arXiv subjects

Vinay L. Kashyap

Publications and source records attributed to Vinay L. Kashyap.

At least 37 records · Page 2Linked to original sources

arXiv2023

Shocks and Photoionization of the Inner 650 AU Jet of the Interacting Binary Star R Aquarii from Multiwavelength Hubble Space Telescope Observations

Astrophysical jets are present in a range of environments, including young stellar objects, X-ray binaries, and active galactic nuclei, but their formation is still not fully understood. As one of the nearest symbiotic binary stars, R Aquarii ($D \sim 220$ pc) offers a unique opportunity to study the inner region within $\sim$ 600 AU of the jet source, which is particularly crucial to our understanding of non-relativistic jet formation and origin. We present high-angular resolution ultraviolet and optical imaging from the \emph{Hubble} Space Telescope in six emission-line regions of the inner jet. Using these observations to obtain a range of representative line ratios for our system and kinematic data derived from a comparison with previous studies, we model the shocked gas in order to determine the relative roles of shock heating and photoionization in the R Aquarii system. We find that our shock models suggest a nonzero magnetic field is needed to describe the measured line ratios. We also find that the Mg~II$λλ$2795,2802 intensities are overpredicted by our models for most of the jet regions, perhaps because of depletion onto grains or to opacity in these resonance lines.

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arXiv2023

Center to limb variation of transition region Doppler shift in active regions

Studying Doppler shifts provides deeper insights into the flow of mass and energy in the solar atmosphere. We perform a comprehensive measurement of Doppler shifts in the transition region and its center-to-limb variation (CLV) in the strong field regions ($|\textbf{B}| \geq$ 50 G) of 50 active regions (ARs), using the \ion{Si}{4} 1394~Å line recorded by the Interface Region Imaging Spectrometer(IRIS). To locate the ARs and identify strong field regions, we have used the magnetograms obtained by the Helioseismic and Magnetic Imager (HMI). We find that in strong field regions, on average, all the ARs show mean redshifts ranging between 4{--}11~ km/s, which varies with ARs. These flows show a mild CLV, with sizable magnitudes at the limb and substantial scatter at the mid-longitude range. Our observations do not support the idea that redshifts in the lower transition region (T $<\sim$ 0.1 MK) are produced by field-aligned downflows as a result of impulsive heating and warrant alternative interpretation, such as downflow of type-\rm{II} spicules in the presence of a chromospheric wall created by cooler type-\rm{I} spicules.

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arXiv2022

Identifying diffuse spatial structures in high-energy photon lists

Data from high-energy observations are usually obtained as lists of photon events. A common analysis task for such data is to identify whether diffuse emission exists, and to estimate its surface brightness, even in the presence of point sources that may be superposed. We have developed a novel non-parametric event list segmentation algorithm to divide up the field of view into distinct emission components. We use photon location data directly, without binning them into an image. We first construct a graph from the Voronoi tessellation of the observed photon locations and then grow segments using a new adaptation of seeded region growing, that we call Seeded Region Growing on Graph, after which the overall method is named SRGonG. Starting with a set of seed locations, this results in an over-segmented dataset, which SRGonG then coalesces using a greedy algorithm where adjacent segments are merged to minimize a model comparison statistic; we use the Bayesian Information Criterion. Using SRGonG we are able to identify point-like and diffuse extended sources in the data with equal facility. We validate SRGonG using simulations, demonstrating that it is capable of discerning irregularly shaped low surface-brightness emission structures as well as point-like sources with strengths comparable to that seen in typical X-ray data. We demonstrate SRGonG's use on the Chandra data of the Antennae galaxies, and show that it segments the complex structures appropriately.

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arXiv2022

Time domain methods for X-ray and gamma-ray astronomy

A variety of statistical methods for understanding variability in the time domain for low count rate X-ray and gamma-ray sources are explored. Variability can be detected using nonparametric (Anderson-Darling and overdispersion tests) and parametric (sequential likelihood-based tests) tools. Once detected, variability can be characterized by nonparametric (autocorrelation function, structure function,wavelet analysis) and parametric (multiple change point model such as Bayesian Blocks, integer autoregressive models, C-statistic and Poisson regression) methods. New multidimensional variability detection approaches are outlined. Software packages designed for high energy data analysis are deficient but tools are available in the R statistical software environment. Most of the methods presented here are not commonly used in high energy astronomy.

