arXiv subjects

Nisha Rani

Publications and source records attributed to Nisha Rani.

9 recordsLinked to original sources

arXiv2026

Testing $f(Q)$ Gravity with DESI DR2 and Strong-Lensing Time Delays

Symmetric teleparallel gravity provides an alternative description of gravitation in which non-metricity replaces curvature and torsion. Its extension through $f(Q)$ gravity offers a different geometric description of the late-time expansion of the Universe and its accelerated phase. In this work, we investigate two $f(Q)$ models, a normalized power-law model and a square-root exponential model, and test their ability to describe the late-time expansion history. We constrain the model parameters through Markov chain Monte Carlo analyses using Cosmic Chronometer measurements, DESI DR2 baryon acoustic oscillations, strong-lensing time-delay observations, and three Type Ia supernova compilations, Pantheon$^+$, Union 3.0, and DES Y5. We compare both models with the flat $\Lambda$CDM model using the minimum $\chi^2$, Akaike information criterion, and Bayesian information criterion. The square-root exponential model provides a better statistical fit than $\Lambda$CDM for the combinations of Cosmic Chronometer, DESI DR2, and strong-lensing time-delay data with Pantheon$^+$ and Union 3.0, with improvements in both the goodness of fit and information criteria. The normalized power-law model remains statistically competitive with $\Lambda$CDM for the supernova-inclusive combinations, although the information criteria do not favor its additional parameter. We also determine the transition redshift from cosmic deceleration to acceleration for both models, obtaining consistent values across the different dataset combinations. The transition redshifts agree with observational estimates of the cosmic acceleration epoch. Overall, our results support $f(Q)$ gravity as a viable alternative to $\Lambda$CDM for explaining the late-time accelerated expansion of the Universe without requiring a cosmological constant.

gr-qc↗

arXiv2026

Revisiting 2D and 3D Dainotti Correlations for GRBs Using Bayesian Neural Networks

Gamma-ray bursts (GRBs) are promising cosmological probes, but their use as standard candles is limited by the circularity problem, necessitating model-independent calibration of GRB luminosity correlations. We revisit the two-dimensional (2D) and three-dimensional (3D) Dainotti correlations using Bayesian Neural Networks (BNNs) trained on the updated Observational Hubble Data (OHD) and Pantheon+ Type Ia Supernova sample. The reconstructed luminosity distances are used to calibrate the Platinum and Narendra et al. GRB samples. We constrain the parameters of the 2D Dainotti relation and the 3D fundamental plane, and examine the impact of calibration datasets and GRB sample selection. Calibration achieved using Pantheon+ yields tighter constraints than OHD, while the 3D correlation exhibits lower intrinsic scatter than the 2D relation. Our results demonstrate that BNNs provide a robust framework for model independent calibration of GRB luminosity correlations with reliable uncertainty propagation. Further, the underlying distance probe is a key factor in model-independent calibration, determining both the size of the GRB samples and the precision of the resulting constraints.

astro-ph.CO↗

arXiv2026

Inferences for f(R) Models from Late-Time Megamaser Observational Data

In this work, we study three widely used models of f(R) gravity, namely HuSawicki, Starobinsky and ArcTanh along with the standard cosmology model ($\Lambda$CDM). For this, we employ the megamaser angular diameter distance and velocity measurements from the Megamaser Cosmology Project, which provide a purely geometric determination of the Hubble constant. We constrain the parameters using the Markov Chain Monte Carlo method. Our results show that values of the Hubble Constant, $H_{0}$, obtained for all four models are in concordance with its value obtained from other late-time observational data such as SNe Ia. The constraints on $H_{0}$ in all the models under study are restrictive and the marginalized estimates lie close to 73 $\mathrm {km s^{-1} Mpc^{-1}}$. The marginalized estimates of the deviation parameter, b, for the three f(R) gravity models lie close to zero. This late-time dataset, thus predicts that f(R) models mimic $\Lambda$CDM. However, the matter density, $\Omega_m$, remains weakly constrained for all the models with its marginalized estimate close to 0.5. Further, comparison of the four models (f(R) models and $\Lambda$CDM) using information criteria such as Akaike Information Criterion and Bayesian Information Criterion shows that within current uncertainties, the dataset finds f(R) models statistically indistinguishable from $\Lambda$CDM. This is consistent with the fact that the favoured value of b for each of the f(R) models lies close to zero.

