arXiv subjects

Nicolas Juillet

Publications and source records attributed to Nicolas Juillet.

17 recordsLinked to original sources

arXiv2025

The football model, stochastic ordering and martingale transport

Tournaments are competitions between a number of teams, the outcome of which determines the relative strength or rank of each team. In many cases, the strength of a team in the tournament is given by a score. Perhaps, the most striking mathematical result on the tournament is Moon's theorem, which provides a necessary and sufficient condition for a feasible score sequence via majorization. To give a probabilistic interpretation of Moon's result, Aldous and Kolesnik introduced the football model, the existence of which gives a short proof of Moon's theorem. However, the existence proof of Aldous and Kolesnik is nonconstructive, leading to the question of a ``canonical'' construction of the football model. The purpose of this paper is to provide explicit constructions of the football model with an additional stochastic ordering constraint, which can be formulated by martingale transport. Two solutions are given: one is by solving an entropy optimization problem via Sinkhorn's algorithm, and the other relies on the idea of shadow couplings. It turns out that both constructions yield the property of strong stochastic transitivity. The nontransitive situations of the football model are also considered.

math.PR↗

arXiv2025

The Analytic Stockwell Transform and its Zeros

A recent original line of research in time--frequency analysis has shifted the interest in energy maxima toward zeros. Initially motivated by the intriguing uniform spread of the zeros of the spectrogram of white noise, it has led to fruitful theoretical developments combining probability theory, complex analysis and signal processing. In this vein, the present work proposes a characterization of the zeros of the Stockwell Transform of white noise, which consists in an hybrid time--frequency multiresolution representation. First of all, an analytic version of the Stockwell Transform is designed. Then, analyticity is leveraged to establish a connection with the hyperbolic Gaussian Analytic Function, whose zero set is invariant under the isometries of the Poincaré disk. Finally, the theoretical spatial statistics of the zeros of the hyperbolic Gaussian Analytic Function and the empirical statistics of the zeros the Analytic Stockwell Transform of white noise are compared through intensive Monte Carlo simulations, supporting the established connection. A publicly available documented Python toolbox accompanies this work.

eess.SP↗

arXiv2025

On absolutely continuous curves in the Wasserstein space over R and their representation by an optimal Markov process

Let $μ$ = ($μ$t)t$\in$R be a 1-parameter family of probability measures on R. In [11] we introduced its ``Markov-quantile''process: a process X= (Xt)t$\in$R that resembles as much as possible the quantile process attached to $μ$, among the Markov processesattached to $μ$, i.e. whose family of marginal laws is $μ$.In this article we look at the case where $μ$ is absolutely continuous in the Wasserstein space P2(R). Then X is solution of adynamical transport problem with marginals ($μ$t)t. It provides a Markov minimal Lagrangian probabilistic representative of $μ$, whichis moreover unique among the processes obtained as certain types of limits: limits for the finite dimensional topology of quantileprocesses where the past is made independent of the future conditionally on the present at finitely many times, or limits of processeslinearly interpolating $μ$.This raises new questions about ways to obtain Markov Lagrangian representatives, and to seek uniqueness properties in thisframework.

math.AP↗

arXiv2024

Taking Music Seriously: on the Dynamics of 'Mathemusical' Research with a Focus on Hexachordal Theorems

After presenting the general framework of 'mathemusical' dynamics, we focus on one music-theoretical problem concerning a special case of homometry theory applied to music composition, namely Milton Babbitt's hexachordal theorem. We briefly discuss some historical aspects of homometric structures and their ramifications in crystallography, spectral analysis and music composition via the construction of rhythmic canons tiling the integer line. We then present the probabilistic generalization of Babbitt's result we recently introduced in a paper entitled ''New hexachordal theorems in metric spaces with probability measure'' and illustrate the new approach with original constructions and examples.

math.PR↗

arXiv2022

Shadow martingales -- a stochastic mass transport approach to the peacock problem

Given a family of real probability measures $(μ_t)_{t\geq 0}$ increasing in convex order (a peacock) we describe a systematic method to create a martingale exactly fitting the marginals at any time. The key object for our approach is the obstructed shadow of a measure in a peacock, a generalization of the (obstructed) shadow introduced in \cite{BeJu16,NuStTa17}. As input data we take an increasing family of measures $(ν^α)_{α\in [0,1]}$ with $ν^α(\mathbb{R})=α$ that are submeasures of $μ_0$, called a parametrization of $μ_0$. Then, for any $α$ we define an evolution $(η^α_t)_{t\geq 0}$ of the measure $ν^α=η^α_0$ across our peacock by setting $η^α_t$ equal to the obstructed shadow of $ν^α$ in $(μ_s)_{s \in [0,t]}$. We identify conditions on the parametrization $(ν^α)_{α\in [0,1]}$ such that this construction leads to a unique martingale measure $π$, the shadow martingale, without any assumptions on the peacock. In the case of the left-curtain parametrization $(ν_{\text{lc}}^α)_{α\in [0,1]}$ we identify the shadow martingale as the unique solution to a continuous-time version of the martingale optimal transport problem. Furthermore, our method enriches the knowledge on the Predictable Representation Property (PRP) since any shadow martingale comes with a canonical Choquet representation in extremal Markov martingales.