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arXiv2021

Hydrodynamics of small transient brightenings in Solar corona

Small scale transients occur in the Solar corona at much higher frequencies than flares and play a significant role in coronal dynamics. Here we study three well-identified transients discovered by Hi-C and also detected by the EUV channels of Atmospheric Imaging Assembly (AIA) on board Solar Dynamics Observatory (SDO). We use 0-D enthalpy-based hydrodynamical simulations and produce synthetic light curves to compare with AIA observations. We have modeled these transients as loops of ~ 1.0~Mm length depositing energies ~ 10^23 ergs in ~ 50 seconds. The simulated synthetic light curves show reasonable agreement with the observed light curves. During the initial phase, conduction flux from the corona dominates over the radiation, like impulsive flaring events. Our results further show that the time-integrated net enthalpy flux is positive, hence into the corona. The fact that we can model the observed light curves of these transients reasonably well by using the same physics as those for nanoflares, microflares, and large flares, suggests that these transients may have a common origin.

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arXiv2021

Concordance: In-flight Calibration of X-ray Telescopes without Absolute References

We describe a process for cross-calibrating the effective areas of X-ray telescopes that observe common targets. The targets are not assumed to be "standard candles" in the classic sense, in that we assume that the source fluxes have well-defined, but {\it a priori} unknown values. Using a technique developed by Chen et al. (2019, arXiv:1711.09429) that involves a statistical method called {\em shrinkage estimation}, we determine effective area correction factors for each instrument that brings estimated fluxes into the best agreement, consistent with prior knowledge of their effective areas. We expand the technique to allow unique priors on systematic uncertainties in effective areas for each X-ray astronomy instrument and to allow correlations between effective areas in different energy bands. We demonstrate the method with several data sets from various X-ray telescopes.

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arXiv2021

eBASCS: Disentangling Overlapping Astronomical Sources II, using Spatial, Spectral, and Temporal Information

The analysis of individual X-ray sources that appear in a crowded field can easily be compromised by the misallocation of recorded events to their originating sources. Even with a small number of sources, that nonetheless have overlapping point spread functions, the allocation of events to sources is a complex task that is subject to uncertainty. We develop a Bayesian method designed to sift high-energy photon events from multiple sources with overlapping point spread functions, leveraging the differences in their spatial, spectral, and temporal signatures. The method probabilistically assigns each event to a given source. Such a disentanglement allows more detailed spectral or temporal analysis to focus on the individual component in isolation, free of contamination from other sources or the background. We are also able to compute source parameters of interest like their locations, relative brightness, and background contamination, while accounting for the uncertainty in event assignments. Simulation studies that include event arrival time information demonstrate that the temporal component improves event disambiguation beyond using only spatial and spectral information. The proposed methods correctly allocate up to 65% more events than the corresponding algorithms that ignore event arrival time information. We apply our methods to two stellar X-ray binaries, UV Cet and HBC515 A, observed with Chandra. We demonstrate that our methods are capable of removing the contamination due to a strong flare on UV Cet B in its companion approximately 40 times weaker during that event, and that evidence for spectral variability at timescales of a few ks can be determined in HBC515 Aa and HBC515 Ab.

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arXiv2021

Change point detection and image segmentation for time series of astrophysical images

Many astrophysical phenomena are time-varying, in the sense that their intensity, energy spectrum, and/or the spatial distribution of the emission suddenly change. This paper develops a method for modeling a time series of images. Under the assumption that the arrival times of the photons follow a Poisson process, the data are binned into 4D grids of voxels (time, energy band, and x-y coordinates), and viewed as a time series of non-homogeneous Poisson images. The method assumes that at each time point, the corresponding multi-band image stack is an unknown 3D piecewise constant function including Poisson noise. It also assumes that all image stacks between any two adjacent change points (in time domain) share the same unknown piecewise constant function. The proposed method is designed to estimate the number and the locations of all the change points (in time domain), as well as all the unknown piecewise constant functions between any pairs of the change points. The method applies the minimum description length (MDL) principle to perform this task. A practical algorithm is also developed to solve the corresponding complicated optimization problem. Simulation experiments and applications to real datasets show that the proposed method enjoys very promising empirical properties. Applications to two real datasets, the XMM observation of a flaring star and an emerging solar coronal loop, illustrate the usage of the proposed method and the scientific insight gained from it.

