arXiv subjects

R. Misra

Publications and source records attributed to R. Misra.

At least 37 records · Page 2Linked to original sources

arXiv2018

Broadband Spectral Fitting of Blazars using XSPEC

The broadband spectral energy distribution(SED) of blazars is generally interpreted as radiation arising from synchrotron and inverse Compton mechanisms.Traditionally, the underlying source parameters responsible for these emission processes,like particle energy density, magnetic field, etc., are obtained through simple visual reproduction of the observed fluxes. However, this procedure is incapable of providing the confidence range on the estimated parameters. In this work, we propose an efficient algorithm to perform a statistical fit of the observed broadband spectrum of blazars using different emission models. Moreover, in this work we use the the observable quantities as the fit parameters, rather than the direct source parameters which govern the resultant SED. This significantly improves the convergence time and eliminates the uncertainty regarding the initial guess parameters. This approach also has an added advantage of identifying the degenerate parameters, which can be removed by including more observable information and/or additional constraints. A computer code developed based on this algorithm is implemented as an user-defined routine in the standard X-ray spectral fitting package, XSPEC. Further, we demonstrate the efficacy of the algorithm by fitting the well sampled SED of the blazar, 3C 279, during its gamma ray flare in 2014.

astro-ph.HE↗

arXiv2017

The Hard X-ray emission of the blazar PKS 2155--304

The synchrotron peak of the X-ray bright High Energy Peaked Blazar (HBL) PKS 2155$-$304 occurs in the UV-EUV region and hence its X-ray emission (0.6--10 keV) lies mostly in the falling part of the synchrotron hump. We aim to study the X-ray emission of PKS 2155$-$304 during different intensity states in 2009$-$2014 using XMM$-$Newton satellite. We studied the spectral curvature of all of the observations to provide crucial information on the energy distribution of the non-thermal particles. Most of the observations show curvature or deviation from a single power-law and can be well modeled by a log parabola model. In some of the observations, we find spectral flattening after 6 keV. In order to find the possible origin of the X-ray excess, we built the Multi-band Spectral Energy distribution (SED). We find that the X-ray excess in PKS 2155--304 is difficult to fit in the one zone model but, could be easily reconciled in the spine/layer jet structure. The hard X-ray excess can be explained by the inverse Comptonization of the synchrotron photons (from the layer) by the spine electrons.

astro-ph.HE↗

arXiv2017

Degree weighted recurrence networks for the analysis of time series data

Recurrence networks are powerful tools used effectively in the nonlinear analysis of time series data. The analysis in this context is done mostly with unweighted and undirected complex networks constructed with specific criteria from the time series. In this work, we propose a novel method to construct "weighted recurrence network"(WRN) from a time series and show how it can reveal useful information regarding the structure of a chaotic attractor, which the usual unweighted recurrence network cannot provide. Especially, we find the node strength distribution of the WRN, from every chaotic attractor follows a power law (with exponential tail) with the index characteristic to the fractal structure of the attractor. This leads to a new class among complex networks, to which networks from all standard chaotic attractors are found to belong. In addition, we present generalized definitions for clustering coefficient and characteristic path length and show that these measures can effectively discriminate chaotic dynamics from white noise and $1/f$ colored noise. Our results indicate that the WRN and the associated measures can become potentially important tools for the analysis of short and noisy time series from the real world systems as they are clearly demarked from that of noisy or stochastic systems.

nlin.CD↗

arXiv2017

Is a hyperchaotic attractor superposition of two multifractals?