astro-ph.CO↗

arXiv2026

Reconstructing Gamma Ray Burst Energy Relations with Observational H(z) data in Neural Network Framework

Gamma-ray bursts (GRBs) offer a powerful probe of the cosmic expansion history far beyond the redshift range accessible to Type Ia supernovae. However, the study of cosmological models using GRBs is hindered by the circularity problem, which arises from assuming a fiducial cosmological model during GRB luminosity distance calibration. In this work, we perform a model-independent calibration of GRB luminosity relations using observational measurements of the Hubble parameter from the A220 and J220 compilations, thereby avoiding explicit cosmological assumptions. We employ an Artificial Neural Network to reconstruct the calibration relation directly from the data. In addition, we implement a Bayesian Neural Network framework as an alternative approach, enabling a data-driven treatment of both statistical and systematic uncertainties. The calibrated GRB sample is used to constrain the Amati relation, and we systematically compare the outcomes obtained from different calibration techniques and datasets. We find that the Amati relation slopes derived from the two neural network approaches are consistent with each other and with previous low-redshift calibrations obtained using model-independent methods. The Bayesian Neural Network approach provides a more robust framework for propagating uncertainties in the calibration procedure.

astro-ph.CO↗

arXiv2025

Study of Various Dark Matter Halo Profiles in Milky Way and M31 Galaxies within the Standard Cosmology Framework

In this paper, we study the rotation curves of the Milky Way galaxy (MW) and Andromeda galaxy (M31) by considering their bulge, disk, and halo components. We model the bulge region by the widely accepted de Vaucouleur's law and the disk region by the well-established exponential profile. In order to understand the distribution of dark matter in the halo region, we consider three different dark matter profiles in the framework of the standard $\Lambda$CDM model, namely, Navarro-Frenk-White (NFW), Hernquist, and Einasto profiles. We use recent datasets of rotation curves of the Milky Way and Andromeda galaxies. The data consist of rotation velocities of the stars and gas in the galaxy as a function of the radial distance from the center. Using Bayesian statistics, we perform an overall fit including all the components, i.e., bulge, disk, and halo, with the data. Our results indicate that the NFW and Hernquist profiles are in concordance with the observational data points. However, the Einasto profile poorly explains the behavior of dark matter in both the galaxies.

astro-ph.GA↗

arXiv2023

Gamma Rays Bursts: A Viable Cosmological Probe?

In this work, our focus is on exploring the potential of current GRB measurements to provide reliable constraints on cosmological model parameters at high redshift. This work is divided into two parts. First, we calibrate the Amati relation in a model-independent way by using Hubble parameter measurements obtained from the differential ages of the galaxies. We further check if the Amati relation parameters evolve with the GRBs' redshift or not, using the data of Old Astrophysical Objects. The results indicate that GRBs do seem to evolve with redshift. In the second part, we test different cosmological models with the calibrated GRB data obtained by using constant and dynamical Amati relation. Our results indicate that the present quality of GRB data is not good enough to put tight constraints on the cosmological parameters. Hence we perform a joint analysis with the combined data of GRBs and Type Ia Supernovae (SNe) and find that this can considerably enhance cosmological constraints in contrast to solely relying on GRBs.

astro-ph.CO↗

arXiv2021

Constraining Cosmological and Galaxy Parameters using Strong Gravitational Lensing Systems