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arXiv2020

M51-ULS-1b: The First Candidate for a Planet in an External Galaxy

Do external galaxies host planetary systems? Many lines of reasoning suggest that the answer must be 'yes'. In the foreseeable future, however, the question cannot be answered by the methods most successful in our own Galaxy. We report on a different approach which focuses on bright X-ray sources (XRSs). M51-ULS-1b is the first planet candidate to be found because it produces a full, short-lived eclipse of a bright XRS. M51-ULS-1b has a most probable radius slightly smaller than Saturn. It orbits one of the brightest XRSs in the external galaxy M51, the Whirlpool Galaxy, located 8.6 Megaparsecs from Earth. It is the first candidate for a planet in an external galaxy. The binary it orbits, M51-ULS-1, is young and massive. One of the binary components is a stellar remnant, either a neutron star (NS) or black hole (BH), and the other is a massive star. X-ray transits can now be used to discover more planets in external galaxies and also planets orbiting XRSs inside the Milky Way.

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arXiv2019

White paper for Chandra cool attitude targets (CAT): Stellar activity with TESS and Chandra

All cool stars show magnetic activity, and X-ray emission is the hallmark of this activity. Gaining an understanding of activity aids us in answering fundamental questions about stellar astrophysics and in determining the impact of activity on the exoplanets that orbit these stars. Stellar activity is driven by magnetic fields, which are ultimately powered by convection and stellar rotation. However, the resulting dynamo properties heavily depend on the stellar interior structure and are far from being understood. X-ray radiation can evaporate exoplanet atmospheres and damage organic materials on the planetary surface, reducing the probability that life can form or be sustained, but also provides an important source of energy for prebiotic chemical reactions. Over the next two years, the TESS mission will deliver a catalog of the closest exoplanets, along with rotation periods and activity diagnostics for millions of stars, whether or not they have a planet. We propose to include all cool stars that are TESS targets and bright enough for Chandra observations, as determined by their detection and flux in the ROSAT all-sky survey (RASS), to the list of Chandra Cool Attitude Targets (CATs). For each target, the signal will be sufficient to fit the coronal plasma with at least two temperature components, and compare abundances of groups of elements with low, medium, or high first ionization potential. Similar to the known relation between X-ray luminosity $L_X$ and rotation period, we can correlate stellar properties with coronal temperatures and abundances to constrain models for stellar activity, coronal heating, and stellar dynamos. Detailed X-ray characterization for even a subset of planet-hosting systems would dramatically advance our knowledge of what impact these emissions have on orbiting planets.

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arXiv2019

Multidimensional Data Driven Classification of Emission-line Galaxies

We propose a new soft clustering scheme for classifying galaxies in different activity classes using simultaneously 4 emission-line ratios; log([NII ]/Ha), log([SII]/Ha), log([OI]/Ha) and log([OIII]/Hb). We fit 20 multivariate Gaussian distributions to the 4-dimensional distribution of these lines obtained from the Sloan Digital Sky Survey (SDSS) in order to capture local structures and subsequently group the multivariate Gaussian distributions to represent the complex multi-dimensional structure of the joint distribution of galaxy spectra in the 4 dimensional line ratio space. The main advantages of this method are the use of all four optical-line ratios simultaneously and the adoption of a clustering scheme. This maximises the available information, avoids contradicting classifications, and treats each class as a distribution resulting in soft classification boundaries and providing the probability for an object to belong to each class. We also introduce linear multi-dimensional decision surfaces using support vector machines based on the classification of our soft clustering scheme. This linear multi-dimensional hard clustering technique shows high classification accuracy with respect to our soft-clustering scheme.