math.PR↗

arXiv2021

Instability of Martingale optimal transport in dimension d $\ge$ 2

Stability of the value function and the set of minimizers w.r.t. the given data is a desirable feature of optimal transport problems. For the classical Kantorovich transport problem, stability is satisfied under mild assumptions and in general frameworks such as the one of Polish spaces. However, for the martingale transport problem several works based on different strategies established stability results for R only. We show that the restriction to dimension d = 1 is not accidental by presenting a sequence of marginal distributions on R 2 for which the martingale optimal transport problem is neither stable w.r.t. the value nor the set of minimizers. Our construction adapts to any dimension d $\ge$ 2. For d $\ge$ 2 it also provides a contradiction to the martingale Wasserstein inequality established by Jourdain and Margheriti in d = 1.

math.OC↗

arXiv2020

SubRiemanniann structures do not satisify Riemannian Brunn--Minkowski inequalities

We prove that no Brunn--Minkowski inequality from the Riemannian theories of curvature-dimension and optimal transportation can by satisfied by a strictly subRiemannian structure. Our proof relies on the same method as for the Heisenberg group together with new investigations by Agrachev, Barillari and Rizzi on ample normal geodesics of subRieman-nian structures and the geodesic dimension attached to them.

math.DG↗

arXiv2019

A Coupling Proof of Convex Ordering for Compound Distributions

In this paper, we give an alternative proof of the fact that, when compounding a nonnegative probability distribution, convex ordering between the distributions of the number of summands implies convex ordering between the resulting compound distributions. Although this is a classical textbook result in risk theory, our proof exhibits a concrete coupling between the compound distributions being compared, using the representation of one-period discrete martingale laws as a mixture of the corresponding extremal measures.

math.PR↗

arXiv2019

On a solution to the Monge transport problem on the real line arising from the strictly concave case

It is well-known that the optimal transport problem on the real line for the classical distance cost may not have a unique solution. In this paper we recover uniqueness by considering the transport problems where the costs are a power smaller than one of the distance, and letting this parameter tend to one. A complete construction of this solution that we call excursion coupling is given. This is reminiscent to the one in the convex case. It is also characterized as the solution of secondary transport problems. Moreover, a combinatoric/geometric characterization of the routes used for this transport plan is provided.

math.PR↗

arXiv2018

On A Mixture Of Brenier and Strassen Theorems

We give a characterization of optimal transport plans for a variant of the usual quadratic transport cost introduced in [33]. Optimal plans are composition of a deterministic transport given by the gradient of a continuously differentiable convex function followed by a martingale coupling. We also establish some connections with Caffarelli's contraction theorem [14].

math.PR↗

arXiv2018

Couplings in $L^p$ distance of two Brownian motions and their L{é}vy area

We study co-adapted couplings of (canonical hypoelliptic) diffu-sions on the (subRiemannian) Heisenberg group, that we call (Heisenberg) Brow-nian motions and are the joint laws of a planar Brownian motion with its L{é}vy area. We show that contrary to the situation observed on Riemannian manifolds of non-negative Ricci curvature, for any co-adapted coupling, two Heisenberg Brownian motions starting at two given points can not stay at bounded distance for all time t $\ge$ 0. Actually, we prove the stronger result that they can not stay bounded in L p for p $\ge$ 2. We also study the coupling by reflection, and show that it stays bounded in L p for 0 $\le$ p < 1. Finally, we explain how the results generalise to the Heisenberg groups of higher dimension

math.PR↗

arXiv2018

The Markov-quantile process attached to a family of Marginals

Let $μ$ = ($μ$t)t$\in$R be any 1-parameter family of probability measures on R. Its quantile process (Gt)t$\in$R : ]0, 1[ $\rightarrow$ RR, given by Gt($α$) = inf{x $\in$ R : $μ$t(]--$\infty$, x]) > $α$}, is not Markov in general. We modify it to build the Markov process we call "Markov-quantile".We first describe the discrete analogue: if ($μ$n)n$\in$Z is a family of probability measures on R, a Markov process Y = (Yn)n$\in$Z such that Law(Yn) = $μ$n is given by the data of its couplings from n to n + 1, i.e. Law((Yn, Yn+1)), and the process Y is the inhomogeneous Markov chain having those couplings as transitions. Therefore, there is a canonical Markov process with marginals $μ$n and as similar as possible to the quantile process: the chain whose transitions are the quantile couplings. We show that an analogous process exists for a continuous parameter t: there is a unique Markov process X with the measures $μ$t as marginals, and being a limit for the finite dimensional topology of quantile processes where the past is made independent of the future at finitely many times (many non-Markovian limits exist in general). The striking fact is that the construction requires no regularity for the family $μ$. We rely on order arguments, which seems to be completely new for the purpose.We also prove new results the Markov-quantile process yields in two contemporary frameworks:-- In case $μ$ is increasing for the stochastic order, X has increasing trajectories. This is an analogue of a result of Kellerer dealing with the convex order, peacocks and martingales. Modifiying Kellerer's proof, we also prove simultaneously his result and ours in this case.-- If $μ$ is absolutely continuous in Wasserstein space P2(R) then X is solution of a Benamou--Brenier transport problem with marginals $μ$t. Itprovides a Markov probabilistic representation of the continuity equation, unique in a certain sense.

