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Denoising diffusion probabilistic models (DDPMs) (Ho et al. 2020) have shown impressive results on image and waveform generation in continuous state spaces. Here, we introduce Discrete Denoising Diffusion Probabilistic Models (D3PMs),…
We investigate the potential and accuracy of clustering-based redshift estimation using the method proposed by M\'enard et al. (2013). This technique enables the inference of redshift distributions from measurements of the spatial…
A new numerical technique to identify the cosmic web is proposed. It is based on locating multi-stream flows, i.e. the places where the velocity field is multi-valued. The method is local in Eulerian space, simple and computaionally…
Lateral diffusion of molecules on surfaces plays a very important role in various biological processes, including lipid transport across the cell membrane, synaptic transmission and other phenomena such as exo- and endocytosis, signal…
The probability density function (PDF) of accelerations in turbulence is derived analytically with the help of the multifractal analysis based on generalized entropy, i.e., the Tsallis or the R\'{e}nyi entropy. It is shown that the derived…
Using a full implementation of resummed perturbation theory (PT) from a multi-point propagator expansion, we put forward new theoretical predictions for the two-point statistics of matter fluctuations in redshift space. The predictions…
We show the apparent redshift-space clustering of galaxies in redshift range of 0.2--0.4 provides surprisingly useful constraints on dark energy component in the universe, because of the right balance between the density of objects and the…
We analyze the flux power spectrum and its covariance using simulated Lyman alpha forests. We find that pseudo-hydro techniques are good approximations of hydrodynamical simulations at high redshift. However, the pseudo-hydro techniques…
We perform a comprehensive redshift-space distortion analysis based on cosmic voids in the large-scale distribution of galaxies observed with the Sloan Digital Sky Survey. To this end, we measure multipoles of the void-galaxy…
We present a model for one-dimensional (1D) matter power spectra in redshift space as estimated from data provided along individual lines of sight. We derive analytic expressions for these power spectra in the linear and nonlinear regimes,…
We present a new method for extracting the true 3-d velocity and density fields from the nonlinear redshift--space projected density field. The method is based on the nonlinear, nonlocal transformation of the density field. We assume a…
As the statistical power of galaxy weak lensing reaches percent level precision, large, realistic and robust simulations are required to calibrate observational systematics, especially given the increased importance of object blending as…
We re-examine the technique of determining the redshifts of galaxies from the ratio of the submillimeter-to-radio continuum flux densities based on a recently published catalog of 850~$\mu$m sources. We derived the expected variation of…
The analytical formalism to obtain the probability distribution functions (PDFs) of spherically-averaged cosmic densities and velocity divergences in the mildly non-linear regime is presented. A large-deviation principle is applied to those…
In probability density function (PDF) methods a transport equation is solved numerically to compute the time and space dependent probability distribution of several flow variables in a turbulent flow. The joint PDF of the velocity…
These lectures notes give an introduction to the fast developing area of research dealing with perturbative descriptions of the gravitational instability in an expanding universe. I just sketch the outlines of some proofs, and many…
Current studies of large-scale asymmetries (i.e. lopsidedness) in the stellar density distribution of disk galaxies have mainly focused on the local Universe. Recent observations have found a significant fraction (over 60%) of lopsided…
The tomographic AP method is so far the best method in separating the Alcock-Paczynski (AP) signal from the redshift space distortion (RSD) effects and deriving powerful constraints on cosmological parameters using the $\lesssim40h^{-1}\…
In this paper we introduce the \textsc{Deepz} deep learning photometric redshift (photo-$z$) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. \textsc{Deepz} reduces the $\sigma_{68}$ scatter…
We apply the scale-length method to several three dimensional samples of the Two degree Field Galaxy Redshift Survey. This method allows us to map in a quantitative and powerful way large scale structures in the distribution of galaxies…