Related papers: Ly$\alpha$NNA: A Deep Learning Field-level Inferen…
Numerous surveys are underway or planned that aim to exploit the Lyman-alpha emission line as a probe of the distant universe. We investigate the reliability of such high-z Lya studies and the validity of the conclusions that are based upon…
Distilling underlying principles from data has historically driven scientific breakthroughs. However, conventional data-driven machine learning often produces complex models that lack interpretability and generalization due to insufficient…
The 3D distribution of matter at small scales encodes valuable information about the nature of dark matter and other fundamental physics. A prominent probe of such scales outside galaxies is the Lyman-alpha forest, which studies absorption…
We present a comprehensive analysis of high resolution hydrodynamic simulations in terms of Lyman-alpha and Lyman-beta one dimensional flux power spectra ($P_{\alpha\alpha}$ and $P_{\beta\beta}$). In particular, we focus on the behaviour…
We use the probability distribution function (PDF) of the lya forest flux at z=2-3, measured from high-resolution UVES/VLT data, and hydrodynamical simulations to obtain constraints on cosmological parameters and the thermal state of the…
We present methods for interpolating between the 1-D flux power spectrum of the Lyman-$\alpha$ forest, as output by cosmological hydrodynamic simulations. Interpolation is necessary for cosmological parameter estimation due to the limited…
We evaluate the performance of the Lyman-$\alpha$ forest weak gravitational lensing estimator of Metcalf et al. on forest data from hydrodynamic simulations and ray-traced simulated lensing potentials. We compare the results to those…
In this paper we present an efficient method for constraining both thermal and non-thermal Dark Matter (DM) scenarios with the Lyman-$\alpha$ forest, based on a simple and flexible parametrisation capable to reproduce the small scale…
In this work, we analyze the Lyman-$\alpha$ forest in cosmological hydrodynamical simulations of chameleon-type f(R) gravity with the goal to assess whether the impact of such models is detectable in absorption line statistics. We carry out…
We simulate the Lya forest in a standard CDM universe using a 2-level hierarchical grid code to evolve the dark and baryonic matter components self-consistently. We solve the time-dependent ionization equations for hydrogen and helium,…
We explore possibility of using the three dimensional bispectra of the Ly-alpha forest and the redshifted 21-cm signal from the post-reionization epoch to constrain primordial non-Gaussianity. Both these fields map out the large scale…
In this work we expand upon the Tomographic Absorption Reconstruction and Density Inference Scheme (TARDIS) in order to include multiple tracers while reconstructing matter density fields at Cosmic Noon (z ~ 2-3). In particular, we jointly…
The signature left in quasar spectra by the presence of neutral hydrogen in the Universe allows one to constrain the sum of the neutrino masses with improved sensitivity, with respect to laboratory experiments, and may shed a new light on…
Deep Neural Networks (DNNs) are powerful algorithms that have been proven capable of extracting non-Gaussian information from weak lensing (WL) data sets. Understanding which features in the data determine the output of these nested,…
We investigate Lyman-alpha forest flux statistics in mixed fuzzy dark matter (FDM) and cold dark matter (CDM) cosmologies using the Fluctuating Gunn-Peterson Approximation (FGPA) applied to hybrid Schr\"odinger-Poisson and N-body…
We present predictions for the one-point probability distribution and cumulants of the transmitted QSO flux in the high redshift Lyman-$\alpha$ Forest. We make use of the correlation between the Lyman-$\alpha$ optical depth and the…
In inference problems, we often have domain knowledge which allows us to define summary statistics that capture most of the information content in a dataset. In this paper, we present a hybrid approach, where such physics-based summaries…
We have developed two independent methods to measure the one-dimensional power spectrum of the transmitted flux in the Lyman-$\alpha$ forest. The first method is based on a Fourier transform, and the second on a maximum likelihood…
We investigate the potential of low-redshift Lyman alpha (Ly$\alpha$) forest for constraining active galactic nuclei (AGN) feedback models by analyzing the Illustris and IllustrisTNG simulation at z=0.1. These simulations are ideal for…
We study parameter estimation in Nonlinear Factor Analysis (NFA) where the generative model is parameterized by a deep neural network. Recent work has focused on learning such models using inference (or recognition) networks; we identify a…