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Register a new userSimulation and Fitting of Multi-Dimensional X-ray Data
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Astronomical data generally consists of 2 or more high-resolution axes, e.g., X,Y position on the sky or wavelength and position-along-one-axis (long-slit spectrometer). Analyzing these multi-dimension observations requires combining 3D source models (including velocity effects), instrument models, and multi-dimensional data comparison and fitting. A prototype of such a Beyond-XSPEC (Noble & Nowak, 2008) system is presented here using Chandra imag- ing and dispersed HETG grating data. Techniques used include: Monte Carlo event generation, chi-squared comparison, conjugate gradient fitting adapted to the Monte Carlo characteristics, and informative visualizations at each step. These simple baby steps of progress only scratch the surface of the computational potential that is available these days for astronomical analysis.
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X-ray spectral fitting of astronomical sources requires convolving the intrinsic spectrum or model with the instrumental response. Standard forward modeling techniques have proven success in recovering the underlying physical parameters in moderate to high signal-to-noise regimes; however, they struggle to achieve the same level of accuracy in low signal-to-noise regimes. Additionally, the use of machine learning techniques on X-ray spectra requires access to the intrinsic spectrum. Therefore, the measured spectrum must be effectively deconvolved from the instrumental response. In this note, we explore numerical methods for inverting the matrix equation describing X-ray spectral convolution. We demonstrate that traditional methods are insufficient to recover the intrinsic X-ray spectrum and argue that a novel approach is required.
An optimal estimate for Stokes parameters is derived for the situation in X-ray astronomy where the instrument has a modulation factor that varies significantly with energy but the signals are very weak or mildly polarized. For such sources, the band of analysis may be broadened in order to obtain a significant polarization measurement. Optimal estimators are provided for the cases of binned and unbinned data and applied to data such as might be obtained for faint or weakly polarized sources observed using the Imaging X-ray Polarimetry Explorer (IXPE). For a sample situation, the improvement in the minimum detectable polarization is 6-7% using a count weighted root-mean-square of the modulation factor, when compared to a count weighted average. Improving the modulation factor, such as when using a neural network approach to IXPE event tracks, can provide additional improvement up to 10-15%. The actual improvement depends on the spectral shape and the details of the instrument response functions.
We present an improved method for the precise reconstruction of cosmic ray air showers above $10^{17}$ eV with sparse radio arrays. The method is based on the comparison of predictions for radio pulse shapes by CoREAS simulations to measured pulses. We applied our method to the data of Tunka-Rex, a 1 km$^2$ radio array in Siberia operating in the frequency band of 30-80 MHz. Tunka-Rex is triggered by the air-Cherenkov detector Tunka-133 and by scintillators (Tunka-Grande). The instrument collects air-shower data since 2012. The present paper describes updated data and signal analyses of Tunka-Rex and details of a new method applied. After efficiency cuts, when Tunka-Rex reaches its full efficiency, the energy resolution of about 10% given by the new method has reached the limit of systematic uncertainties due to the calibration uncertainty and shower-to-shower fluctuations. At the same time the shower maximum reconstruction is significantly improved up to an accuracy of 35 g/cm$^2$ compared to the previous method based on the slope of the lateral distribution. We also define and now achieved conditions of the measurements, at which the shower maximum resolution of Tunka-Rex reaches a value of 25 g/cm$^2$ and becomes competitive to optical detectors. To check and validate our reconstruction and efficiency cuts we compare individual events to the reconstruction of Tunka-133. Furthermore, we compare the mean of shower maximum as a function of primary energy to the measurements of other experiments.
We perform multi-dimensional radiative transfer simulations to compute spectra for a hydrodynamical simulation of a line-driven accretion disk wind from an active galactic nucleus. The synthetic spectra confirm expectations from parameterized models that a disk wind can imprint a wide variety of spectroscopic signatures including narrow absorption lines, broad emission lines and a Compton hump. The formation of these features is complex with contributions originating from many of the different structures present in the hydrodynamical simulation. In particular, spectral features are shaped both by gas in a successfully launched outflow and in complex flows where material is lifted out of the disk plane but ultimately falls back. We also confirm that the strong Fe Kalpha line can develop a weak, red-skewed line wing as a result of Compton scattering in the outflow. In addition, we demonstrate that X-ray radiation scattered and reprocessed in the flow has a pivotal part in both the spectrum formation and determining the ionization conditions in the wind. We find that scattered radiation is rather effective in ionizing gas which is shielded from direct irradiation from the central source. This effect likely makes the successful launching of a massive disk wind somewhat more challenging and should be considered in future wind simulations.
We present the Exoplanet Simple Orbit Fitting Toolbox (ExoSOFT), a new, open-source suite to fit the orbital elements of planetary or stellar mass companions to any combination of radial velocity and astrometric data. To explore the parameter space of Keplerian models, ExoSOFT may be operated with its own multi-stage sampling approach, or interfaced with third-party tools such as emcee. In addition, ExoSOFT is packaged with a collection of post-processing tools to analyze and summarize the results. Although only a few systems have been observed with both the radial velocity and direct imaging techniques, this number will increase thanks to upcoming spacecraft and ground based surveys. Providing both forms of data enables simultaneous fitting that can help break degeneracies in the orbital elements that arise when only one data type is available. The dynamical mass estimates this approach can produce are important when investigating the formation mechanisms and subsequent evolution of substellar companions. ExoSOFT was verified through fitting to artificial data and was implemented using the Python and Cython programming languages; available for public download at https://github.com/kylemede/ExoSOFT under the GNU General Public License v3.
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