Search Results for author:
Found 5 papers, 2 papers with code
Deep Learning for Line Intensity Mapping Observations: Information Extraction from Noisy Maps
The trained cGANs successfully reconstruct H{\alpha} emission from galaxies at a target redshift from observed, noisy intensity maps.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics
A semi-analytic model of pairwise velocity distribution between dark matter halos
At the length scales of $r=5-40\, [h^{-1}\, \mathrm{Mpc}]$, our model predicts the mean and dispersion of the pairwise velocity for dark matter halos with their masses of $10^{12. 5-13. 5} \, [h^{-1}M_{\odot}]$ at $0. 3 < z < 1$ with a 5%-level precision, while the model precision reaches a 20% level (mostly a 10% level) for other masses and redshifts explored in the simulations.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies
Noise reduction for weak lensing mass mapping: An application of generative adversarial networks to Subaru Hyper Suprime-Cam first-year data
We study the non-Gaussian information in denoised maps using one-point probability distribution functions (PDFs) and also perform matching analysis for positive peaks and massive clusters.
Denoising Weak Lensing Mass Maps with Deep Learning
Weak gravitational lensing is a powerful probe of the large-scale cosmic matter distribution.
Full-sky Gravitational Lensing Simulation for Large-area Galaxy Surveys and Cosmic Microwave Background Experiments
The data sets include full-sky convergence and shear maps from redshifts $z=0. 05$ to $5. 3$ at intervals of $150 \, h^{-1}{\rm Mpc}$ comoving radial distance (corresponding to a redshift interval of $\Delta z \simeq 0. 05$ at the nearby universe), enabling the construction of a mock shear catalog for an arbitrary source distribution up to $z=5. 3$.
Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology
