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One of the main goals of modern observational cosmology is to map the large scale structure of the Universe. A potentially powerful approach for doing this would be to exploit three-dimensional spectral maps, i.e. the specific intensity of extragalactic light as a function of wavelength and direction on the sky, to measure spatial variations in the total extragalactic light emission and use these as a tracer of the clustering of matter. A main challenge is that the observed intensity as a function of wavelength is a convolution of the source luminosity density with the rest-frame spectral energy distribution. In this paper, we introduce the method of spectral deconvolution as a way to invert this convolution and extract the clustering information. We show how one can use observations of the mean and angular fluctuations of extragalactic light as a function of wavelength, assuming statistical isotropy, to reconstruct jointly the rest-frame spectral energy distribution of the sources and the source spatial density fluctuations. This method is more general than the well known line mapping technique as it does not rely on spectral lines in the emitted spectra. After introducing the general formalism, we discuss its implementation and limitations. This formal paper sets the stage for future more practical studies.
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The new generation of radio interferometers is characterized by high sensitivity, wide fields of view and large fractional bandwidth. To synthesize the deepest images enabled by the high dynamic range of these instruments requires us to take into account the direction-dependent Jones matrices, while estimating the spectral properties of the sky in the imaging and deconvolution algorithms. In this paper we discuss and implement a wide-band wide-field spectral deconvolution framework (DDFacet) based on image plane faceting, that takes into account generic direction-dependent effects. Specifically, we present a wide-field co-planar faceting scheme, and discuss the various effects that need to be taken into account to solve for the deconvolution problem (image plane normalization, position-dependent PSF, etc). We discuss two wide-band spectral deconvolution algorithms based on hybrid matching pursuit and sub-space optimisation respectively. A few interesting technical features incorporated in our imager are discussed, including baseline dependent averaging, which has the effect of improving computing efficiency. The version of DDFacet presented here can account for any externally defined Jones matrices and/or beam patterns.
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.
Olivine and pyroxene are important mineral end-members for studying the sur-face material compositions of mafic bodies. The profiles of visible and near-infraredspectra of olivine-orthopyroxene mixtures systematically varied with their compositionratios. In our experiments, we combine the RELAB spectral database with a new spec-tral data obtained from some assembled olivine-orthopyroxene mixtures. We found thatthe commonly-used band area ratio (BAR, Cloutis et al. 1986) does not work well onour newly obtained spectral data. To investigate this issue, an empirical procedure basedon fitted results by modified Gaussian model is proposed to analyze the spectral curves.Following the new empirical procedure, the end-member abundances can be estimatedwith a 15% accuracy with some prior mineral absorption features. In addition, the mix-ture samples configured in our experiments are also irradiated by pulsed lasers to simulateand investigate the space weathering effects. Spectral deconvolution results confirm thatlow-content olivine on celestial bodies are difficult to measure and estimate. Therefore,the olivine abundance of space weathered materials may be underestimated from remotesensing data. This study may be used to quantify the spectral relationship of olivine-orthopyroxene mixtures and further reveal their correlation between the spectra of ordi-nary chondrites and silicate asteroids.
We apply the iterative MCS deconvolution method (ISMCS) to near-IR HST archives data of seven gravitationally lensed quasars currently monitored by the COSMOGRAIL collaboration: HE 0047-1756, RX J1131-1231, SDSS J1138+0314, SDSS J1155+6346, SDSS J1226-0006, WFI J2026-4536 and HS 2209+1914. In doing so, we obtain relative positions for the lensed images and shape parameters for the light distribution of the lensing galaxy in each system. The lensed image positions are derived with 1-2 mas accuracy. To predict time delays and to test the ability of simple mass models to reproduce the observed configuration, isothermal and de Vaucouleurs mass models are calculated for the whole sample using state-of-the-art modeling techniques. The effect of the lens environment on the lens mass models is taken into account with a shear term. Doubly imaged quasars are equally well fitted by each of these models. A large amount of shear is necessary to reproduce SDSS J1155+6346 and SDSS J1226-006. In the latter case, we identify a nearby galaxy as the dominant source of shear. The quadruply imaged quasar SDSS J1138+0314 is well reproduced by simple lens models, which is not the case for the two other quads, RX J1131-1231 and WFI J2026-4536. This might be the signature of astrometric perturbations due to massive substructures in the lensing galaxy unaccounted for by the models. Other possible explanations are also presented.
We develop a new method for deconvolving the smearing effect of the survey window in the analysis of the galaxy multipole power spectra from a redshift survey. This method is based on the deconvolution theorem, and is compatible with the use of the fast Fourier transform. It is possible to measure the multipole power spectra deconvolved from the window effect efficiently. Applying this method to the luminous red galaxy sample of the Sloan Digital Sky Survey data release 7 as well as mock catalogues, we demonstrate how the method works properly. Using this deconvolution technique, the amplitude of the multipole power spectrum is corrected. Besides, the covariance matrices of the deconvolved power spectra get quite close to the diagonal form. This is also advantageous in the study of the BAO signature.
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