arXiv subjects

Arnab Chakraborty

Publications and source records attributed to Arnab Chakraborty.

53 records · Page 3Linked to original sources

arXiv2022

Deep uGMRT observations of the ELAIS-North 1 field: statistical properties of radio--infrared relations up to $z \sim$2

Comprehending the radio--infrared (IR) relations of the faint extragalactic radio sources is important for using radio emission as a tracer of star-formation in high redshift ($z$) star-forming galaxies (SFGs). Using deep uGMRT observations of the ELAIS-N1 field in the 0.3--0.5\,GHz range, we study the statistical properties of the radio--IR relations and the variation of the `$q$-parameter' up to $z=2$ after broadly classifying the faint sources as SFGs and AGN. We find the dust temperature ($\tdust$) to increase with $z$. This gives rise to $\qmir$, measured at $24\,\upmu$m, to increase with $z$ as the peak of IR emission shifts towards shorter wavelengths, resulting in the largest scatter among different measures of $q$-parameters. $\qfir$ measured at $70\,\upmu$m, and $q_{\rm TIR}$ using total-IR (TIR) emission are largely unaffected by $\tdust$. We observe strong, non-linear correlations between the radio luminosities at 0.4 and 1.4\,GHz with $70\,\upmu$m luminosity and TIR luminosity($\ltir$). To assess the possible role of the radio-continuum spectrum in making the relations non-linear, for the first time we study them at high $z$ using integrated radio luminosity ($\lrc$) in the range 0.1--2\,GHz. In SFGs, the $\lrc$--$\ltir$ relation remains non-linear with a slope of $1.07\pm0.02$, has a factor of 2 lower scatter compared to monochromatic radio luminosities, and $\qtirbol$ decreases with $z$ as $\qtirbol = (2.27 \pm 0.03)\,(1+z)^{-0.12 \pm 0.03}$. A redshift variation of $q$ is a natural consequence of non-linearity. We suggest that a redshift evolution of magnetic field strengths and/or cosmic ray acceleration efficiency in high-$z$ SFGs could give rise to non-linear radio--IR relations.

astro-ph.GA↗

arXiv2022

A Comparative Analysis To Deal With Missing Spectral Information Caused By RFI In Cosmological HI 21CM Observations

We investigate the effect of radio-frequency interference (RFI) excision in estimating the cosmological \hi\ 21 cm power spectrum. Flagging of RFI-contaminated channels results in a non-uniform sampling of the instrumental bandpass response. Hence, the Fourier transformation (FT) of visibilities from frequency to delay domain contaminates the higher foreground-free delay modes, and separating the spectrally fluctuating \hi\ signal from spectrally smooth foregrounds becomes challenging. We have done a comparative analysis between two algorithms, one-dimensional CLEAN and Least Square Spectral Analysis (LSSA), which have been used widely to solve this issue in the literature. We test these algorithms using the simulated SKA-1 low observations in the presence of different RFI flagging scenarios. We find that in the presence of random flagging of data, both algorithms perform well and can mitigate the foreground leakage issue. But, CLEAN fails to restrict the foreground leakage in the presence of periodic and periodic plus broadband RFI flagging and gives an extra bias to the estimated power spectrum. However, LSSA can restrict the foreground leakage for these RFI flagging scenarios and gives an unbiased estimate of the \hi\ 21 cm power spectrum. We have also applied these algorithms to the upgraded GMRT observation and found that both CLEAN and LSSA give consistent results in the presence of realistic random flagging scenarios for this observed data set. This comparative analysis demonstrates the effectiveness and robustness of these two algorithms in estimating the \hi\ 21 cm power spectrum from the data set affected by different RFI scenarios.

astro-ph.CO↗

arXiv2020

First multi-redshift limits on post-Epoch of Reionization (post-EoR) 21 cm signal from z = 1.96 - 3.58 using uGMRT

