相关论文: Predicting the Neutral Hydrogen Content of Galaxie…

A standard parametric maximum-likelihood technique is used to determine both the probability distribution over total HI mass $M_{\rm HI}$ and the regression of this quantity on the linear optical diameter $D_{\rm o}$ for field giant spirals…

Using a simple model of photodissociated atomic hydrogen on a galactic scale, it is possible to derive total hydrogen volume densities. These densities, obtained through a combination of atomic hydrogen, far-ultraviolet and metallicity…

We present a machine learning search for local, low-mass galaxies ($z < 0.02$ and $10^6 M_\odot < M_* < 10^9 M_\odot$) using the combined photometric data from the DESI Imaging Legacy Surveys and the WISE survey. We introduce the spectrally…

We describe a combined halo model to constrain the distribution of neutral hydrogen (HI) in the post-reionization universe. We combine constraints from the various probes of HI at different redshifts: the low-redshift 21-cm emission line…

Upcoming 21cm surveys will map the spatial distribution of cosmic neutral hydrogen (HI) over very large cosmological volumes. In order to maximize the scientific return of these surveys, accurate theoretical predictions are needed.…

Galaxies are theorized to form and co-evolve with their dark matter halos, such that their stellar masses and halo masses should be well-correlated. However, it is not known whether other observable galaxy features, such as their…

The cross-correlation of optical galaxies with the neutral hydrogen (HI) radiation intensity can enhance the signal-to-noise ratio (SNR) of the HI intensity measurement. In this paper, we investigate the cross-correlation of the galaxy…

Strong gravitational lensing provides some of the deepest views of the Universe, enabling studies of high-redshift galaxies only possible with next-generation facilities without the lensing phenomenon. To date, 21 cm radio emission from…

The HI gas content is a key ingredient in galaxy evolution, the study of which has been limited to moderate cosmological distances for individual galaxies due to the weakness of the hyperfine HI 21-cm transition. Here we present a new…

Context: We present the first Cosmological Parameter inferences from eROSITA X-ray observations of galaxy clusters using a Machine Learning algorithm. Methods: We train a Random Forest using mock catalogs of clusters from Magneticum…

This paper presents a comprehensive study of quasar photometric classification and redshift estimation using machine learning techniques. We cross-matched photometric data from the Dark Energy Survey Data Release 2 (DES DR2) with…

In this study, we present a sophisticated hybrid machine-learning framework that significantly improves the accuracy of predicting hydrogen storage capacities in metal hydrides. This is a critical challenge due to the scarcity of…

We present a random forest framework for predicting circumgalactic medium (CGM) physical conditions from quasar absorption line observables, trained on a sample of Voigt profile-fit synthetic absorbers from the Simba cosmological…

Here I briefly highlight our studies of the gas content, kinematics and star formation in nearby dwarf galaxies (D < 10 Mpc) based on the `Local Volume HI Survey' (LVHIS, Koribalski et al. 2018), which was conducted with the Australia…

Atomic hydrogen constitutes the gas reservoir from which molecular gas and star formation in galaxies emerges. However, the weakness of the line means it has been difficult to directly detect in all but the very local Universe. Here we…

In order to retrieve cosmological parameters from photometric surveys, we need to estimate the distribution of the photometric redshift in the sky with excellent accuracy. We use and apply three different machine learning methods to…

We study the clustering properties of the recently compiled HIPASS neutral hydrogen (HI) sources catalogue using the two point correlation function in redshift space. If the two point correlation is modelled as a power law,…

We examine the properties of atomic hydrogen (HI) associated with galaxies in the EAGLE simulations of galaxy formation. EAGLE's feedback parameters were calibrated to reproduce the stellar mass function and galaxy sizes at $z=0.1$, and we…

The observed high covering fractions of neutral hydrogen (HI) with column densities above $\sim 10^{17} \rm{cm}^{-2}$ around Lyman-Break Galaxies (LBGs) and bright quasars at redshifts z ~ 2-3 has been identified as a challenge for…

We introduce redMaGiC, an automated algorithm for selecting Luminous Red Galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC…