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It is well-known that when an astronomical image is collected by a telescope, the measured intensities at pixels near the edge of the image may depend on the intensity of the object outside of the field of view (FOV) of the instrument. This makes the deconvolution of astronomical images troublesome. Standard approaches for solving this problem artificially extend the object outside the FOV via the imposition of boundary conditions (BCs). Unfortunately, in many instances the artificially extended object has little in common with the object itself outside of the FOV. This is most pronounced in the case of objects close to the boundary of the image and/or extended objects not completely contained in the image domain. In such cases, an inaccurate extension of the image outside of the FOV can introduce non-physical edge effects near the boundary that can degrade the quality of the reconstruction. For example, if the BCs used result in an extended image that is discontinuous at the boundary, these edge effects take the form of ripples (Gibbs oscillations). In this paper, we extend to least-squares (LS) algorithms a method recently proposed by Bertero & Boccacci (2005, A&A, 437, 369) in the context of the Richardson-Lucy (RL) algorithm for the restoration of images contaminated by Poissonian noise. The most important characteristic of the proposed approach is that it does not impose any kind of artificial BCs and is therefore free from edge effects. For this reason it can be considered the natural method for the restoration of images via LS algorithms.

In this paper we consider the problem of the limits concerning the physical information that can be extracted from the analysis of one or more time series (light curves) typical of astrophysical objects. On the basis of theoretical considerations and numerical simulations, we show that with no a priori physical model there are not many possibilities to obtain interpretable results. For this reason, the practice to develop more and more sophisticated statistical methods of time series analysis is not productive. Only techniques of data analysis developed in a specific physical context can be expected to provide useful results. The field of stochastic dynamicsappears to be an interesting framework for such an approach. In particular, it is shown that modelling the experimental time series by means of the stochastic differential equations (SDE) represents a valuable tool of analysis. For example, besides a more direct connection between data analysis and theoretical models, in principle the use of SDE permits the analysis of a continuous signal independent of the characteristics (e.g., frequency, regularity, ...) of the sampling with which the experimental time series were obtained. In this respect, an efficient approach based on the extended Kalman filter technique is presented. Its performances and limits are discussed and tested through numerical experiments. Freely downloadable software is made available.

We consider the estimation of the regularization parameter for the simultaneous deblurring of multiple noisy images via Tikhonov regularization. We approach the problem in three ways. We first reduce the problem to a single-image deblurring for which the regularization parameter can be estimated through a classic generalized cross-validation (${\rm GCV}$) method. A modification of this function is used for correcting the undersmoothing typical of the original technique. With a second method, we minimize an average least-squares fit to the images and define a new ${\rm GCV}$function. In the last approach, we use the classical ${\rm GCV}$on a single higher-dimensional image obtained by concatenating all the images into a single vector. With a reliable estimator of the regularization parameter, one can fully exploit the excellent computational characteristics typical of direct deblurring methods, which, especially for large images, makes them competitive with the more flexible but much slower iterative algorithms. The performance of the techniques is analyzed through numerical experiments. We find that under the independent homoscedastic and Gaussian assumptions made on the noise, the three approaches provide almost identical results with the first single image providing the practical advantage that no new software is required and the same image can be used with other deblurring algorithms.

We consider the simultaneous deblurring of a set of noisy images whose point spread functions are different but known and spatially invariant, and with Gaussian noise. Currently available iterative algorithms that are typically used for this type of problem are computationally expensive, which makes their application for very large images impractical. We present a simple extension of a classical least-squares (LS) method where the multi-image deblurring is efficiently reduced to a computationally efficient single-image deblurring. In particular, we show that it is possible to remarkably improve the ill-conditioning of the LS problem by means of stable operations on the corresponding normal equations, which in turn speed up the convergence rate of the iterative algorithms. The performance and limitations of the method are analyzed through numerical simulations. Its connection with a column weighted least-squares approach is also considered in an appendix.

In this paper we comment on the results concerning the performances of matched filters, scale adaptive filters and Mexican hat wavelet that recently appeared in literature in the context of point source detection in Cosmic Microwave Background maps. In particular, we show that, contrary to what has been claimed, the use of the matched filters still appear to be the most reliable and efficient method to disantangle point sources from the backgrounds, even when using detection criterion that, differently from the classic $n\sigma$thresholding rule, takes into account not only the height of the peaks in the signal corresponding to the candidate sources but also their curvature.