Measurement of fluctuations in diffuse HI 21 cm background radiation from the post-reionization epoch (z < 6) is a promising avenue to probe the large-scale structure of the Universe and understand the evolution of galaxies. We observe the European Large-Area ISO Survey-North 1 (ELAIS-N1) field at 300-500 MHz using the upgraded Giant Meterwave Radio Telescope (uGMRT) and employ the 'foreground avoidance' technique to estimate the HI 21 cm power spectrum in the redshift range z = 1.96-3.58. Given the possible systematics that may remain in the data, we find the most stringent upper limits on the spherically averaged 21 cm power spectra at k~1.0 Mpc$^{-1}$ are (58.87 mK)$^2$, (61.49 mK)$^2$, (60.89 mK)$^2$, (105.85 mK)$^2$ at z = 1.96,2.19,2.62 and 3.58, respectively. We use this to constrain the product of neutral HI mass density (Omega_HI) and HI bias (b_HI) to the underlying dark matter density field, [Omega_HI*b_HI], as 0.09,0.11,0.12,0.24 at z=1.96,2.19,2.62,3.58, respectively. To the best of our knowledge these are the first limits on the HI 21 cm power spectra at the redshift range z = 1.96 - 3.58 and would play a significant role to constrain the models of galaxy formation and evolution.

astro-ph.CO↗

arXiv2020

Characterizing EoR foregrounds: A study of the Lockman Hole Region at 325 MHz

One of the key science goals for the most sensitive telescopes, both current and upcoming, is the detection of the redshifted 21-cm signal from the Cosmic Dawn and Epoch of Reionization. The success of detection relies on accurate foreground modeling for their removal from data sets. This paper presents the characterization of astrophysical sources in the Lockman Hole region. Using 325 MHz data obtained from the GMRT, a $6^\circ \times 6^\circ$ mosaiced map is produced with an RMS reaching 50 $μ$Jy $\mathrm{beam}^{-1}$. A source catalog containing 6186 sources is created, and the Euclidean normalized differential source counts have been derived from it, consistent with previous observations as well as simulations. A detailed comparison of the source catalog is also made with previous findings - at both lower and higher frequencies. The angular power spectrum (APS) of the diffuse Galactic synchrotron emission is determined for three different galactic latitudes using the Tapered Gridded Estimator. The values of the APS lie between $\sim$1 mK$^2$ to $\sim$100 mK$^2$. Fitting a power law of the form $A\ell^{-β}$ gives values of $A$ and $β$ varying across the latitudes considered. This paper demonstrates, for the first time, the variation of the power-law index for diffuse emission at very high galactic locations. It follows the same trend that is seen at locations near the galactic plane, thus emphasizing the need for low-frequency observations for developing better models of the diffuse emission.

astro-ph.CO↗

arXiv2020

The study of the angular and spatial distribution of radio selected AGNs and star-forming galaxies in the ELAIS N1 field

The cosmic evolution of bias of different source populations with underlying dark matter density field in post reionization era can shed light on large scale structures. Studying the angular and spatial distribution of different compact sources using deep radio catalogue at low-frequency is essential to understand the matter distribution of the present Universe. Here, we investigate the relationship of luminous matter with their host dark matter haloes by measuring the angular and spatial clustering of sources (two-point statistics), using deep radio observation of ELAIS N1 (EN1) field with upgraded Giant Metrewave Radio Telescope (uGMRT) at 300-500 MHz. We also analyze the 612 MHz GMRT archival data of the same field to understand the cosmic evolution of clustering of different source populations. We classify the sources as star-forming galaxies (SFGs) and active galactic nuclei (AGN) based on their radio luminosity. We find that the spatial clustering length and bias to the dark matter density field of SFGs are smaller than AGNs at both frequencies. This proves that AGNs are mainly hosted by massive haloes and hence strongly clustered. However, a small decrease in the bias for both kind of sources at higher frequency indicates that we are most likely tracing the faint objects residing in less massive haloes at higher frequencies. Our results are in excellent agreement with previous findings at radio and multi-frequency surveys. However, comparison with SKADS simulation suggests that the halo mass for different populations used in the simulation is systematically lower. This work quantifies the spatial distribution of extragalactic compact objects in EN1 field and bridges the gap between shallow and deep surveys.

astro-ph.GA↗

arXiv2020

Characterization of unresolved and unclassified sources detected in radio continuum surveys of the Galactic plane

