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We measure photometric redshifts and spectral types for galaxies in the COSMOS survey. We use template fitting technique combined with luminosity function priors and with the option to simultaneously estimate dust extinction (i.e. E(B-V))…

We present an algorithm to self-consistently generate mock weak gravitational lensing convergence fields and galaxy distributions in redshift space. We generate three-dimensional cosmic density fields that follow a log-normal distribution,…

Cosmology and Nongalactic Astrophysics · Physics 2021-04-14 Ryu Makiya , Issha Kayo , Eiichiro Komatsu

The current weak lensing measurements of the large scale structure are mostly related to statistical study of background galaxy ellipticities. We consider a possibility to extend lensing studies with intrinsically unresolved sources and…

Astrophysics · Physics 2008-11-26 Asantha Cooray

Reconstructing astrophysical and cosmological fields from observations is challenging. It requires accounting for non-linear transformations, mixing of spatial structure, and noise. In contrast, forward simulators that map fields to…

Cosmology and Nongalactic Astrophysics · Physics 2023-11-01 Florian List , Noemi Anau Montel , Christoph Weniger

As an interpretation of the 750 GeV diphoton excesses recently reported by both ATLAS and CMS collaborations, we consider a simple extension of the Standard Model with a Dirac fermion dark matter where a singlet complex scalar field…

High Energy Physics - Phenomenology · Physics 2016-08-03 Soo-Min Choi , Yoo-Jin Kang , Hyun Min Lee

We study the prospects for three-dimensional mapping of the dark matter to high redshift through the shearing of faint galaxies images at multiple distances by gravitational lensing. Such maps could provide invaluable information on the…

Astrophysics · Physics 2009-08-12 Wayne Hu , Charles R. Keeton

We present DeepCHART (Deep learning for Cosmological Heterogeneity and Astrophysical Reconstruction via Tomography), a deep learning framework designed to reconstruct the three-dimensional dark matter density field at redshift $z=2.5$ from…

Cosmology and Nongalactic Astrophysics · Physics 2025-07-02 Soumak Maitra , Matteo Viel , Girish Kulkarni

We use the physics of ellipsoidal collapse to model the probability distribution function of the smoothed dark matter density field in real and redshift space. We provide a simple approximation to the exact collapse model which shows…

Astrophysics · Physics 2008-08-05 Tsz Yan Lam , Ravi K. Sheth

We provide a method for estimating the projected density distribution $\bar{n}_2w_p(r_p)$ of photometric objects around spectroscopic objects in a redshift survey. This quantity describes the distribution of Photometric sources with certain…

Astrophysics of Galaxies · Physics 2022-01-27 Kun Xu , Yun Zheng , Yipeng Jing

The mapping of dark matter clustering from real space to redshift space introduces the anisotropic property to the measured density power spectrum in redshift space, known as the redshift space distortion effect. The mapping formula is…

Cosmology and Nongalactic Astrophysics · Physics 2016-08-31 Yi Zheng , Yong-Seon Song

Cross-correlations between the galaxy number density in a lensing source sample and that in an overlapping spectroscopic sample can in principle be used to calibrate the lensing source redshift distribution. In this paper, we study in…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-16 Roland de Putter , Olivier Doré , Sudeep Das

We present a cosmic density field reconstruction method that augments the traditional reconstruction algorithms with a convolutional neural network (CNN). Following Shallue $\&$ Eisenstein (2022), the key component of our method is to use…

Cosmology and Nongalactic Astrophysics · Physics 2023-07-05 Xinyi Chen , Fangzhou Zhu , Sasha Gaines , Nikhil Padmanabhan

Degeneracies among parameters of the cosmological model are known to drastically limit the information contained in the matter distribution. In the first paper of this series, we shown that the cosmic web environments; namely the voids,…

Cosmology and Nongalactic Astrophysics · Physics 2023-06-21 Tony Bonnaire , Joseph Kuruvilla , Nabila Aghanim , Aurélien Decelle

An important issue in cosmology is reconstructing the effective dark energy equation of state directly from observations. With so few physically motivated models, future dark energy studies cannot only be based on constraining a dark energy…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-20 Chris Clarkson , Caroline Zunckel

We apply the measurement reduction technique to optimally reconstruct an object image from multiplexed ghost images (GI) while taking into account both GI correlations and object image sparsity. We show that one can reconstruct an image in…

Quantum Physics · Physics 2019-02-15 D. A. Balakin , A. V. Belinsky , A. S. Chirkin

I review the statistical techniques needed to extract information about physical parameters of galaxies from their observed spectra. This is important given the sheer size of the next generation of large galaxy redshift surveys. Going to…

Astrophysics · Physics 2007-05-23 Raul Jimenez

Using third-order perturbation theory, we derive a relation between the mean divergence of the peculiar velocity given density and the density itself. Our calculations assume Gaussian initial conditions and are valid for Gaussian filtering…

Astrophysics · Physics 2015-06-24 Michal Chodorowski , Ewa Lokas , Agnieszka Pollo , Adi Nusser

We study the evolution of cosmological perturbations, using a hybrid approximation scheme which upgrades the weak-field limit of Einstein's field equations to account for post-Newtonian scalar and vector metric perturbations and for…

Astrophysics · Physics 2007-05-23 Carmelita Carbone , Sabino Matarrese

Field-level inference has emerged as a promising framework to fully harness the cosmological information encoded in next-generation galaxy surveys. It involves performing Bayesian inference to jointly estimate the cosmological parameters…

Cosmology and Nongalactic Astrophysics · Physics 2025-12-19 Hugo Simon , François Lanusse , Arnaud de Mattia
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