In the context of chaotic dynamical systems with exponential divergence of nearby trajectories in phase space, hyperchaos is defined as a state where there is divergence or stretching in at least two directions during the evolution of the system. Hence the detection and characterization of a hyperchaotic attractor is usually done using the spectrum of Lyapunov Exponents (LEs) that measure this rate of divergence along each direction. Though hyperchaos arise in different dynamical situations and find several practical applications, a proper understanding of the geometric structure of a hyperchaotic attractor still remains an unsolved problem. In this paper, we present strong numerical evidence to suggest that the geometric structure of a hyperchaotic attractor can be characterized using a multifractal spectrum with two superimposed components. In other words, apart from developing an extra positive LE, there is also a structural change as a chaotic attractor makes a transition to the hyperchaotic phase and the attractor changes from a simple multifractal to a dual multifractal, equivalent to two inter-mingled multifractals. We argue that a cross-over behavior in the scaling region for computing the correlation dimension is a manifestation of such a structure. In order to support this claim, we present an illustrative example of a synthetically generated set of points in the unit interval (a Cantor set with a variable iteration scheme) displaying dual multifractal spectrum. Our results are also used to develop a general scheme to generate both hyperchaotic as well as high dimensional chaotic attractors by coupling two low dimensional chaotic attractors and tuning a time scale parameter.

nlin.CD↗

arXiv2017

Recurrence network measures for hypothesis testing using surrogate data: application to black hole light curves

Recurrence networks and the associated statistical measures have become important tools in the analysis of time series data. In this work, we test how effective the recurrence network measures are in analyzing real world data involving two main types of noise, white noise and colored noise. We use two prominent network measures as discriminating statistic for hypothesis testing using surrogate data for a specific null hypothesis that the data is derived from a linear stochastic process. We show that the characteristic path length is especially efficient as a discriminating measure with the conclusions reasonably accurate even with limited number of data points in the time series. We also highlight an additional advantage of the network approach in identifying the dimensionality of the system underlying the time series through a convergence measure derived from the probability distribution of the local clustering coefficients. As examples of real world data, we use the light curves from a prominent black hole system and show that a combined analysis using three primary network measures can provide vital information regarding the nature of temporal variability of light curves from different spectroscopic classes.

physics.data-an↗

arXiv2017

Detecting Dynamical States from Noisy Time Series using Bicoherence

Deriving meaningful information from observational data is often restricted by many limiting factors, the most important of which is the presence of noise. In this work, we present the use of the bicoherence function to extract information about the underlying nonlinearity from noisy time series. We show that a system evolving in the presence of noise which has its dynamical state concealed from quantifiers like the power spectrum and correlation dimension D2, can be revealed using the bicoherence function. We define an index called main peak bicoherence function as the bicoherence associated with the maximal power spectral peak. We show that this index is extremely useful while dealing with quasi-periodic data as it can distinguish strange non chaos from quasi periodicity even with added noise. We demonstrate this in a real world scenario, by taking the bicoherence of variable stars showing period doubling and strange non-chaotic behavior. Our results indicate that bicoherence analysis can also bypass the method of surrogate analysis using Fourier phase randomization, used to differentiate linear stochastic processes from non linear ones, in conventional methods involving measures like D2.

nlin.CD↗

arXiv2017

Detection of the high energy cut-off from the Seyfert 1.5 galaxy NGC 5273

We perform the NuSTAR and Swift/XRT joint energy spectral fitting of simultaneous observations from the broad-line Seyfert 1.5 galaxy NGC 5273. When fitted with the combination of an exponential cut-off power-law and a reflection model, a high energy cut-off is detected at 143$^{+96}_{-40}$ keV with 2-sigma significance. Existence of such cut-off is also consistent with the observed Comptonizing electron temperature when fitted with a Comptonization model independently. We observe a moderate hard X-ray variability of the source over the time-scale of ~12 years using INTEGRAL/ISGRI observations in the energy range of 20-100 keV. When the hard band count rate (6-20 keV) is plotted against the soft band count rate (3-6 keV), a hard offset is observed. Our results indicate that the cut-off energy may not correlate with the coronal X-ray luminosity in a simple manner. Similarities in parameters that describe coronal properties indicate that the coronal structure of NGC 5273 may be similar to that of the broad-line radio galaxy 3C 390.3 and another galaxy MCG-5-23-16 where the coronal plasma is dominated by electrons, rather than electron-positron pairs. Therefore, the coronal cooling is equally efficient to the heating mechanism keeping the cut-off energy at low even at the low accretion rate.