The continuum emission from 1 to 2 GHz of The HI/OH/Recombination line survey of the inner Milky Way (THOR) at $\lesssim$18" resolution covers $\sim 132$ square degrees of the Galactic plane and detects 10387 sources. Similarly, the first data release of the Global View of Star Formation in the Milky Way (GLOSTAR) surveys covers $\sim 16$ square degrees of the Galactic plane from 4-8 GHz at 18" resolution and detects 1575 sources. However, a large fraction of the unresolved discrete sources detected in these radio continuum surveys of the Galactic plane remain unclassified. Here, we study the Euclidean-normalized differential source counts of unclassified and unresolved sources detected in these surveys and compare them with simulated extragalactic radio source populations as well as previously established source counts. We find that the differential source counts for THOR and GLOSTAR surveys are in excellent agreement with both simulation and previous observations. We also estimate the angular two-point correlation function of unclassified and unresolved sources detected in THOR survey. We find a higher clustering amplitude in comparison with the Faint Images of the Radio Sky at Twenty-cm (FIRST) survey up to the angular separation of $5^{\circ}$. The decrease in angular correlation with increasing flux cut and the excellent agreement of clustering pattern of sources above 1 mJy with high $z$ samples ($z >0.5$) of the FIRST survey indicates that these sources might be high $z$ extragalactic compact objects. The similar pattern of one-point and two-point statistics of unclassified and compact sources with extragalactic surveys and simulations confirms the extragalactic origin of these sources.

astro-ph.GA↗

arXiv2019

21cm Global Signal Extraction: Extracting the 21cm Global Signal using Artificial Neural Networks

The study of the cosmic Dark Ages, Cosmic Dawn, and Epoch of Reionization (EoR) using the all-sky averaged redshifted HI 21cm signal, are some of the key science goals of most of the ongoing or upcoming experiments, for example, EDGES, SARAS, and the SKA. This signal can be detected by averaging over the entire sky, using a single radio telescope, in the form of a Global signal as a function of only redshifted HI 21cm frequencies. One of the major challenges faced while detecting this signal is the dominating, bright foreground. The success of such detection lies in the accuracy of the foreground removal. The presence of instrumental gain fluctuations, chromatic primary beam, radio frequency interference (RFI) and the Earth's ionosphere corrupts any observation of radio signals from the Earth. Here, we propose the use of Artificial Neural Networks (ANN) to extract the faint redshifted 21cm Global signal buried in a sea of bright Galactic foregrounds and contaminated by different instrumental models. The most striking advantage of using ANN is the fact that, when the corrupted signal is fed into a trained network, we can simultaneously extract the signal as well as foreground parameters very accurately. Our results show that ANN can detect the Global signal with $\gtrsim 92 \%$ accuracy even in cases of mock observations where the instrument has some residual time-varying gain across the spectrum.

astro-ph.CO↗

arXiv2019

Detailed study of ELAIS N1 field with the uGMRT -- II. Source Properties and Spectral Variation Of Foreground Power Spectrum from 300-500 MHz Observations

Understanding the low-frequency radio sky in depth is necessary to subtract foregrounds in order to detect the redshifted 21 cm signal of neutral hydrogen from the Cosmic Dawn, Epoch of Reionization (EoR) and post-reionization era. In this second paper of the series, we present the upgraded Giant Metrewave Radio Telescope (uGMRT) observation of the ELAIS N1 field made at 300-500 MHz. The image covers an area of $\sim 1.8$ $\mathrm{deg}^{2}$ and has a central background rms noise of $\sim$ 15 $μ\mathrm{Jy}$ $\mathrm{beam}^{-1}$. We present a radio source catalog containing 2528 sources (with flux densities > 100 $μ$Jy) and normalized source counts derived from that. The detailed comparison of detected sources with previous radio observations is shown. We discuss flux scale accuracy, positional offsets, spectral index distribution and correction factors in source counts. The normalized source counts are in agreement with previous observations of the same field, as well as model source counts from the Square Kilometre Array Design Study (SKADS) simulation. It shows a flattening below $\sim$1 mJy which corresponds to rise in population of star forming galaxies and radio-quiet AGN. For the first time, we estimated the spectral characteristics of the angular power spectrum or Multi-Frequency Angular Power Spectrum (MFAPS) of diffuse Galactic synchrotron emission (DGSE) over the wide frequency bandwidth of $300-500$~MHz from radio interferometric observations. This work demonstrates the improved capabilities of the uGMRT.

