Amit K. Mandal | Searcharxiv

arXiv2025

Application of the FRADO model of BLR formation to the Seyfert galaxy NGC 5548 and the first step toward determining the Hubble constant

The dynamical and geometric structures of the Broad Line Region (BLR), along with the origins of continuum time delays in active galaxies, remain topics of ongoing debate. In this study, we aim to reproduce the observed broadband spectrum, the H$β$ line delay, and the continuum time delays using our newly developed model for the source NGC 5548. We adopt the standard accretion disk model, with the option of an inner hot flow, and employ the lamp-post model to account for disk irradiation. Additionally, we model the BLR structure based on radiation pressure acting on dust. The model is parameterized by the black hole mass, $M_{\text{BH}}$ (which is fixed), the accretion rate, the viewing angle, the height of the lamp-post, the cloud density, and the cloud covering factor. The resulting continuum time delays arise from a combination of disk reprocessing and the reprocessing of a fraction of radiation by the BLR. Our model reasonably reproduces the observed broad-band continuum, the H$β$ time delay, and the continuum inter-band time delays measured during the observational campaign. When the accretion rate is not constrained by the known distance to the source, our approach allows for a direct estimation of the distance. The resulting Hubble constant, $H_0$ = $66.9^{+10.6}_{-2.1}$ km s$^{-1}$ Mpc$^{-1}$, represents a significant improvement over previously reported values derived from continuum time delays in the literature. This pilot study demonstrates that, with sufficient data coverage, it is possible to disentangle the time delays originating from the accretion disk and the BLR. This paves the way for effectively using inter-band continuum time delays as a method for determining the Hubble constant. Additionally, the findings provide strong support for the adopted model for the formation of the H$β$ line.

astro-ph.GA↗

arXiv2017

Pruned non-local means

In Non-Local Means (NLM), each pixel is denoised by performing a weighted averaging of its neighboring pixels, where the weights are computed using image patches. We demonstrate that the denoising performance of NLM can be improved by pruning the neighboring pixels, namely, by rejecting neighboring pixels whose weights are below a certain threshold $λ$. While pruning can potentially reduce pixel averaging in uniform-intensity regions, we demonstrate that there is generally an overall improvement in the denoising performance. In particular, the improvement comes from pixels situated close to edges and corners. The success of the proposed method strongly depends on the choice of the global threshold $λ$, which in turn depends on the noise level and the image characteristics. We show how Stein's unbiased estimator of the mean-squared error can be used to optimally tune $λ$, at a marginal computational overhead. We present some representative denoising results to demonstrate the superior performance of the proposed method over NLM and its variants.

cs.CV↗