astro-ph.HE↗

arXiv2017

Determining the minimum embedding dimension for state space reconstruction through recurrence networks

The analysis of observed time series from nonlinear systems is usually done by making a time-delay reconstruction to unfold the dynamics on a multi-dimensional state space. An important aspect of the analysis is the choice of the correct embedding dimension. The conventional procedure used for this is either the method of false nearest neighbors or the saturation of some invariant measure, such as, correlation dimension. Here we examine this issue from a complex network perspective and propose a recurrence network based measure to determine the acceptable minimum embedding dimension to be used for such analysis. The measure proposed here is based on the well known Kullback-Leibler divergence commonly used in information theory. We show that the measure is simple and direct to compute and give accurate result for short time series. To show the significance of the measure in the analysis of practical data, we present the analysis of two EEG signals as examples.

q-bio.NC↗

arXiv2016

Measure for degree heterogeneity in complex networks and its application to recurrence network analysis

We propose a novel measure of degree heterogeneity, for unweighted and undirected complex networks, which requires only the degree distribution of the network for its computation. We show that the proposed measure can be applied to all types of network topology with ease and increases with the diversity of node degrees in the network. The measure is applied to compute the heterogeneity of synthetic (both random and scale free) and real world networks with its value normalized in the interval [0, 1]. To define the measure, we introduce a limiting network whose heterogeneity can be expressed analytically with the value tending to 1 as the size of the network N tends to infinity. We numerically study the variation of heterogeneity for random graphs (as a function of p and N) and for scale free networks with and N as variables. Finally, as a specific application, we show that the proposed measure can be used to compare the heterogeneity of recurrence networks constructed from the time series of several low dimensional chaotic attractors9thereby providing a single index to compare the structural complexity of chaotic attractors.

physics.soc-ph↗

arXiv2016

Can recurrence networks show small world property?

Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value εchosen at or just above the percolation threshold of the network are quite well understood, what happens as the threshold increases beyond the usual operational window is still not clear from a complex network perspective. The present Letter is focused mainly on the network properties at intermediate-to-large values of the recurrence threshold, for which no systematic study has been performed so far. We argue, with numerical support, that recurrence networks constructed from chaotic attractors with εequal to the usual recurrence threshold or slightly above cannot, in general, show small-world property. However, if the threshold is further increased, the recurrence network topology initially changes to a small-worldstructure and finally to that of a classical random graph as the threshold approaches the size of the strange attractor.

nlin.CD↗

arXiv2016

Accretion disc-corona and jet emission from the radio-loud narrow-line Seyfert 1 galaxy RX J1633.3+4719

We perform X-ray/ultraviolet (UV) spectral and X-ray variability studies of the radio-loud narrow-line Seyfert 1 (NLS1) galaxy RX J1633.3+4719 using XMM-Newton and Suzaku observations from 2011 and 2012. The 0.3-10 keV spectra consist of an ultrasoft component described by an accretion disc blackbody (kT_in = 39.6^{+11.2}_{-5.5} eV) and a power law due to the thermal Comptonization (Γ = 1.96^{+0.24}_{-0.31}) of the disc emission. The disc temperature inferred from the soft excess is at least a factor of 2 lower than that found for the canonical soft excess emission from radio-quiet NLS1s. The UV spectrum is described by a power law with photon index 3.05^{+0.56}_{-0.33}. The observed UV emission is too strong to arise from the accretion disc or the host galaxy, but can be attributed to a jet. The X-ray emission from RX J1633.3+4719 is variable with fractional variability amplitude $F_{\rm var}$=13.5$\pm1.0$ per cent. In contrast to radio-quiet active galactic nuclei (AGN), X-ray emission from the source becomes harder with increasing flux. The fractional rms variability increases with energy and the rms spectrum is well described by a constant disc component and a variable power-law continuum with the normalization and photon index being anticorrelated. Such spectral variability cannot be caused by variations in the absorption and must be intrinsic to the hot corona. Our finding of possible evidence for emission from the inner accretion disc, jet and hot corona from RX J1633.3+4719 in the optical to X-ray bands makes this object an ideal target to probe the disc-jet connection in AGN.

