Krattenthaler Université de Vienne, Autriche (rapporteur) M. Gilles Villard CNRS, ENS de Lyon (rapporteur) COMPUTER ALGEBRA FOR LATTICE PATH COMBINATORICS ALIN BOSTAN∗ Abstract. Classifying lattice walks in restricted lattices is an important problem in enumerative combinatorics. Recently, computer algebra has been used to explore and to solve a number of diffi- cult questions related to lattice walks. We give an overview of recent results on structural properties and explicit formulas for generating functions of walks in the quarter plane, with an emphasis on the algorithmic methodology. Key words. Enumerative combinatorics, random walks in cones, lattice paths in the quarter plane, Gessel walks, generating functions, computer algebra, automated guessing, creative telescoping, diago- nals, binomial sums, algebraic functions, D-finite functions, hypergeometric functions, elliptic integrals. AMS subject classifications. Primary 05A10, 05A15, 05A16, 97N70, 33F10, 68W30, 14Q20; Secondary 33C05, 97N80, 13P15, 33C75, 12Y05, 13P05, 14Q20. This document is structured as follows. Section1 gives an overview of recent results obtained in lattice path combinatorics with the help of computer algebra, with a focus on the exact enumeration of walks confined to the quarter plane. Sections2 and3 then go into more details of two classes of fruitful algorithmic approaches: guess-and-prove and creative telescoping. 1. General presentation. 1.1. Prelude. Consider the following innocent-looking problem. A tandem-walk is a path in Z2 taking steps from f", , &g only. Show that, for any integer n ≥ 0, the following quantities are equal: (i) the number an of tandem-walks of length n (i.e., using n steps), confined to the upper half-plane Z × N, that start and end at (0, 0); (ii) the number bn of tandem-walks of length n confined to the quarter plane N2, that start at (0, 0) and finish on the diagonal x = y. For instance, for n = 3, this common value is a3 = b3 = 3, as shown below. (i) (ii) The problem establishes a rather surprising connection between tandem-walks in the lattice plane, submitted to two different kinds of constraints: the evolution domain of the walk, and its ending point. The domain constraint is weaker for the first family of walks, while the ending constraint is relaxed for the second family. It appears that this problem is far from being trivial. Several solutions exist, but none of them is elementary. One of the main aims of the present text is to ∗Inria, Université Paris-Saclay, 91120 Palaiseau, France ([email protected]). 2 COMPUTER ALGEBRA FOR LATTICE PATH COMBINATORICS 3 convince the reader that this problem (and many others with a similar flavor) can be solved with the help of a computer. More precisely, Computer Algebra tools, extensively described in the following sections, can be used to discover and to prove the following equalities (3n)! (1) a = b = , and am = bm = 0 if 3 does not divide m. 3n 3n n!2 · (n + 1)! It goes without saying that such a simple and beautiful expression cannot be an element of chance. As it will turn out, closed forms are quite rare for this kind of enumeration problems. Nevertheless, even in absence of nice formulas, the structural properties of the corresponding enumeration sequences reflect the symmetries of the step set and of the evolution domain. Equation (1) shows that the sequences (an) and (bn) are P-recursive, that is, they satisfy a linear recurrence with polyno- mial coefficients (in the index n). One of the messages that will emerge from the text is that this important property of the enumeration sequences is intimately related to the finiteness of a certain group, naturally attached to the step set f", , &g. 1.2. General context: lattice paths confined to cones. Let us put the previous problem into a more general framework. Let d ≥ 1 be an integer (dimension), let S d d be a finite subset (called step set, or model) of vectors in Z , and p0 2 Z (starting point). A S-path (or S-walk) of length n starting at p0 is a sequence (p0, p1,..., pn) d of elements in the lattice Z such that pi+1 − pi 2 S for all 0 ≤ i < n. Let C be a cone of Rd, that is a subset of Rd such that r · v 2 C for any v 2 C and r > 0, assumed to contain p0. We will be interested in the (exact and asymptotic) enumeration of S-walks confined to the cone C, and potentially subject to additional constraints. Example 1. Consider the model S = f(1, 0), (−1, 0), (1, −1), (−1, 1)g (called the Gouyou-Beauchamps model) in dimension d = 2, with starting point p0 = (0, 0) and 2 with cone C = R+ (the quarter plane). The picture below displays the step set of the model (on the left), and a S-walk of length n = 17 confined to C (on the right). (i, j) = (5, 1) The main typical questions in this context are then the following: • What is the number an of n-step S-walks contained in C and starting at p0? • For fixed i 2 C, what is the number an;i of such walks that end at i? • What is the nature of their generating functions n n i A(t) = ∑ ant and A(t; x) = ∑ an;it x ? n n,i As expected from the introductory example of tandem-walks, the answers to these questions are not simple, and heavily depend on the various parameters. The aim of this text is to provide a survey of recent results —notably classification results and closed form expressions— obtained using Computer Algebra. 4 ALIN BOSTAN 1.3. Why count walks in cones?. Lattice paths are fundamental objects in combinatorics. They have been studied at least since the second half of the 19th century, in connection with the ballot problem (see §1.4). Even earlier, embryonic occurrences (around 1650) are in Pascal’s and Huygens’ solutions of the so-called problem of di- vision of the stakes (or, problem of points), and of the gambler’s ruin problem, which motivated the beginnings of modern probability theory [170, 226, 157]. Despite these historically important examples, the enumeration of lattice walks has long re- mained part of what may be called recreational mathematics. It is only in the late 1960s that their study really became an independent field of research, at the cross- roads of pure and applied mathematics. Since then, various approaches have been progressively involved, separately or in interaction, in the study of lattice walks. These methods arise from various fields of classical mathematics (algebra, combinatorics, complex analysis, probability theory), and more recently from computer science. There are several reasons for the ubiquity of lattice walks, but the most solid one is that they encode several important classes of mathematical objects, in discrete mathematics (permutations, trees, words, urns, . ), in statistical physics (magnetism, polymers, . ), in probability theory (branching processes, games of chance, . ), in operations research (birth-death processes, queueing theory, . ). Therefore, many questions from all these various fields can be reduced to solving lattice path problems. For more motivations, the reader is referred to the introduc- tion of [26]. Nowadays, several books are entirely devoted to lattice paths and their applications [355, 312, 315, 160, 146, 384, 180, 388, 47, 284, 44], and an international conference titled Lattice path combinatorics and applications is entirely devoted to this field. We recommend Humphreys’ article [237] for a brief review of the history of lattice path enumeration and for a survey of the recent evolution of the field. Also, Krattenthaler’s recent survey [269] is an excellent overview of various results and methods in lattice path enumeration. 1.4. The ballot problem and the reflection principle. As mentioned before, the enumeration of lattice walks is an old topic. We want to illustrate this using Bertrand’s ballot problem [36, 10]. The aim is not only to provide the flavor of a nice piece of combinatorial reasoning, but especially to introduce the so-called reflection principle, seemingly invented by Aebly and Mirimanoff [5, 306], which contains the roots of a systematic method for lattice walks, to be presented later, and based on the notion of group of a walk, see §1.18. Bertrand’s problem is the following: Suppose that two candidates A and B are running in an election.

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