astro-ph.CO↗

arXiv2019

A Statistical Analysis of Noisy Crowdsourced Weather Data

Spatial prediction of weather-elements like temperature, precipitation, and barometric pressure are generally based on satellite imagery or data collected at ground-stations. None of these data provide information at a more granular or "hyper-local" resolution. On the other hand, crowdsourced weather data, which are captured by sensors installed on mobile devices and gathered by weather-related mobile apps like WeatherSignal and AccuWeather, can serve as potential data sources for analyzing environmental processes at a hyper-local resolution. However, due to the low quality of the sensors and the non-laboratory environment, the quality of the observations in crowdsourced data is compromised. This paper describes methods to improve hyper-local spatial prediction using this varying-quality noisy crowdsourced information. We introduce a reliability metric, namely Veracity Score (VS), to assess the quality of the crowdsourced observations using a coarser, but high-quality, reference data. A VS-based methodology to analyze noisy spatial data is proposed and evaluated through extensive simulations. The merits of the proposed approach are illustrated through case studies analyzing crowdsourced daily average ambient temperature readings for one day in the contiguous United States.

stat.AP↗

arXiv2019

On Statistical Properties of A Veracity Scoring Method for Spatial Data

Measuring veracity or reliability of noisy data is of utmost importance, especially in the scenarios where the information are gathered through automated systems. In a recent paper, Chakraborty et. al. (2019) have introduced a veracity scoring technique for geostatistical data. The authors have used a high-quality `reference' data to measure the veracity of the varying-quality observations and incorporated the veracity scores in their analysis of mobile-sensor generated noisy weather data to generate efficient predictions of the ambient temperature process. In this paper, we consider the scenario when no reference data is available and hence, the veracity scores (referred as VS) are defined based on `local' summaries of the observations. We develop a VS-based estimation method for parameters of a spatial regression model. Under a non-stationary noise structure and fairly general assumptions on the underlying spatial process, we show that the VS-based estimators of the regression parameters are consistent. Moreover, we establish the advantage of the VS-based estimators as compared to the ordinary least squares (OLS) estimator by analyzing their asymptotic mean squared errors. We illustrate the merits of the VS-based technique through simulations and apply the methodology to a real data set on mass percentages of ash in coal seams in Pennsylvania.

stat.ME↗

arXiv2019

Detailed study of the ELAIS N1 field with the uGMRT - I. Characterizing the 325 MHz foreground for redshifted 21 cm observations

In this first paper of the series, we present initial results of newly upgraded Giant Meterwave Radio Telescope (uGMRT) observation of European Large-Area ISO Survey-North 1 (ELAIS-N1) at 325 MHz with 32 MHz bandwidth. Precise measurement of fluctuations in Galactic and extragalactic foreground emission as a function of frequency as well as angular scale is necessary for detecting redshifted 21-cm signal of neutral hydrogen from Cosmic Dawn, Epoch of Reionization (EoR) and post-reionization epoch. Here, for the first time we have statistically quantified the Galactic and extragalactic foreground sources in the ELAIS-N1 field in the form of angular power spectrum using the newly developed Tapered Gridded Estimator (TGE). We have calibrated the data with and without direction-dependent calibration techniques. We have demonstrated the effectiveness of TGE against the direction dependent effects by using higher tapering of field of view (FoV). We have found that diffuse Galactic synchrotron emission (DGSE) dominates the sky, after point source subtraction, across the angular multipole range $ 1115 \leqslant \mathcal{\ell} \leqslant 5083 $ and $ 1565 \leqslant \mathcal{\ell} \leqslant 4754 $ for direction-dependent and -independent calibrated visibilities respectively. The statistical fluctuations in DGSE has been quantified as a power law of the form $\mathcal{C}_{\mathcal{\ell}}= A \mathcal{\ell}^{-β} $. The best fitted values of (A, $β$) are ($ 62 \pm 6$ $mK^{2}$, $2.55 \pm 0.3 $) and ($ 48 \pm 4$ $mK^{2}$, $2.28 \pm 0.4 $ ) for the two different calibration approaches. For both the cases, the power law index is consistent with the previous measurements of DGSE in other parts of sky.