Strong gravitational lensing along with the distance sum rule method can constrain both cosmological parameters as well as density profiles of galaxies without assuming any fiducial cosmological model. To constrain galaxy parameters and cosmic curvature $(Ω_{k0})$, we use the distance ratio data from a recently compiled database of $161$ galactic scale strong lensing systems. We use databases of supernovae type-Ia (Pantheon) and Gamma Ray Bursts (GRBs) for calculating the luminosity distance. To study the model of the lens galaxy, we consider a general lens model namely, the Extended Power-Law model. Further, we take into account two different parametrisations of the mass density power-law index $(γ)$ to study the dependence of $γ$ on redshift. The best value of $Ω_{k0}$ suggests a closed universe, though a flat universe is accommodated at $68\%$ confidence level. We find that parametrisations of $γ$ have a negligible impact on the best fit value of the cosmic curvature parameter. Furthermore, measurement of time delay can be a promising cosmographic probe via "time delay distance" that includes the ratio of distances between the observer, the lens and the source. We again use the distance sum rule method with time-delay distance dataset of H0LiCOW to put constraints on the Cosmic Distance Duality Relation (CDDR) and the cosmic curvature parameter $(Ω_{k0})$. For this we consider two different redshift-dependent parametrisations of the distance duality parameter $(η)$. The best fit value of $Ω_{k0}$ clearly indicates an open universe. However, a flat universe can be accommodated at $95\%$ confidence level. Further, at $95\%$ confidence level, no violation of CDDR is observed. We believe that a larger sample of strong gravitational lensing systems is needed in order to improve the constraints on the cosmic curvature and distance duality parameter.

astro-ph.CO↗

arXiv2017

Revisiting dark energy models using differential ages of galaxies

In this work, we use a test based on the differential ages of galaxies for distinguishing the dark energy models. As proposed by Jimenez and Loeb, relative ages of galaxies can be used to put constraints on various cosmological parameters. In the same vein, we reconstruct $H_0dt/dz$ and its derivative ($H_0d^2t/dz^2$) using a model independent technique called non-parametric smoothing. Basically, $dt/dz$ is the change in the age of the object as a function of redshift which is directly link with the Hubble parameter. Hence for reconstruction of this quantity, we use the most recent $H(z)$ data. Further, we calculate $H_0dt/dz$ and its derivative for several models like Phantom, Einstein de Sitter (EdS), $Λ$CDM, Chevallier-Polarski-Linder (CPL) parametrization, Jassal-Bagla-Padmanabhan (JBP) parametrization and Feng-Shen-Li-Li (FSLL) parametrization. We check the consistency of these models with the results of reconstruction obtained in model independent way from the data. It is observed that $H_0dt/dz$ as a tool is not able to distinguish between the $Λ$CDM, CPL, JBP and FSLL parametrizations but as expected EdS and Phantom models show noticeable deviation from the reconstructed results. Further, the derivative of $H_0dt/dz$ for various dark energy models is more sensitive at low redshift. It is observed that the FSLL model is not consistent with the reconstructed results at redshifts less than $0.5$, however, the $Λ$CDM model is in concordance with the 3$σ$ region of the reconstruction.

astro-ph.CO↗

arXiv2015

Transition Redshift: New constraints from parametric and nonparametric methods

In this paper, we use the Cosmokinematics approach to study the accelerated expansion of the Universe. This is a model independent approach and depends only on the assumption that the Universe is homogeneous and isotropic and is described by the FRW metric. We parametrize the deceleration parameter, $q(z)$, to constrain the transition redshift ($z_t$) at which the expansion of the Universe goes from a decelerating to an accelerating phase. We use three different parametrizations of $q(z)$ namely, $q_\I(z)=q_{\textnormal{\tiny\textsc{1}}}+q_{\textnormal{\tiny\textsc{2}}}z$, $q_\II (z) = q_\3 + q_\4 \ln (1 + z)$ and $q_\III(z)=\frac{1}{2}+\frac{q_{\textnormal{\tiny\textsc{5}}}}{(1+z)^2}$. A joint analysis of the age of galaxies, strong lensing and supernovae Ia data indicates that the transition redshift is less than unity i.e. $z_t<1$. We also use a nonparametric approach (LOESS+SIMEX) to constrain $z_t$. This too gives $z_t<1$ which is consistent with the value obtained by the parametric approach.

gr-qc↗