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Related papers: Multiplicative chaos of the Brownian loop soup

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We derive the non-Maxwellian distribution of self-gravitating $N$-body systems around the core by a model based on the random process with the additive and the multiplicative noise. The number density can be obtained through the steady…

Astrophysics of Galaxies · Physics 2011-08-09 Tohru Tashiro , Takayuki Tatekawa

A theory of intermittency differentiation is developed for a general class of Gaussian Multiplicative Chaos measures including the measure of Bacry and Muzy on the interval and circle as special cases. An exact, non-local functional…

Probability · Mathematics 2018-01-04 Dmitry Ostrovsky

In this paper we compute the level-crossing intensity for the density of the image of the Lebesgue measure under the action of a Brownian stochastic flow which is a smooth approximation of the Arratia flow and determine its asymptotic…

Probability · Mathematics 2017-04-04 V. V. Fomichov

This work investigates a fully discrete mixed finite element method for the stochastic Boussinesq system driven by multiplicative noise. The spatial discretization is performed using a standard mixed finite element method, while the…

Numerical Analysis · Mathematics 2025-12-25 Liet Vo

We introduce a four-parameter extended family of distributions related to the wrapped Cauchy distribution on the circle. The proposed family can be derived by altering the settings of a problem in Brownian motion which generates the wrapped…

Statistics Theory · Mathematics 2013-02-04 Shogo Kato , M. C. Jones

We show that the scaling limit of the random walk loop soup on suitable planar graphs is the Brownian loop soup, under a topology on multisets of unrooted, unparameterized, and macroscopic loops. The result holds assuming only convergence…

Probability · Mathematics 2026-03-16 Yihao Pang

We obtain a formula for the density of the free convolution of an arbitrary probability measure on the unit circle of $\mathbb{C}$ with the free multiplicative analogues of the normal distribution on the unit circle. This description relies…

Probability · Mathematics 2014-04-25 Ping Zhong

The influence theorem for product measures on the discrete space {0,1}^N may be extended to probability measures with the property of monotonicity (which is equivalent to `strong positive-association'). Corresponding results are valid for…

Probability · Mathematics 2007-05-23 B. T. Graham , G. R. Grimmett

The additive monotone (resp. boolean) unitary Brownian motion is a non-commutative stochastic process with monotone (resp. boolean) independent and stationary increments which are distributed according to the arcsine law (resp. Bernoulli…

Probability · Mathematics 2015-06-02 Tarek Hamdi

Accurate approximations of the change of system's output and its statistics with respect to the input are highly desired in computational dynamics. Ruelle's linear response theory provides breakthrough mathematical machinery for computing…

Dynamical Systems · Mathematics 2021-09-29 Adam A. Sliwiak , Qiqi Wang

We discuss random geometric structures obtained by percolation of Brownian loops, in relation to the Gaussian Free Field, and how their existence and properties depend on the dimension of the ambient space. We formulate a number of…

Probability · Mathematics 2020-02-27 Wendelin Werner

In this paper, we introduce a model of Brownian polymer in a continuous random environment. The asymptotic behavior of the partition function associated to this polymer measure is studied, and we are able to separate a weak and strong…

Probability · Mathematics 2007-05-23 Carles Rovira , amy Tindel

Constraints on cosmological parameters from large-scale structure have traditionally been obtained from two-point statistics. However, non-linear structure formation renders these statistics insufficient in capturing the full information…

Cosmology and Nongalactic Astrophysics · Physics 2017-11-22 Alex Hall , Alexander Mead

Carrollian amplitudes are scattering amplitudes of massless particles written in position space at null infinity. We study various aspects of Carrollian amplitudes for gauge theory and gravity at loop level using primarily the modified…

High Energy Physics - Theory · Physics 2026-05-15 Vijay Nenmeli , Bin Zhu

The added mass effect is the contribution to a Brownian particle's effective mass arising from the hydrodynamic flow its motion induces. For a spherical particle in an incompressible fluid, the added mass is half the fluid's displaced mass,…

Statistical Mechanics · Physics 2024-05-06 Long Him Cheung , Christopher Jarzynski

We investigate small deviation properties of Gaussian random fields in the space $L_q(\R^N,\mu)$ where $\mu$ is an arbitrary finite compactly supported Borel measure. Of special interest are hereby "thin" measures $\mu$, i.e., those which…

Probability · Mathematics 2007-05-23 Mikhail Lifshits , Werner Linde , Zhan Shi

For large classes of even-dimensional Riemannian manifolds $(M,g)$, we construct and analyze conformally invariant random fields. These centered Gaussian fields $h=h_g$, called co-polyharmonic Gaussian fields, are characterized by their…

Probability · Mathematics 2025-07-16 Lorenzo Dello Schiavo , Ronan Herry , Eva Kopfer , Karl-Theodor Sturm

Consider a log-correlated Gaussian field $\Gamma$ and its associated imaginary multiplicative chaos $:e^{i \beta \Gamma}:$ where $\beta$ is a real parameter. In [AJJ22], we showed that for any nonzero test function $f$, the law of $\int f…

Probability · Mathematics 2025-12-01 Juhan Aru , Antoine Jego , Janne Junnila

The problem of conditioning on the occupation field was investigated for the Brownian motion in 1998 independently by Aldous [4] and Warren and Yor [34] and recently for the loop soup at intensity $1/2$ by Werner [35], Sabot and Tarr\`es…

Probability · Mathematics 2023-06-23 Elie Aïdékon , Yueyun Hu , Zhan Shi

We present a novel approach to Bayesian inference and general Bayesian computation that is defined through a sequential decision loop. Our method defines a recursive partitioning of the sample space. It neither relies on gradients nor…

Machine Learning · Statistics 2021-06-10 Erik Bodin , Zhenwen Dai , Neill D. F. Campbell , Carl Henrik Ek