astro-ph.CO↗

arXiv2018

Data Reduction in Markov model using EM algorithm

This paper describes a data reduction technique in case of a markov chain of specified order. Instead of observing all the transitions in a markov chain we record only a few of them and treat the remaining part as missing. The decision about which transitions to be filtered is taken before the observation process starts. Based on the filtered chain we try to estimate the parameters of the markov model using EM algorithm. In the first half of the paper we characterize a class of filtering mechanism for which all the parameters remain identifiable. In the later half we explain methods of estimation and testing about the transition probabilities of the markov chain based on the filtered data. The methods are first developed assuming a simple markov model with each probability of transition positive, but then generalized for models with structural zeroes in the transition probability matrix. Further extension is also done for multiple markov chains. The performance of the developed method of estimation is studied using simulated data along with a real life data.

stat.ME↗

arXiv2017

Congestion Barcodes: Exploring the Topology of Urban Congestion Using Persistent Homology

This work presents a new method to quantify connectivity in transportation networks. Inspired by the field of topological data analysis, we propose a novel approach to explore the robustness of road network connectivity in the presence of congestion on the roadway. The robustness of the pattern is summarized in a congestion barcode, which can be constructed directly from traffic datasets commonly used for navigation. As an initial demonstration, we illustrate the main technique on a publicly available traffic dataset in a neighborhood in New York City.

physics.soc-ph↗

arXiv2014

Compressive Sampling Using EM Algorithm

Conventional approaches of sampling signals follow the celebrated theorem of Nyquist and Shannon. Compressive sampling, introduced by Donoho, Romberg and Tao, is a new paradigm that goes against the conventional methods in data acquisition and provides a way of recovering signals using fewer samples than the traditional methods use. Here we suggest an alternative way of reconstructing the original signals in compressive sampling using EM algorithm. We first propose a naive approach which has certain computational difficulties and subsequently modify it to a new approach which performs better than the conventional methods of compressive sampling. The comparison of the different approaches and the performance of the new approach has been studied using simulated data.

stat.ME↗

arXiv2013

VOStat: A Statistical Web Service for Astronomers

VOStat is a Web service providing interactive statistical analysis of astronomical tabular datasets. It is integrated into the suite of analysis and visualization tools associated with the international Virtual Observatory (VO) through the SAMP communication system. A user supplies VOStat with a dataset extracted from the VO, or otherwise acquired, and chooses among $\sim 60$ statistical functions. These include data transformations, plots and summaries, density estimation, one- and two-sample hypothesis tests, global and local regressions, multivariate analysis and clustering, spatial analysis, directional statistics, survival analysis (for censored data like upper limits), and time series analysis. The statistical operations are performed using the public domain {\bf R} statistical software environment, including a small fraction of its $>4000$ {\bf CRAN} add-on packages. The purpose of VOStat is to facilitate a wider range of statistical analyses than are commonly used in astronomy, and to promote use of more advanced methodology in {\bf R} and {\bf CRAN}.

astro-ph.IM↗

arXiv2011

RESID: A Practical Stochastic Model for Software Reliability

A new approach called RESID is proposed in this paper for estimating reliability of a software allowing for imperfect debugging. Unlike earlier approaches based on counting number of bugs or modelling inter-failure time gaps, RESID focuses on the probability of "bugginess" of different parts of a program buggy. This perspective allows an easy way to incorporate the structure of the software under test, as well as imperfect debugging. One main design objective behind RESID is ease of implementation in practical scenarios.

stat.AP↗

arXiv2011

QuECT: A New Quantum Programming Paradigm

Quantum computation constitutes a rapidly expanding subfield of computer science. Development quantum algorithms is facilitated by the availability of efficient quantum programming languages, and a plethora of approaches has been already suggested in the literature, ranging from GUI-based simple tools to elaborate standalone programming languages. In this paper we propose a novel paradigm called Quantum Embeddable Circuit Technique (QuECT) that allows a programmer to embed a circuit diagram in a classical "host" language. The paradigm can be implemented in any modern classical language. A prototype has been developed by the author using Java.

quant-ph↗