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arXiv2019

Pointing Chandra Toward the Extreme Ultraviolet Fluxes of Very Low-Mass Stars

The X-ray and EUV emission of stars plays a key role in the loss and evolution of the atmospheres of their planets. The coronae of dwarf stars later than M6 appear to behave differently to those of earlier spectral types and are more X-ray dim and radio bright. Too faint to have been observed by the Extreme Ultraviolet Explorer, their EUV behavior is currently highly uncertain. We have devised a method to use the Chandra X-ray Observatory High Resolution Camera to provide a measure of EUV emission in the 50-170 Å range and have applied it to the M6.5 dwarf LHS 248 in a pilot 10 ks exposure. Analysis with model spectra using simple, idealised coronal emission measure distributions inspired by an analysis of Chandra HETG spectra of the M5.5 dwarf Proxima Cen and results from the literature, finds greatest consistency with a very shallow emission measure distribution slope, $DEM \propto T^{3/2}$ or shallower, in the range $\log T=5.5$-$6.5$. Within $2σ$ confidence, a much wider range of slopes can be accommodated. Model spectra constrained by this method can provide accurate (within a factor of 2-4) synthesis and extrapolation of EUV spectra for wavelengths $<400$-500 Å. At longer wavelengths models are uncertain by an order of magnitude or more, and depend on the details of the emission measure distribution at temperatures $\log T < 5.5$. The method is sensitive to possible incompleteness of plasma radiative loss models in the 30 170 Å range for which re-examination would be warranted.

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arXiv2018

Calibration Concordance for Astronomical Instruments via Multiplicative Shrinkage

Calibration data are often obtained by observing several well-understood objects simultaneously with multiple instruments, such as satellites for measuring astronomical sources. Analyzing such data and obtaining proper concordance among the instruments is challenging when the physical source models are not well understood, when there are uncertainties in "known" physical quantities, or when data quality varies in ways that cannot be fully quantified. Furthermore, the number of model parameters increases with both the number of instruments and the number of sources. Thus, concordance of the instruments requires careful modeling of the mean signals, the intrinsic source differences, and measurement errors. In this paper, we propose a log-Normal hierarchical model and a more general log-t model that respect the multiplicative nature of the mean signals via a half-variance adjustment, yet permit imperfections in the mean modeling to be absorbed by residual variances. We present analytical solutions in the form of power shrinkage in special cases and develop reliable MCMC algorithms for general cases. We apply our method to several data sets obtained with a variety of X-ray telescopes such as Chandra. We demonstrate that our method provides helpful and practical guidance for astrophysicists when adjusting for disagreements among instruments.

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arXiv2018

Incorporating Uncertainties in Atomic Data Into the Analysis of Solar and Stellar Observations: A Case Study in Fe XIII

Information about the physical properties of astrophysical objects cannot be measured directly but is inferred by interpreting spectroscopic observations in the context of atomic physics calculations. Ratios of emission lines, for example, can be used to infer the electron density of the emitting plasma. Similarly, the relative intensities of emission lines formed over a wide range of temperatures yield information on the temperature structure. A critical component of this analysis is understanding how uncertainties in the underlying atomic physics propagates to the uncertainties in the inferred plasma parameters. At present, however, atomic physics databases do not include uncertainties on the atomic parameters and there is no established methodology for using them even if they did. In this paper we develop simple models for the uncertainties in the collision strengths and decay rates for Fe XIII and apply them to the interpretation of density sensitive lines observed with the EUV Imagining spectrometer (EIS) on Hinode. We incorporate these uncertainties in a Bayesian framework. We consider both a pragmatic Bayesian method where the atomic physics information is unaffected by the observed data, and a fully Bayesian method where the data can be used to probe the physics. The former generally increases the uncertainty in the inferred density by about a factor of 5 compared with models that incorporate only statistical uncertainties. The latter reduces the uncertainties on the inferred densities, but identifies areas of possible systematic problems with either the atomic physics or the observed intensities.

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arXiv2018

Energetics of Hi-C EUV Brightenings

We study the thermal structure and energetics of the point-like EUV brightenings within a system of fan loops observed in the active region \textsl{AR~11520}. These brightenings were simultaneously observed on 2012 July 11 by the HIgh-resolution Coronal (Hi-C) imager and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). We identified 27 brightenings by automatically determining intensity enhancements in both Hi-C and AIA ~193~Å light curves. The energetics of these brightenings were studied by using the Differential Emission Measure (DEM) diagnostics. The DEM weighted temperatures of these transients are in the range $\log{T} (K) = 6.2 - 6.6$ with radiative energies ${\approx}10^{24-25}$~ergs and densities ${\approx}$ a few times $10^{9}$~cm$^{-3}$. To the best of our knowledge, these are the smallest brightenings in EUV ever detected. We used these results to determine the mechanism of energy loss in these brightenings. Our analysis reveals that the dominant mechanism of energy loss for all the identified brightenings is conduction rather than radiation.

