Related papers: Void Probability Function of Simulated Surveys of …
Using a sample of approximately 14,000 z>2.1 quasars observed in the first year of the Baryon Oscillation Spectroscopic Survey (BOSS), we measure the three-dimensional correlation function of absorption in the Lyman-alpha forest. The…
A significant fraction of the high-redshift galaxies show strong Lyman emission lines. For redshifts z>5, most known galaxies belong to this class. However, so far not much is known about the physical structure and nature of these objects.…
With a total integration time of 168 hours and a narrowband (NB) filter tuned to Lyman alpha at z = 8.8, the UltraVISTA survey has set out to find some of the most distant galaxies, on the verge of the Epoch of Reionization. Previous…
Higher-order statistics are a useful and complementary tool for measuring the clustering of galaxies, containing information on the non-gaussian evolution and morphology of large-scale structure in the Universe. In this work we present…
The aim of the VIRMOS VLT Deep Survey (VVDS) is to study of the evolution of galaxies, large scale structures and AGNs from a sample of more than 150,000 galaxies with measured redshifts in the range 0<z<5+. The VVDS will rely on the VIMOS…
Three-dimensional conformal field theories (CFTs) with slightly broken higher spin symmetry provide an interesting laboratory to study general properties of CFTs and their roles in the AdS/CFT correspondence. In this work we compute the…
Cosmic voids, the underdense regions of the Large Scale Structure (LSS), provide cosmological information highly complementary to that obtained from overdense regions. In this work, we investigate the constraining power of the void-shear…
Obtaining a reliable estimate of the joint probability mass function (PMF) of a set of random variables from observed data is a significant objective in statistical signal processing and machine learning. Modelling the joint PMF as a tensor…
We present a theoretical framework for calculating the volume filling fraction of galactic outflows in cosmic voids by integrating analytical models for the halo mass function (HMF), the halo occupation fraction, the stellar mass-halo mass…
Traditional neural networks are simple to train but they typically produce overconfident predictions. In contrast, Bayesian neural networks provide good uncertainty quantification but optimizing them is time consuming due to the large…
The standard $\rm \Lambda$CDM cosmological model predicts that a large amount of diffuse neutral hydrogen distributes in cosmic filaments, which could be mapped through Lyman-alpha (Ly$\alpha$) emission observations. We use the…
The Kalman filter is ubiquitous for state space models because of its desirable statistical properties, ease of implementation, and generally good performance. However, it can perform poorly in the presence of outliers, or measurements with…
Under the assumption of a void-filled Universe we investigate if the characteristic scale of voids can be determined from existing surveys. We use the Voronoi tessellation to create mock surveys and study the properties of the first…
The physical processes which make a galaxy a Lyman Alpha Emitter have been extensively studied for the past 25 years. However, the correlations between physical and morphological properties of galaxies and the strength of the Ly$\alpha$…
We consider the problem of reconstructing an unknown bounded function $u$ defined on a domain $X\subset \mathbb{R}^d$ from noiseless or noisy samples of $u$ at $n$ points $(x^i)_{i=1,\dots,n}$. We measure the reconstruction error in a norm…
Parity-violating physics in the early Universe can leave detectable traces in late-time observables. Whilst vector- and tensor-type parity-violation can be observed in the $B$-modes of the cosmic microwave background, scalar-type signatures…
New arguments supporting the reality of large-scale fluctuations in the density of the visible matter in deep galaxy surveys are presented. A statistical analysis of the radial distributions of galaxies in the COSMOS and HDF-N deep fields…
Federated learning (FL) has attracted significant attention for enabling collaborative learning without exposing private data. Among the primary variants of FL, vertical federated learning (VFL) addresses feature-partitioned data held by…
Variational Bayes (VB) has become a widely-used tool for Bayesian inference in statistics and machine learning. Nonetheless, the development of the existing VB algorithms is so far generally restricted to the case where the variational…
Radiotherapy is sensitive to executional and preparational uncertainties that propagate to uncertainty in dose and plan quality indicators like dose-volume histograms (DVHs). Current approaches to quantify and mitigate such uncertainties…