math.PR↗

arXiv2016

Pliability, or the whitney extension theorem for curves in carnot groups

The Whitney extension theorem is a classical result in analysis giving a necessary and sufficient condition for a function defined on a closed set to be extendable to the whole space with a given class of regularity. It has been adapted to several settings, among which the one of Carnot groups. However, the target space has generally been assumed to be equal to R^d for some d $\ge$ 1. We focus here on the extendability problem for general ordered pairs (G\_1,G\_2) (with G\_2 non-Abelian). We analyze in particular the case G\_1 = R and characterize the groups G\_2 for which the Whitney extension property holds, in terms of a newly introduced notion that we call pliability. Pliability happens to be related to rigidity as defined by Bryant an Hsu. We exploit this relation in order to provide examples of non-pliable Carnot groups, that is, Carnot groups so that the Whitney extension property does not hold. We use geometric control theory results on the accessibility of control affine systems in order to test the pliability of a Carnot group. In particular, we recover some recent results by Le Donne, Speight and Zimmermann about Lusin approximation in Carnot groups of step 2 and Whitney extension in Heisenberg groups. We extend such results to all pliable Carnot groups, and we show that the latter may be of arbitrarily large step.

math.MG↗

arXiv2016

Shadow couplings

A classical result of Strassen asserts that given probabilities $μ, ν$ on the real line which are in convex order, there exists a \emph{martingale coupling} with these marginals, i.e.\ a random vector $(X_1,X_2)$ such that $X_1\sim μ, X_2\sim ν$ and $E[X_2|X_1]=X_1$. Remarkably, it is a non trivial problem to construct particular solutions to this problem. In this article, we introduce a family of such martingale couplings, each of which admits several characterizations in terms of optimality properties / geometry of the support set / representation through a Skorokhod embedding. As a particular element of this family we recover the (left-) curtain martingale transport, which has recently been studied \cite{BeJu16, HeTo13, CaLaMa14, BeHeTo15} and which can be viewed as a martingale analogue of the classical monotone rearrangement. As another canonical element of this family we identify a martingale coupling that resembles the usual \emph{product coupling} and appears as an optimizer in the general transport problem recently introduced by Gozlan et al. In addition, this coupling provides an explicit example of a Lipschitz-kernel, shedding new light on Kellerer's proof of the existence of Markov martingales with specified marginals.

math.PR↗

arXiv2016

Smoothing and non-smoothing via a flow tangent to the Ricci flow

We study a transformation of metric measure spaces introduced by Gigli and Mantegazza consisting in replacing the original distance with the length distance induced by the transport distance between heat kernel measures. We study the smoothing effect of this procedure in two important examples. Firstly, we show that in the case of some Euclidean cones, a singularity persists at the apex. Secondly, we generalize the construction to a sub-Riemannian manifold, namely the Heisenberg group, and show that it regularizes the space instantaneously to a smooth Riemannian manifold.

math.DG↗

arXiv2016

On a problem of optimal transport under marginal martingale constraints

The basic problem of optimal transportation consists in minimizing the expected costs $\mathbb {E}[c(X_1,X_2)]$ by varying the joint distribution $(X_1,X_2)$ where the marginal distributions of the random variables $X_1$ and $X_2$ are fixed. Inspired by recent applications in mathematical finance and connections with the peacock problem, we study this problem under the additional condition that $(X_i)_{i=1,2}$ is a martingale, that is, $\mathbb {E}[X_2|X_1]=X_1$. We establish a variational principle for this problem which enables us to determine optimal martingale transport plans for specific cost functions. In particular, we identify a martingale coupling that resembles the classic monotone quantile coupling in several respects. In analogy with the celebrated theorem of Brenier, the following behavior can be observed: If the initial distribution is continuous, then this "monotone martingale" is supported by the graphs of two functions $T_1,T_2:\mathbb {R}\to \mathbb {R}$.

math.PR↗

arXiv2014

Stability of the shadow projection and the left-curtain coupling

The (left-)curtain coupling, introduced by Beiglböck and the author is an extreme element of the set of "martingale" couplings between two real probability measures in convex order. It enjoys remarkable properties with respect to order relations and a minimisation problem inspired by the theory of optimal transport. An explicit representation and a number of further noteworthy attributes have recently been established by Henry-Labordère and Touzi. In the present paper we prove that the curtain coupling depends continuously on the prescribed marginals and quantify this with Lipschitz estimates. Moreover, we investigate the Markov composition of curtain couplings as a way of associating Markovian martingales with peacocks.

math.PR↗