相关论文: Parameter estimation from Ly$\alpha$ forest in Fou…
We present new simulations of Lyman-$\alpha$ (Ly$\alpha$) intensity maps that include Ly$\alpha$ radiative transfer in the intergalactic medium (IGM) and all significant sources of Ly$\alpha$ photons. The sources considered include…
The one-dimensional flux power spectrum (P1D) of the Lyman-$\alpha$ forest probes small-scale structure in the intergalactic medium (IGM) and is therefore sensitive to a variety of cosmological and astrophysical parameters. These include…
The Ly$\alpha$ forest transmission probability distribution function (PDF) is an established probe of the intergalactic medium (IGM) astrophysics, especially the temperature-density relationship of the IGM. We measure the transmission PDF…
Many different studies have shown that a wealth of cosmological information resides on small, non-linear scales. Unfortunately, there are two challenges to overcome to utilize that information. First, we do not know the optimal estimator…
A combined analysis of Cosmic Microwave Background (CMB) and Lyman-a forest data allows to constrain the matter power spectrum from small scales of about 1 Mpc/h all the way to the horizon scale. The long lever arm and complementarity…
Small-scale correlations measured in the Lyman-$\alpha$ (Ly$\alpha$) forest encode information about the intergalactic medium and the primordial matter power spectrum. In this article, we present and implement a simple method to measure the…
This study is devoted to the inference problem of extracting the nuclear matter properties directly from a set of mass-radius observations. We employ Bayesian neural networks (BNNs), which is a probabilistic model capable of estimating the…
Unlike the ordinary least-squares (OLS) estimator for the linear model, a ridge regression linear model provides coefficient estimates via shrinkage, usually with improved mean-square and prediction error. This is true especially when the…
We present LyMAS2, an improved version of the "Lyman-{\alpha} Mass Association Scheme" aiming at predicting the large-scale 3d clustering statistics of the Lyman-{\alpha} forest (Ly-{\alpha}) from moderate resolution simulations of the dark…
Correlations in the Lyman-$\alpha$ (Ly$\alpha$) forest, both as a function of line of sight separation (1D) and 3D separation, provide a unique window to the distribution of matter at redshifts not accessible by current galaxy surveys.…
Measurements of the Ly$\alpha$ forest based on large numbers of quasar spectra from sky surveys such as SDSS/eBOSS accurately probe the distribution of matter on small scales and thus provide important constraints on several ingredients of…
We investigate the capability of TianQin and LISA to reconstruct the model parameters in the Lagrangian of new physics scenarios that can generate an electroweak SFOPT. Taking the dimension-six Higgs operator extension of the Standard Model…
Hamiltonian learning (HL), enabling precise estimation of system parameters and underlying dynamics, plays a critical role in characterizing quantum systems. However, conventional HL methods face challenges in noise robustness and resource…
We introduce to astrophysics the threshold probability functions S_2, C_2, and D_2 first derived by \citet{torq+88}, which effectively samples the flux probability distribution (PDF) of the Lya forest at different spatial scales. These…
N:M structured pruning is essential for large language models (LLMs) because it can remove less important network weights and reduce the memory and computation requirements. Existing pruning methods mainly focus on designing metrics to…
We investigate the possibility of constraining primordial non-Gaussianity using the 3D bispectrum of Ly-alpha forest. The strength of the quadratic non-Gaussian correction to an otherwise Gaussian primordial gravitational field is assumed…
Observations of the Lyman-$\alpha$ (Ly$\alpha$) forest from spectroscopic surveys such as BOSS/eBOSS, or the ongoing DESI, offer a unique window to study the growth of structure on megaparsec scales. Interpretation of these measurements is…
As large language models (LLMs) are increasingly deployed in high-stakes and operational settings, evaluation strategies based solely on aggregate accuracy are often insucient to characterize system reliability. This study proposes a…
We propose a new method of analysis for the \lya forest, namely to measure the 1-point and 2-point joint probability distribution of the transmitted flux. The results for a sample of seven observed quasars and from two simulations of…
To improve predictive models for STEM applications, supplemental physics-based features computed from input parameters are introduced into single and multiple layers of a deep neural network (DNN). While many studies focus on informing DNNs…