24 citations · 37 across the 5 of their papers we have counts for
5 papers
From Redshift to Real Space: Combining Linear Theory With Neural Networks
Edoardo Maragliano, Punyakoti Ganeshaiah Veena, Giulia Degni +1
Spectroscopic redshift surveys are key tools to trace the large-scale structure (LSS) of the Universe and test the CDM model. However, using redshifts as distance proxies introd…
Bending the web: exploring the impact of modified gravity on the density field and halo properties within the cosmic web
Suhani Gupta, Simon Pfeifer, Punyakoti Ganeshaiah Veena +1
This work investigates the impact of different Modified Gravity (MG) models on the large-scale structures (LSS) properties in relation to the cosmic web (CW), using N-body simulati…
Neural network reconstruction of density and velocity fields from the 2MASS Redshift Survey
Robert Lilow, Punyakoti Ganeshaiah Veena, Adi Nusser
We reconstruct the 3D matter density and peculiar velocity fields in the local Universe up to a distance of 200Mpc from the Two-Micron All-Sky Redshift Survey (2MRS), u…
Back to the present: A general treatment for the tidal field from the wake of dynamical friction
Rain Kipper, Peeter Tenjes, María Benito +6
Dynamical friction can be a valuable tool for inferring dark matter properties that are difficult to constrain by other methods. Most applications of dynamical friction calculation…
Large-scale density and velocity field reconstructions with neural networks
Punyakoti Ganeshaiah Veena, Robert Lilow, Adi Nusser
We assess a neural network (NN) method for reconstructing 3D cosmological density and velocity fields (target) from discrete and incomplete galaxy distributions (input). We employ…