Related papers: exoALMA. VIII. Probabilistic Moment Maps and Data …
Density inhomogeneities are ubiquitous in space and astrophysical plasmas, in particular at contact boundaries between different media. They often correspond to regions that exhibits strong dynamics on a wide range of spatial and temporal…
Understanding the formation and evolution of the Universe is crucial for cosmological studies, and the line intensity mapping provides a powerful tool for this kind of study. We propose to make use of multipole moments of redshift-space…
Point pattern data often exhibit features such as abrupt changes, hotspots and spatially varying dependence in local intensity. Under a Poisson process framework, these correspond to discontinuities and nonstationarity in the underlying…
In the standard picture for low-mass star formation, a dense molecular cloud undergoes gravitational collapse to form a protostellar system consisting of a new central star, a circumstellar disk, and a surrounding envelope of remaining…
Turbulence is thought to be a key driver of the evolution of protoplanetary disks, regulating the mass accretion process, the transport of angular momentum, and the growth of dust particles. We intend to determine the magnitude of the…
The large quantity and high quality of modern radio and infrared line observations require efficient modeling techniques to infer physical and chemical parameters such as temperature, density, and molecular abundances. We present a computer…
Theoretical calculations are contributing a significantly higher proportion of data to contemporary spectroscopic databases, which have traditionally relied on experimental observations and semi-empirical models. It is now a common…
We present a high-resolution (2.5 au) multiband analysis of the protoplanetary disk around TW Hya using ALMA long baseline data at Bands 3, 4, 6, and 7. We aim to reconstruct a high-sensitivity millimeter continuum image and revisit the…
We introduce the Linearized Diffusion Map (LDM), a novel linear dimensionality reduction method constructed via a linear approximation of the diffusion-map kernel. LDM integrates the geometric intuition of diffusion-based nonlinear methods…
From the perspective of non-equilibrium statistical mechanics, modeling the velocity distribution of particles in non-equilibrium, steady-state plasmas presents a significant challenge. Under this context, a family of kappa distributions…
Accurately estimating data density is crucial for making informed decisions and modeling in various fields. This paper presents a novel nonparametric density estimation procedure that utilizes bivariate penalized spline smoothing over…
Observations of protoplanetary disks provide information on planet formation and the reasons for the diversity of planetary systems. The key to understanding planet formation is the study of dust evolution from small grains to pebbles.…
We study the problem of non-parametric Bayesian estimation of the intensity function of a Poisson point process. The observations are $n$ independent realisations of a Poisson point process on the interval $[0,T]$. We propose two related…
We consider the problem of making nonparametric inference in a class of multi-dimensional diffusions in divergence form, from low-frequency data. Statistical analysis in this setting is notoriously challenging due to the intractability of…
We develop nonparametric Bayesian modelling approaches for Poisson processes, using weighted combinations of structured beta densities to represent the point process intensity function. For a regular spatial domain, such as the unit square,…
A comprehensive new approach is presented for deriving probability densities of physical properties characterizing lens or source that constitute an observed galactic microlensing event. While previously encountered problems are overcome,…
In nonlinear dynamical systems with highly nonorthogonal linear eigenvectors, linear non-modal analysis is more useful than normal mode analysis in predicting turbulent properties. However, the non-trivial time evolution of non-modal…
This article develops a methodology allowing application of the complete machinery of particle-based inference methods upon the class of continuous-discrete State Space Models (CD-SSMs). Such models correspond to a latent continuous-time…
Many physical datasets are generated by collections of instruments that make measurements at regular time intervals. For such regular monitoring data, we extend the framework of half-spectral covariance functions to the case of…
With positive signals from multiple direct detection experiments it will, in principle, be possible to measure the mass and cross sections of weakly-interacting massive particle (WIMP) dark matter. Recent work has shown that, with a…