In this second paper in a series dedicated to developing efficient numerical techniques for the deblurring Cosmic Microwave Background (CMB) maps, we consider the case of asymmetric point spread functions (PSF). Although conceptually this problem is not different from the symmetric case, there are important differences from the computational point of view because it is no longer possible to use some of the efficient numerical techniques that work with symmetric PSFs. We present procedures that permit the use of efficient techniques even when this condition is not met. In particular, two methods are considered: a procedure based on a Kronecker approximation technique that can be implemented with the numerical methods used with symmetric PSFs but that has the limitation of requiring only mildly asymmetric PSFs. The second is a variant of the classic Tikhonov technique that works even with very asymmetric PSFs but that requires discarding the edges of the maps. We provide details for efficient implementations of the algorithms. Their performance is tested on simulated CMB maps.

Digital deblurring of images is an important problem that arises in multifrequency observations of the Cosmic Microwave Background (CMB) where, because of the width of the point spread functions (PSF), maps at different frequencies suffer a different loss of spatial resolution. Deblurring is useful for various reasons: first, it helps to restore high frequency components lost through the smoothing effect of the instrument's PSF; second, emissions at various frequencies observed with different resolutions can be better studied on a comparable resolution; third, some map-based component separation algorithms require maps with similar level of degradation. Because of computational efficiency, deblurring is usually done in the frequency domain. But this approach has some limitations as it requires spatial invariance of the PSF, stationarity of the noise, and is not flexible in the selection of more appropriate boundary conditions. Deblurring in real space is more flexible but usually not used because of its high computational cost. In this paper (the first in a series on the subject) we present new algorithms that allow the use of real space deblurring techniques even for very large images. In particular, we consider the use of Tikhonov deblurring of noisy maps with applications to PLANCK. We provide details for efficient implementations of the algorithms. Their performance is tested on Gaussian and non-Gaussian simulated CMB maps, and PSFs with both circular and elliptical symmetry. Matlab code is made available.

Point-source contamination in high-precision Cosmic Microwave Background (CMB) maps severely affects the precision of cosmological parameter estimates. Among the methods that have been proposed for source detection, the family of pseudo-filters optimizes a measure of signal-to-noise and amplitude-scale relation. In this paper we show that these filters are in fact only restrictive cases of a more general class of matched filters that optimize signal-to-noise ratio and that have, in general, better source detection capabilities, especially for lower amplitude sources. These conclusions are confirmed by some numerical experiments.

It is the purpose of the paper to describe the virtues of time-frequency methods for signal processing applications, having astronomical time series in mind. Different methods are considered and their potential usefulness respectively drawbacks are discussed and illustrated by examples. As areas where one can hope for a successful application of joint time-frequency analysis (JTFA), we describe specifically the problem of signal denoising as well as the question of signal separation which allows to separate signals (possibly overlapping in time or frequency, but) which are living on disjoint parts of the time-frequency plane. Some recipes for practical use of the algorithms are also provided.

The colliding-wind binary system WR 140(HD 193793, WC7pd+O4-5, P= 7.94 yr) was monitored in the ultraviolet by IUEfrom 1979 to 1994 in 35 short-wavelength high-resolution spectra. An absorption-line radial-velocity solution is obtained from the photospheric lines of the O component, by comparison with a single O star. The resulting orbital parameters, e= 0.87 ±0.05, ω= 31° ±9° and $K_{\rm O star}$= 25 ±15 km s-1, confirm the large eccentricity of the orbit, within the uncertainties of previous optical studies. This brings the weighted mean UV-optical eccentricity to e= 0.85 ±0.04. Occultation of the O-star light by the WC wind and the WC+O colliding-wind region results into orbital modulation of the P-Cygni profiles of the C ii, C ivand Si ivresonance lines. Near periastron passage, the absorption troughs of those resonance-line profiles increase abruptly in strength and width, followed by a gradual decrease. In particular, near periastron the blueblack-edges of the P-Cygni absorption troughs shift to larger outflow velocities. We discuss that the apparently larger wind velocity and velocity dispersion observed at periastron could be explained by four phenomena: (i) geometrical resonance-line eclipse effects being the main cause of the observed UV spectral variability, enhanced by sightline crossing of the turbulent wind-wind collision zone; (ii) the possibility of an orbital-plane enhanced WC7 stellar wind; (iii) possible common-envelope acceleration by the combined WC and O stellar radiation fields; and (iv) possible enhanced radiatively driven mass loss due to tidal stresses, focused along the orbiting line of centers.

This paper deals with the definition of the input fluxes used for the calibration of the IUE Final Archive. The method adopted consists in the determination of the shapeof the detector's sensitivity curves using IUE low resolution observations with model fluxes of the DA white dwarf G191-B2B. A scale factorwas then determined so that the IUE observations of some bright OAO-2 standards match the original measurements from Meade ([CITE]) in the spectral region 2100-2300 Å. The ultraviolet fluxes of six standard stars used as input for the Final Archive photometric calibration together with the model fluxes of G191-B2B normalized to the OAO-2 scale are given. A comparison with the independent FOS calibration shows that the IUE flux scale for the Ultraviolet is 7.2% lower. We consider this mainly to be caused by the different normalization procedures. It is shown that the present flux calibration applies to spectra processed with the INESlow resolution extraction software.

