A limit field for orthogonal range searches in two-dimensional random point search trees

We consider the cost of general orthogonal range queries in random quadtrees. The cost of a given query is encoded into a (random) function of four variables which characterize the coordinates of two opposite corners of the query rectangle. We prove that, when suitably shifted and rescaled, the random cost function converges uniformly in probability towards a random field that is characterized as the unique solution to a distributional fixed-point equation. We also state similar results for $2$-d trees. Our results imply for instance that the worst case query satisfies the same asymptotic estimates as a typical query, and thereby resolve an old question of Chanzy, Devroye and Zamora-Cura [\emph{Acta Inf.}, 37:355--383, 2000]Comment: 24 pages, 8 figure

The dual tree of a recursive triangulation of the disk

In the recursive lamination of the disk, one tries to add chords one after another at random; a chord is kept and inserted if it does not intersect any of the previously inserted ones. Curien and Le Gall [Ann. Probab. 39 (2011) 2224-2270] have proved that the set of chords converges to a limit triangulation of the disk encoded by a continuous process $\mathscr{M}$. Based on a new approach resembling ideas from the so-called contraction method in function spaces, we prove that, when properly rescaled, the planar dual of the discrete lamination converges almost surely in the Gromov-Hausdorff sense to a limit real tree $\mathscr{T}$, which is encoded by $\mathscr{M}$. This confirms a conjecture of Curien and Le Gall.Comment: Published in at http://dx.doi.org/10.1214/13-AOP894 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

On martingale tail sums in affine two-color urn models with multiple drawings

In two recent works, Kuba and Mahmoud (arXiv:1503.090691 and arXiv:1509.09053) introduced the family of two-color affine balanced Polya urn schemes with multiple drawings. We show that, in large-index urns (urn index between $1/2$ and $1$) and triangular urns, the martingale tail sum for the number of balls of a given color admits both a Gaussian central limit theorem as well as a law of the iterated logarithm. The laws of the iterated logarithm are new even in the standard model when only one ball is drawn from the urn in each step (except for the classical Polya urn model). Finally, we prove that the martingale limits exhibit densities (bounded under suitable assumptions) and exponentially decaying tails. Applications are given in the context of node degrees in random linear recursive trees and random circuits.Comment: 17 page

On a functional contraction method

In den letzten zwanzig Jahren hat sich die Kontraktionsmethode als ein wesentlicher Zugang zu Problemen der Konvergenz in Verteilung von Folgen von Zufallsvariablen, die additiven Rekurrenzen genügen, herausgestellt. Dabei beschränkten sich ihre Anwendungen zunächst auf reellwertige Zufallsvariablen, in den letzten Jahren wurde die Methode allerdings auch für komplexere Wertebereiche, wie etwa Hilberträume entwickelt. Basierend auf der Klasse der Zolotarev-Metriken, die in den siebziger Jahren eingeführt wurden, entwickeln wir die Methode im Rahmen von Banachräumen und präzisieren sie in den Fällen von stetigen resp. cadlag Funktionen auf dem Einheitsintervall. Wir formulieren ausreichende Bedingungen an die unter Betrachtung stehende Folge und deren möglichen Grenzwert, welcher eine stochastische Fixpunktgleichung erfüllt, die es erlauben, in Anwendungen funktionale Grenzwertsätze zu beweisen. Im Weiteren präsentieren wir als Anwendung zunächst einen neuen Beweis vom klassischen Invarianzprinzip nach Donsker, der auf additiven Rekursionen beruht. Außerdem wenden wir die Methode zur Analyse der Komplexität von partiellen Suchproblemen in zweidimensionalen Quadrantenbäumen und 2-d Bäumen an. Diese grundlegenden Datenstrukturen werden seit ihrer Einführung in den siebziger Jahren viel studiert. Unsere Ergebnisse liefern Antworten auf Fragen, die seit den Pionierarbeiten von Flajolet et al. in den achtziger und neunziger Jahren auf diesem Gebiet unbeantwortet blieben. Wir erwarten, dass die von uns entwickelte funktionale Kontraktionsmethode in den nächsten Jahren zur Lösung weiterer Fragen des asymptotischen Verhaltens von Zufallsgrößen, die additive Rekursionen erfüllen, beitragen wird.Within the last twenty years, the contraction method has turned out to be a fruitful approach to distributional convergence of sequences of random variables which obey additive recurrences. It was mainly invented for applications in the real-valued framework; however, in recent years, more complex state spaces such as Hilbert spaces have been under consideration. Based upon the family of Zolotarev metrics which were introduced in the late seventies, we develop the method in the context of Banach spaces and work it out in detail in the case of continuous resp. cadlag functions on the unit interval. We formulate sufficient conditions for both the sequence under consideration and its possible limit which satisfies a stochastic fixed-point equation, that allow to deduce functional limit theorems in applications. As a first application we present a new and considerably short proof of the classical invariance principle due to Donsker. It is based on a recursive decomposition. Moreover, we apply the method in the analysis of the complexity of partial match queries in two-dimensional search trees such as quadtrees and 2-d trees. These important data structures have been under heavy investigation since their invention in the seventies. Our results give answers to problems that have been left open in the pioneering work of Flajolet et al. in the eighties and nineties. We expect that the functional contraction method will significantly contribute to solutions for similar problems involving additive recursions in the following years