astro-ph.HE↗

arXiv2016

Uniform framework for the recurrence-network analysis of chaotic time series

We propose a general method for the construction and analysis of unweighted $ε$ - recurrence networks from chaotic time series. The selection of the critical threshold $ε_c$ in our scheme is done empirically and we show that its value is closely linked to the embedding dimension $M$. In fact, we are able to identify a small critical range $Δε$ numerically that is approximately the same for the random and several standard chaotic time series for a fixed $M$. This provides us a uniform framework for the non subjective comparison of the statistical measures of the recurrence networks constructed from various chaotic attractors. We explicitly show that the degree distribution of the recurrence network constructed by our scheme is characteristic to the structure of the attractor and display statistical scale invariance with respect to increase in the number of nodes $N$. We also present two practical applications of the scheme, detection of transition between two dynamical regimes in a time delayed system and identification of the dimensionality of the underlying system from real world data with limited number of points, through recurrence network measures. The merits, limitations and the potential applications of the proposed method have also been highlighted.

nlin.CD↗

arXiv2015

Effect of data gaps on correlation dimension computed from light curves of variable stars

Observational data, especially astrophysical data, is often limited by gaps in data that arises due to lack of observations for a variety of reasons. Such inadvertent gaps are usually smoothed over using interpolation techniques. However the smoothing techniques can introduce artificial effects, especially when non-linear analysis is undertaken. We investigate how gaps can affect the computed values of correlation dimension of the system, without using any interpolation. For this we introduce gaps artificially in synthetic data derived from standard chaotic systems, like the R{ö}ssler and Lorenz, with frequency of occurrence and size of missing data drawn from two Gaussian distributions. Then we study the changes in correlation dimension with change in the distributions of position and size of gaps. We find that for a considerable range of mean gap frequency and size, the value of correlation dimension is not significantly affected, indicating that in such specific cases, the calculated values can still be reliable and acceptable. Thus our study introduces a method of checking the reliability of computed correlation dimension values by calculating the distribution of gaps with respect to its size and position. This is illustrated for the data from light curves of three variable stars, R Scuti, U Monocerotis and SU Tauri. We also demonstrate how a cubic spline interpolation can cause a time series of Gaussian noise with missing data to be misinterpreted as being chaotic in origin. This is demonstrated for the non chaotic light curve of variable star SS Cygni, which gives a saturated D$_{2}$ value, when interpolated using a cubic spline. In addition we also find that a careful choice of binning, in addition to reducing noise, can help in shifting the gap distribution to the reliable range for D$_2$ values.

astro-ph.IM↗

arXiv2015

How does noise affect the structure of a chaotic attractor: A recurrence network perspective

We undertake a preliminary numerical investigation to understand how the addition of white and colored noise to a time series affects the topology and structure of the underlying chaotic attractor. We use the methods and measures of recurrence networks generated from the time series for this analysis. We explicitly show that the addition of noise destroys the recurrence of trajectory points in the phase space. By using the results obtained from this analysis, we go on to analyse the light curves from a dominant black hole system and show that the recurrence network measures are effective in the analysis of real world data involving noise and are capable of identifying the nature of noise contamination in a time series.

physics.data-an↗

arXiv2015

Relationship between X-ray spectral index and X-ray Eddington ratio for Mrk 335 and Ark 564

