papers

Publications (6)

astro-ph.CO2024

Improved analytical modeling of the non-linear power spectrum in modified gravity cosmologies

Suhani Gupta, Wojciech A. Hellwing, Maciej Bilicki

Reliable analytical modeling of the non-linear power spectrum (PS) of matter perturbations is among the chief pre-requisites for cosmological analyses from the largest sky surveys.…

astro-ph.CO2024

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…

astro-ph.CO2022

Universality of the halo mass function in modified gravity cosmologies

Suhani Gupta, Wojciech A. Hellwing, Maciej Bilicki +1

We study the halo mass function (HMF) in modified gravity (MG) models using a set of large -body simulations -- the ELEPHANT suite. We consider two popular beyond-general relati…

astro-ph.CO2021

Probing gravity with redshift-space distortions: effects of tracer bias and sample selection

Jorge Enrique García-Farieta, Wojciech A. Hellwing, Suhani Gupta +1

We investigate clustering properties of dark matter halos and galaxies to search for optimal statistics and scales where possible departures from general relativity (GR) could be f…

astro-ph.CO2025

Dynamics of pairwise motions in the fully non-linear regime in LCDM and Modified Gravity cosmologies

Mariana Jaber, Wojciech A. Hellwing, Jorge E. García-Farieta +2

In contrast to our understanding of density field tracers, the modelling of direct statistics pertaining to the cosmic velocity field remains open to significant opportunities for…

cs.AI2025

Personalized Artificial General Intelligence (AGI) via Neuroscience-Inspired Continuous Learning Systems

Rajeev Gupta, Suhani Gupta, Ronak Parikh +3

Artificial Intelligence has made remarkable advancements in recent years, primarily driven by increasingly large deep learning models. However, achieving true Artificial General In…