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arXiv2017

Bayesian Estimates of Astronomical Time Delays between Gravitationally Lensed Stochastic Light Curves

The gravitational field of a galaxy can act as a lens and deflect the light emitted by a more distant object such as a quasar. Strong gravitational lensing causes multiple images of the same quasar to appear in the sky. Since the light in each gravitationally lensed image traverses a different path length from the quasar to the Earth, fluctuations in the source brightness are observed in the several images at different times. The time delay between these fluctuations can be used to constrain cosmological parameters and can be inferred from the time series of brightness data or light curves of each image. To estimate the time delay, we construct a model based on a state-space representation for irregularly observed time series generated by a latent continuous-time Ornstein-Uhlenbeck process. We account for microlensing, an additional source of independent long-term extrinsic variability, via a polynomial regression. Our Bayesian strategy adopts a Metropolis-Hastings within Gibbs sampler. We improve the sampler by using an ancillarity-sufficiency interweaving strategy and adaptive Markov chain Monte Carlo. We introduce a profile likelihood of the time delay as an approximation of its marginal posterior distribution. The Bayesian and profile likelihood approaches complement each other, producing almost identical results; the Bayesian method is more principled but the profile likelihood is simpler to implement. We demonstrate our estimation strategy using simulated data of doubly- and quadruply-lensed quasars, and observed data from quasars Q0957+561 and J1029+2623.

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arXiv2016

Detecting Relativistic X-ray Jets in High-Redshift Quasars

We analyze Chandra X-ray images of a sample of 11 quasars that are known to contain kiloparsec scale radio jets. The sample consists of five high-redshift (z >= 3.6) flat-spectrum radio quasars, and six intermediate redshift (2.1 < z < 2.9) quasars. The dataset includes four sources with integrated steep radio spectra and seven with flat radio spectra. A total of 25 radio jet features are present in this sample. We apply a Bayesian multi-scale image reconstruction method to detect and measure the X-ray emission from the jets. We compute deviations from a baseline model that does not include the jet, and compare observed X-ray images with those computed with simulated images where no jet features exist. This allows us to compute p-value upper bounds on the significance that an X- ray jet is detected in a pre-determined region of interest. We detected 12 of the features unambiguously, and an additional 6 marginally. We also find residual emission in the cores of 3 quasars and in the background of 1 quasar that suggest the existence of unresolved X-ray jets. The dependence of the X-ray to radio luminosity ratio on redshift is a potential diagnostic of the emission mechanism, since the inverse Compton scattering of cosmic microwave background photons (IC/CMB) is thought to be redshift dependent, whereas in synchrotron models no clear redshift dependence is expected. We find that the high-redshift jets have X-ray to radio flux ratios that are marginally inconsistent with those from lower redshifts, suggesting that either the X-ray emissions is due to the IC/CMB rather than the synchrotron process, or that high redshift jets are qualitatively different.

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arXiv2015

Detecting Abrupt Changes in the Spectra of High-Energy Astrophysical Sources

Variable-intensity astronomical sources are the result of complex and often extreme physical processes. Abrupt changes in source intensity are typically accompanied by equally sudden spectral shifts, i.e., sudden changes in the wavelength distribution of the emission. This article develops a method for modeling photon counts collected from observation of such sources. We embed change points into a marked Poisson process, where photon wavelengths are regarded as marks and both the Poisson intensity parameter and the distribution of the marks are allowed to change. To the best of our knowledge this is the first effort to embed change points into a marked Poisson process. Between the change points, the spectrum is modeled non-parametrically using a mixture of a smooth radial basis expansion and a number of local deviations from the smooth term representing spectral emission lines. Because the model is over parameterized we employ an $\ell_1$ penalty. The tuning parameter in the penalty and the number of change points are determined via the minimum description length principle. Our method is validated via a series of simulation studies and its practical utility is illustrated in the analysis of the ultra-fast rotating yellow giant star known as FK Com.

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