We present a comprehensive flux resolved spectral analysis of the bright Narrow line Seyfert I AGNs, Mrk~335 and Ark~564 using observations by XMM-Newton satellite. The mean and the flux resolved spectra are fitted by an empirical model consisting of two Comptonization components, one for the low energy soft excess and the other for the high energy power-law. A broad Iron line and a couple of low energies edges are required to explain the spectra. For Mrk~335, the 0.3 - 10 keV luminosity relative to the Eddington value, L{$_{X}$}/L$_{Edd}$, varied from 0.002 to 0.06. The index variation can be empirically described as $Γ$ = 0.6 log$_{10}$ L{$_{X}$}/L$_{Edd}$ + 3.0 for $0.005 < L{_{X}}/L_{Edd} < 0.04$. At $ L_{X}/L_{Edd} \sim 0.04$ the spectral index changes and then continues to follow $Γ$ = 0.6 log$_{10}$ L$_{X}$/L$_{Edd}$ + 2.7, i.e. on a parallel track. We confirm that the result is independent of the specific spectral model used by fitting the data in the 3 - 10 keV band by only a power-law and an Iron line. For Ark~564, the index variation can be empirically described as $Γ$ = 0.2 log$_{10}$ L$_{X}$/L$_{Edd}$ + 2.7 with a significantly large scatter as compared to Mrk~335. Our results indicate that for Mrk~335, there may be accretion disk geometry changes which lead to different parallel tracks. These changes could be related to structural changes in the corona or enhanced reflection at high flux levels. There does not seem to be any homogeneous or universal relationship for the X-ray index and luminosity for different AGNs or even for the same AGN.

astro-ph.GA↗

arXiv2014

Long term optical variability of bright X-ray point sources in elliptical galaxies

We present long term optical variability studies of bright X-ray sources in four nearby elliptical galaxies with {\it Chandra} Advanced CCD Imaging Spectrometer array (ACIS-S) and {\it Hubble Space Telescope (HST)} Advanced Camera for Surveys observations. Out of the 46 bright (X-ray counts $> 60$) sources that are in the common field of view of the {\it Chandra} and {\it HST} observations, 34 of them have potential optical counterparts, while the rest of them are optically dark. After taking into account of systematic errors, estimated using the field optical sources as reference, we find that four of the X-ray sources (three in NGC1399 and one in NGC1427) have variable optical counterparts at a high significance level. The X-ray luminosities of these source are $\sim 10^{38}$ $\rm ergs~s^{-1}$ and are also variable on similar time-scales. The optical variability implies that the optical emission is associated with the X-ray source itself rather than being the integrated light from a host globular cluster. For one source the change in optical magnitude is $> 0.3$, which is one of the highest reported for this class of X-ray sources and this suggests that the optical variability is induced by the X-ray activity. However, the optically variable sources in NGC1399 have been reported to have blue colours ($g - z > 1$). All four sources have been detected in the infra-red (IR) by {\it Spitzer} as point sources, and their ratio of $5.8$ to $3.6 μm$ flux are $> 0.63$ indicating that their IR spectra are like those of Active Galactic Nuclei (AGN). While spectroscopic confirmation is required, it is likely that all four sources are background AGNs. We find none of the X-ray sources having optical/IR colours different from AGNs, to be optically variable.

astro-ph.HE↗

arXiv2014

Epitaxial Growth of VO$_{2}$ by Periodic Annealing

We report the growth of ultrathin VO$_{2}$ films on rutile TiO$_{2}$ (001) substrates via reactive molecular-beam epitaxy. The films were formed by the cyclical deposition of amorphous vanadium and its subsequent oxidation and transformation to VO$_{2}$ via solid-phase epitaxy. Significant metal-insulator transitions were observed in films as thin as 2.3 nm, where a resistance change ΔR/R of 25 was measured. Low angle annular dark field scanning transmission electron microscopy was used in conjunction with electron energy loss spectroscopy to study the film/substrate interface and revealed the vanadium to be tetravalent and the titanium interdiffusion to be limited to 1.6 nm.

cond-mat.mtrl-sci↗

arXiv2013

Structural control of magnetic anisotropy in a strain driven multiferroic EuTiO3 thin film

Octahedral distortion plays a key role in engineering the physical properties of heterostructures composed of perovskite oxides. We observe a strong in-plane uniaxial magnetic anisotropy in a strain-enabled multiferroic EuTiO3 thin film epitaxially grown on a (110)o DyScO3 substrate. First principles calculations show that the magnetic anisotropy is closely correlated with the uniaxial TiO6 octahedral tilting and the ferroelectric polarization of the film, indicating potential strong magnetoelectric coupling in the strain-engineered multiferroic system.

cond-mat.mtrl-sci↗