On a functional contraction method

Methods for proving functional limit laws are developed for sequences of stochastic processes which allow a recursive distributional decomposition either in time or space. Our approach is an extension of the so-called contraction method to the space $\mathcal{C}[0,1]$ of continuous functions endowed with uniform topology and the space $\mathcal {D}[0,1]$ of c\`{a}dl\`{a}g functions with the Skorokhod topology. The contraction method originated from the probabilistic analysis of algorithms and random trees where characteristics satisfy natural distributional recurrences. It is based on stochastic fixed-point equations, where probability metrics can be used to obtain contraction properties and allow the application of Banach's fixed-point theorem. We develop the use of the Zolotarev metrics on the spaces $\mathcal{C}[0,1]$ and $\mathcal{D}[0,1]$ in this context. Applications are given, in particular, a short proof of Donsker's functional limit theorem is derived and recurrences arising in the probabilistic analysis of algorithms are discussed.Comment: Published at http://dx.doi.org/10.1214/14-AOP919 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

On martingale tail sums for the path length in random trees

For a martingale $(X_n)$ converging almost surely to a random variable $X$, the sequence $(X_n - X)$ is called martingale tail sum. Recently, Neininger [Random Structures Algorithms, 46 (2015), 346-361] proved a central limit theorem for the martingale tail sum of R{\'e}gnier's martingale for the path length in random binary search trees. Gr{\"u}bel and Kabluchko [to appear in Annals of Applied Probability, (2016), arXiv 1410.0469] gave an alternative proof also conjecturing a corresponding law of the iterated logarithm. We prove the central limit theorem with convergence of higher moments and the law of the iterated logarithm for a family of trees containing binary search trees, recursive trees and plane-oriented recursive trees.Comment: Results generalized to broader tree model; convergence of moments in the CL

On weighted depths in random binary search trees

Following the model introduced by Aguech, Lasmar and Mahmoud [Probab. Engrg. Inform. Sci. 21 (2007) 133-141], the weighted depth of a node in a labelled rooted tree is the sum of all labels on the path connecting the node to the root. We analyze weighted depths of nodes with given labels, the last inserted node, nodes ordered as visited by the depth first search process, the weighted path length and the weighted Wiener index in a random binary search tree. We establish three regimes of nodes depending on whether the second order behaviour of their weighted depths follows from fluctuations of the keys on the path, the depth of the nodes, or both. Finally, we investigate a random distribution function on the unit interval arising as scaling limit for weighted depths of nodes with at most one child

A limit process for partial match queries in random quadtrees and 22-d trees

We consider the problem of recovering items matching a partially specified pattern in multidimensional trees (quadtrees and $k$-d trees). We assume the traditional model where the data consist of independent and uniform points in the unit square. For this model, in a structure on $n$ points, it is known that the number of nodes $C_n(\xi )$ to visit in order to report the items matching a random query $\xi$, independent and uniformly distributed on $[0,1]$, satisfies $\mathbf {E}[{C_n(\xi )}]\sim\kappa n^{\beta}$, where $\kappa$ and $\beta$ are explicit constants. We develop an approach based on the analysis of the cost $C_n(s)$ of any fixed query $s\in[0,1]$, and give precise estimates for the variance and limit distribution of the cost $C_n(x)$. Our results permit us to describe a limit process for the costs $C_n(x)$ as $x$ varies in $[0,1]$; one of the consequences is that $\mathbf {E}[{\max_{x\in[0,1]}C_n(x)}]\sim \gamma n^{\beta}$; this settles a question of Devroye [Pers. Comm., 2000].Comment: Published in at http://dx.doi.org/10.1214/12-AAP912 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org). arXiv admin note: text overlap with arXiv:1107.223

The profile of binary search trees

Binärsuchbäume sind eine wichtige Datenstruktur, die in der Informatik vielfach Anwendung finden. Ihre Konstruktion ist deterministisch, zur Analyse ihrer Eigenschaften wird aber eine rein zufällige Eingabe zugrundegelegt. Viele Größe, wie z.B. Tiefe, Höhe und Pfadlänge werden seit Jahren viel untersucht. Als besonders interessant hat sich die Analyse des Profils, der Anzahl Knoten einer bestimmten Tiefe herausgestellt. In dieser Arbeit wird ein funktionaler Grenzwertsatz für das am Erwartungswert normierte Profil vorgestellt. Dazu werden unterschiedliche Zugänge gewählt, die hauptsächlich auf dem sogenannten Profil-Polynom beruhen. Zunächst wird ein klassischer Zugang mit Hilfe von Martingalen besprochen. Der diskrete Prozess wird dazu auf kanonische Weise in ein zeitstetiges Modell (Yule-Prozess) eingebettet. Ergebnisse im kontinuierlichen Prozess werden dann durch Stoppen auf den diskreten übertragen. Zudem wird ein neuerer Zugang vorgestellt, der auf der Kontraktionsmethode in Banachräumen unter Verwendung der Zolotarev-Metrik beruht.Binary search trees are an important data structure in Computer Science. Their construction is deterministic, for analyzing their typical behavior a random input is assumed. Many quantities like depth, height and path length have been studied for years. The analysis of the profile, the number of nodes on a certain level has turned out to be quite interesting. In this work a functional limit theorem for the profile, normalized by its expectation, is presented. Two different approaches, both based upon the so-called profile-polynomial, are presented. A classical approach based upon martingales is discussed. The discrete process is embedded in a time-continuous model (Yule-process) in a canonical way. Results for the continuous process are transferred to the discrete one by making use of stopping times. Secondly, a new approach based on to the contraction method in Banach spaces using the Zolotarev metric is presented