arXiv subjects

Santosh Kumar Yadav

Publications and source records attributed to Santosh Kumar Yadav.

22 records · Page 2Linked to original sources

arXiv2019

Dark sector interaction: a remedy of the tensions between CMB and LSS data

The well-known tensions on the cosmological parameters $H_0$ and $σ_8$ within the $Λ$CDM cosmology shown by the Planck-CMB and LSS data are possibly due to the systematics in the data or our ignorance of some new physics beyond the $Λ$CDM model. In this letter, we focus on the second possibility, and investigate a minimal extension of the $Λ$CDM model by allowing a coupling between its dark sector components (dark energy and dark matter). We analyze this scenario with Planck-CMB, KiDS and HST data, and find that the $H_0$ and $σ_8$ tensions disappear at 68\% CL. In the joint analyzes with Planck, HST and KiDS data, we find non-zero coupling in the dark sector up to 99\% CL. Thus, we find a strong statistical support from the observational data for an interaction in the dark sector of the Universe while solving the $H_0$ and $σ_8$ tensions simultaneously.

astro-ph.CO↗

arXiv2018

Cosmological bounds on dark matter-photon coupling

We investigate an extension of the $Λ$CDM model where the dark matter (DM) is coupled to photons, inducing a nonconservation of the numbers of particles for both species, where the DM particles are allowed to dilute throughout the cosmic history with a small deviation from the standard evolution decaying into photons, while the associated scattering processes are assumed to be negligible. In addition, we consider the presence of massive neutrinos with the effective number of species $N_{\rm eff}$ as a free parameter. The effects of the DM-photon coupling on the cosmic microwave background (CMB) and matter power spectra are analyzed. We derive the observational constraints on the model parameters by using the data from CMB, baryonic acoustic oscillation (BAO) measurements, the recently measured new local value of the Hubble constant from the Hubble Space Telescope, and large scale structure (LSS) information from the abundance of galaxy clusters. The DM-photon coupling parameter $Γ_{γ}$ is constrained to $Γ_{γ} \leq 1.3 \times10^{-5}$ (at 95\% C.L.) from the joint analysis carried out by using all the mentioned data sets. The neutrino mass scale $\sum m_ν$ upper bounds at 95\% C.L. are obtained as $\sum m_ν \sim 0.9$ eV and $\sum m_ν \sim 0.4$ eV with and without the LSS data, respectively. We observe that the DM-photon coupling cause significant changes in the best fit value of $N_{\rm eff}$ but yields statistical ranges of $N_{\rm eff}$ compatible with the standard predictions, and we do not find any evidence of dark radiation. Due to nonconservation of photons in our model, we also evaluate and analyze the effects on the BAO acoustic scale at the drag epoch. The DM-photon coupling model yields high values of Hubble constant consistent with the local measurement, and thus alleviates the tension on this parameter.

astro-ph.CO↗

arXiv2017

A Fast Data Driven Shrinkage of Singular Values for Arbitrary Rank Signal Matrix Denoising

Recovering a low-rank signal matrix from its noisy observation, commonly known as matrix denoising, is a fundamental inverse problem in statistical signal processing. Matrix denoising methods are generally based on shrinkage or thresholding of singular values with a predetermined shrinkage parameter or threshold. However, most of the existing adaptive shrinkage methods use multiple parameters to obtain a better flexibility in shrinkage. The optimal value of these parameters using either cross-validation or Stein's principle. In both the cases, the iterative estimation of various parameters render the existing shrinkage methods computationally latent for most of the real-time applications. This paper presents an efficient data dependent shrinkage function whose parameters are estimated using Stein's principle but in a non-iterative manner, thereby providing a comparatively faster shrinkage method. In addition, the proposed estimator is found to be consistent with the recently proposed asymptotically optimal estimators using the results from random matrix theory. The experimental studies on artificially generated low-rank matrices and on the magnetic resonant imagery data, show the efficacy of the proposed denoising method.

stat.ME↗

arXiv2016

Electrocardiogram signal denoising using non-local wavelet transform domain filtering

ECG signals are usually corrupted by baseline wander, power-line interference, muscle noise, etc. and numerous methods have been proposed to remove these noises. However, in case of wireless recording of the ECG signal it gets corrupted by the additive white Gaussian noise (AWGN). For the correct diagnosis, removal of AWGN from ECG signals becomes necessary as it affects the all the diagnostic features. The natural signals exhibit correlation among their samples and this property has been exploited in various signal restoration tasks. Motivated by that, in this work we propose a nonlocal wavelet transform domain ECG signal denoising method which exploits the correlations among both local and nonlocal samples of the signal. In the proposed method, the similar blocks of the samples are grouped in a matrix and then denoising is achieved by the shrinkage of its two-dimensional discrete wavelet transform coefficients. The experiments performed on a number of ECG signals show significant quantitative and qualitative improvement in denoising performance over the existing ECG signal denoising methods.

stat.AP↗