Mid-infrared images of the Seyfert 1 galaxy Mrk 279obtained with the ISO satellite are presented together with the results of a one-year monitoring campaign of the 2.5-11.7 μm spectrum. Contemporaneous optical photometric and spectrophotometric observations are also presented. The galaxy appears as a point-like source at the resolution of the ISOCAM instrument (4-5″). The 2.5-11.7 μm average spectrum of the nucleus in Mrk 279shows a strong power law continuum with $\alpha = -0.80\pm0.05$(${ F_{\nu} \propto \nu^{\alpha}}$) and weak PAH emission features. The Mrk 279spectral energy distribution shows a mid-IR bump, which extends from 2 to 15-20 μm. The mid-IR bump is consistent with thermal emission from dust grains at a distance of $\ga 100$lt-d. No significant variations of the mid-IR flux have been detected during our observing campaign, consistent with the relatively low amplitude (~10% rms) of the optical variability during the campaign. The time delay for Hβline emission in response to the optical continuum variations is $\tau = 16.7^{+5.3}_{-5.6}$days, consistent with previous measurements.

In this paper we document the results of the study which led to the ripple correction and absolute calibration algorithms applied to the high resolution spectra processed with the  software for the Final Archive of the  Project. In this analysis, based on a very large number of spectra, we find that both the Kand αparameters (not only the former as previously believed) vary with order number. This fact, together with the finding that the central peaks of the blaze function vary also as a function of the THDA temperature (for the SWP camera) and of the date of observations (for the LWP and LWR cameras), makes the ripple correction algorithm more complex than previously considered but, at the same time, considerably more reliable. As for the high resolution absolute calibration, the method followed is similar to the one implemented in . The internal accuracy of the high resolution calibration is about 4%. We note that the ripple correction and absolute calibration algorithms here described apply also to  data processed and distributed with the  system.

This paper discusses the overall quality of  high resolution data processed with the software in terms of flux and wavelength accuracy. It also describes the processing of  high resolution spectra within the framework of the ESA “IUE Newly Extracted Spectra” () System. This system provides the  high resolution data in two formats: the high resolution “concatenated” spectra, in which the spectral orders are connected, eliminating the overlap regions through a procedure designed to optimize the signal-to-noise ratio at the edges of the orders, and the “rebinned” spectra, i.e. the high resolution concatenated spectra resampled into the low resolution wavelength domain. Our study reveals the existence of a significant discrepancy in the wavelength scales of short and long wavelength  high resolution spectra. The  processing applies a correction of +17.7 km s-1to the wavelength scale of the high resolution SWP spectra in order to provide an internally consistent velocity scale. Similarly, suitable corrections have been applied to long wavelength small aperture spectra. The new wavelength scale is, within the errors, in good agreement with the optical velocity scale.

We present the extraction and processing of the  Low Dispersion spectra within the framework of the ESA "IUE Newly Extracted Spectra” () System. Weak points of , the optimal extraction implementation to produce the  output products (extracted spectra) are discussed, and the procedures implemented in  to solve these problems are outlined. The more relevant modifications are: 1) the use of a new noise model, 2) a more accurate representation of the spatial profile of the spectrum and 3) a more reliable determination of the background. The  extraction also includes a correction for the contamination by solar light in long wavelength spectra. Examples showing the improvements obtained in with respect to are described. Finally, the linearity and repeatability characteristics of  data are evaluated and the validity of the errors provided in the extraction is discussed.

We present a wide multi-wavelength database of most observations of the quasar 3C 273 obtained during the last 30 years. This database is the most complete set of observations available for an active galactic nucleus (AGN). It contains nearly 20 000 observations grouped together into 70 light curves covering 16 orders of magnitude in frequency from the radio to the γ-ray domain. The database is constituted of many previously unpublished observations and of most publicly available data gathered in the literature and on the World Wide Web (WWW). It is complete to the best of our knowledge, except in the optical (UBV) domain where we chose not to add all observations from the literature. In addition to the photometric data, we present the spectra of 3C 273 obtained by the International Ultraviolet Explorer (IUE) satellite. In the X-ray domain, we used the spectral fit parameters from the literature to construct the light curves. Apart from describing the data, we show the most representative light curves and the average spectrum of 3C 273. The database is available on the WWW in a homogeneous and clear form and we wish to update it regularly by adding new observations.

