arXiv subjects

Suresh Parekh

Publications and source records attributed to Suresh Parekh.

4 recordsLinked to original sources

arXiv2026

Blowing star formation away in AGN hosts (BAH) -- V: The Feeding-Feedback Cycle in local AGNs as revealed by their stellar populations

We present a spatially resolved analysis of the stellar populations in the inner kiloparsec of NGC 3884, 3C 293, and CGCG 012-070. Using near-infrared spectroscopy, we reconstruct their star formation histories (SFHs) by comparing the M13, XSL, and FSPS stellar population synthesis models. The stellar light is dominated by intermediate-age to old populations (t >= 1 Gyr) with super-solar metallicities (Z >= 1 Z_sun). All models clearly indicate recent star formation (rejuvenation) in these AGN hosts, with young to intermediate-age populations contributing significantly in the nuclear regions. The SFHs from M13 and XSL broadly agree in showing coexisting old and young components, whereas FSPS favours a larger fraction of very young (t < 50 Myr) stars. Moreover, XSL- and FSPS-based SFHs are generally more irregular and "bumpy," while M13 yields smoother, more continuous SFHs. In NGC 3884 and 3C 293, stars with 0.2 < t <= 0.7 Gyr form a ring-like structure around the nucleus. The nuclear spectra further require non-stellar components: a featureless power-law continuum (FC) and hot dust emission (HD). In 3C 293, the FC component appears in two spatially separated regions, possibly indicating a dual active galactic nucleus, though a heavily reddened starburst origin for the secondary component cannot be excluded. Nearly all fits show a central drop in stellar metallicity, consistent with inflow of metal-poor gas that fuels recent accretion and AGN activity. Radial profiles show that HD and FC contributions decrease with radius, while younger stellar populations become more prominent outward. Together, these results support a feeding-feedback scenario in which gas inflows trigger circumnuclear star formation and, via stellar mass loss, help sustain ongoing AGN activity. .

astro-ph.GA↗

arXiv2024

Observational constraints using Bayesian statistics and Deep Learning in $f(Q)$ gravity

This study investigates the evolution of Friedmann-Robertson-Walker (FRW) cosmological models within the $f(Q)$ gravity framework, utilizing a specific $f(Q)$ formulation and a novel Hubble parameter $H(z)$ parameterization to probe the universe's accelerating expansion. A central aspect is the application of advanced machine learning techniques for cosmological parameter estimation, alongside comparisons with traditional Bayesian (MCMC) methods. We employ a hybrid Mixed Neural Network (MNN), which synergistically combines Artificial Neural Networks (ANNs) and Mixture Density Networks (MDNs), to enhance the accuracy and robustness of parameter constraints. This MNN architecture is integrated into the CoLFI (Cosmological Likelihood-Free Inference) framework. CoLFI facilitates likelihood-free inference, a significant methodological advancement that provides an efficient and robust alternative, particularly for complex models with computationally expensive or intractable likelihood functions. Training efficiency for the neural networks is optimized by generating data via hyperellipsoid sampling. The $f(Q)$ model, constrained using these diverse approaches, successfully describes a universe transitioning from an early decelerating phase to the current accelerated expansion, with a computed transition redshift of $z_t = 0.60$. The physical and kinematic properties of the model are discussed, underscoring the efficacy of the MNN-CoLFI methodology and its consistency with MCMC results, while highlighting its advantages for obtaining observational constraints in $f(Q)$ gravity.

gr-qc↗

arXiv2024

Constraining anisotropic universe under $f(R,T)$ theory of gravity

We try to find the possibility of a Bianchi V universe in the modified gravitational field theory of $f(R,T)$. We have considered a Lagrangian model in the connection between the trace of the energy-momentum tensor $T$ and the Ricci scalar $R$. In order to solve the field equations a power law for the scaling factor was also considered. To make a comparison of the model parameters with the observational data, we put constraints on the model under the datasets of the Hubble parameter, Baryon Acoustic Oscillations, Pantheon, joint datasets of Hubble parameter + Pantheon, and collective datasets of the Hubble parameter + Baryon Acoustic Oscillations + Pantheon. The outcomes for the Hubble parameter in the present epoch are reasonably acceptable, especially since our estimation of this $H_0$ is remarkably consistent with various recent Planck Collaboration studies that utilize the $\Lambda$-CDM model.

gr-qc↗

arXiv2023

A power law solution for FRLW Universe with observational constraints

This paper examines a power law solution under $f(R,T)$ gravity for an isotropic and homogeneous universe by considering its functional form as $f(R,T) = R + ξRT$, where $ξ$ is a positive constant. In $f(R,T)$ gravity, we have built the field equation for homogeneous and isotropic spacetime. The developed model's solution is $a = αt^β$. We have used the redshift in the range $0 \leq z \leq 1.965$ and obtained the model parameters $α$, $β$, $H_0$ by using the Markov Chain Monte Carlo (MCMC) method. The constrained values of the model parameter are as follows: $H_0 = 67.098^{+2.148}_{-1.792}$ km s$^{-1}$ Mpc$^{-1}$, $H_0 = 67.588^{+2.229}_{-2.170}$ km s$^{-1}$ Mpc$^{-1}$, $H_0 = 66.270^{+2.215}_{-2.181}$ km s$^{-1}$ Mpc$^{-1}$, $H_0 = 65.960^{+2.380}_{-1.834}$ km s$^{-1}$ Mpc$^{-1}$, $H_0 = 66.274^{+2.015}_{-1.864}$ km s$^{-1}$ Mpc$^{-1}$ which have been achieved by bounding the model with the Hubble parameter ($H(z)$) dataset, Baryon Acoustic Oscillations (BAO) dataset, Pantheon dataset, joint $H(z)$ + Pantheon dataset and collective $H(z)$ + BAO + Pantheon dataset, respectively. These computed $H_o$ observational values agree well with the outcomes from the Plank collaboration group. Through an analysis of the energy conditions' behaviour on our obtained solution, the model has been examined and analysed. Using the Om diagnostic as the state finder diagnostic tool and the jerk parameter, we have also investigated the model's validity. Our results show that, within a certain range of restrictions, the proposed model agrees with the observed signatures.

astro-ph.CO↗