We generalize a reliable and efficient algorithm, to deal with the case of spatially-variant PSFs. The algorithm was developed in the context of a least-square (LS) approach, to estimate the image corresponding to a given object when a set of observed images are available with different and spatially-invariant PSFs. Noise is assumed additive and Gaussian. The proposed algorithm allows the use of the classical LS single-image deblurring techniques for the simultaneous deblurring of the observed images, with obvious advantages both for computational cost and ease of implementation. Its performance and limitations, also in the case of Poissonian noise, are analyzed through numerical simulations. In an appendix we also present a novel, computationally efficient deblurring algorithm that is based on a Singular Value Decomposition (SVD) approximation of the variant PSF, and which is usable with any standard space-invariant direct deblurring algorithm. The corresponding Matlab code is made available.

We describe here the structure under which the IUE Project will leave its archive at the completion of the distribution system and final data processing, within the INES system.The INES system is a total system, which comprises both the data in their final bulk processing mode for direct application to scientific analysis, as well as the software driving the distributed service for data retrieval directly by the end user.As a consequence of the expected long-term usage and support needs, it has been designed to require minimum maintenance costs and will not suffer single point failures because of the distributed nature. Integration of the INES system in a more general multi-wavelength archive for specialized analysis is anticipated tobe relatively easy, so further evolution of the data availabilitywill be driven fully by the users community and will evolve as thedata needs of the community develop. The long term responsibilitywill be transferred from ESA to the astronomical community throughthe establishment of the INES Principal Centre at the LAEFF Instituteof INTA in Spain.

This paper discusses the overall quality of IUE high resolution data processed with the NEWSIPSsoftware in terms of flux and wavelength accuracy. It also describes the processing of NEWSIPS high resolution spectra within the framework of the ESA ``IUE Newly Extracted Spectra'' (INES) System. This system provides the IUE high resolution data in two formats: the high resolution ``concatenated'' spectra, in which the spectral orders are connected, eliminating the overlap regions through a procedure designed to optimize the signal-to-noise ratio at the edges of the orders, and the ``rebinned'' spectra, i.e. the high resolution concatenated spectra resampled into the low resolution wavelength domain. Our study reveals the existence of a significant discrepancy in the wavelength scales of short and long wavelength NEWSIPS high resolution spectra. The INES processing applies a correction of +17.7 km s$^{-1}$ to the wavelength scale of the high resolution SWP spectra in order to provide an internally consistent velocity scale. Similarly, suitable corrections have been applied to long wavelength small aperture spectra. The new wavelength scale is, within the errors, in good agreement with the optical velocity scale.

In this paper we document the results of the study which led to the ripple correction and absolute calibration algorithms applied to the high resolution spectra processed with the NEWSIPS software for the Final Archive of the IUE Project. In this analysis, based on a very large number of spectra, we find that both the $K$ and $\alpha$ parameters (not only the former as previously believed) vary with order number. This fact, together with the finding that the central peaks of the blaze function vary also as a function of the THDA temperature (for the SWP camera) and of the date of observations (for the LWP and LWR cameras), makes the ripple correction algorithm more complex than previously considered but, at the same time, considerably more reliable. As for the high resolution absolute calibration, the method followed is similar to the one implemented in IUESIPS. The internal accuracy of the high resolution calibration is about 4%. We note that the ripple correction and absolute calibration algorithms here described apply also to IUE data processed and distributed with the INES system.

We compare high-resolution spectra from the Sun and the four solar-type stars 16 Cyg A, 16 Cyg B, HD 32008, HD 34411 obtained with IUE in the wavelength range 2650–2930 Å. The comparison is made for peak intensities between absorption lines. At the level of accuracy of the IUE observations, the stars 16 Cyg A, 16 Cyg B, HD 34411 are indistinguishable from the Sun, in particular the Mgii resonance line profiles are identical. HD 32008 is not a solar analog but is evidently of late G to early K spectral type.

We summarize the nature of modern astronomical archives with special reference to spectroscopic data archives and illustrate in which ways archives can play a role in the accelerated development of Basic Space Sciences in the developing countries. Some of the conflicting issues in the current planning of archives are addressed. Astronomical spectroscopic archives constitute a tool to progress towards an intellectual environment which is required to stimulate the sociological evolution which can support the peaceful and harmonious development of states. This is especially true under the conditions generated by the rapid evolution of technology in the industrialized countries.

One of the reasons why the bright supernova SN1987A is of such importance is the fact that its proximity would allow for the first time, the identification of a supernova progenitor star. Attempts to establish which star was the progenitor have led to uncertainties, however. Here we use spatial and spectroscopic information from International Ultraviolet Explorer (IUE) spectra in the range 1,150–1,950Å to demonstrate that Sk–69 202, the star coinciding positionally with the Large Magellanic Cloud (LMC) supernova, has disappeared from sight. Two weaker sources, named star 2 and star 3 in the astrometric analysis of the image of Sk–69 202 before the supernova outburst, are still present in the ultraviolet spectra. We isolate their spectra and give a spectral classification. We conclude that Sk-69 202 is the progenitor the LMC supernova.