Sky subtraction for LAMOST

Sky subtraction is a key technique in data reduction of multi-fiber spectra. Knowledge of characteristics related to the instrument is necessary to determine the method adopted in sky subtraction.In this study, we describe the sky subtraction method designed for the Large sky Area Multi-Object fiber Spectroscopic Telescope(LAMOST) survey. The method has been integrated into the LAMOST 2D Pipeline v2.6 and applied to data from LAMOST DR3 and later. For LAMOST, calibration using sky emission lines is used to alleviate the position-dependent(and thus time-dependent) ~ 4% fiber throughput uncertainty and small wavelength instability(0.1 A) during observation. Sky subtraction using principal component analysis(PCA) further reduces 25% of the sky line residual from OH lines in the red part of LAMOST spectra after the master sky spectrum, which is derived from a B-spline fit of 20 sky fibers in each spectrograph. Using this approach, values are adjusted by a sky emission line and subtracted from each fiber. Further analysis shows that our wavelength calibration accuracy is about 4.5 km s~(-1), and the averages of residuals after sky subtraction are about 3% for sky emission lines and 3% for the continuum region. The relative sky subtraction residuals vary with moonlight background brightness, and can reach as low as 1.5% for regions that have sky emission lines during a dark night.Tests on F stars with both similar sky emission line strength and similar object continuum intensity show that the sky emission line residual of LAMOST is smaller than that of the SDSS survey.     

一种基于主分量分析的减天光方法

天光是天体观测中的一种重要噪声源.减天光问题是制约多目标光纤光谱观测深度的重要因素.主分量分析(PCA)是统计学的一种分析方法,它可以用来寻找各个天光谱之间的关系,以进一步获得目标光谱中含有的天光成分.为了研究LAMOST的减天光方法,用SDSS的一组原始观测数据进行了仿真实验,实验结果表明,采用PCA方法比SDSS处理程序能够更有效地减天光.最后对PCA方法在LAMOST中的应用前景进行了展望.     

The SAURON project – I. The panoramic integral-field spectrograph

A new integral-field spectrograph, SAURON, is described. It is based on the TIGER principle, and uses a lenslet array. SAURON has a large field of view and high throughput, and allows simultaneous sky subtraction. Its design is optimized for studies of the stellar kinematics, gas kinematics, and line-strength distributions of nearby early-type galaxies. The instrument design and specifications are described, as well as the extensive analysis software which was developed to obtain fully calibrated spectra, and the associated kinematic and line-strength measurements. A companion paper will report on the first results obtained with SAURON on the William Herschel Telescope.     

Evidence for condensed-phase methane enhancement over Xanadu on Titan

We present evidence for condensed-phase methane precipitation near Xanadu using nine nights of observations from the SINFONI integral-field spectrograph at the Very Large Telescope and imaging analysis with empirical surface subtraction. Radiative transfer models are used to support the imaging technique by simulating the spectrometer datacubes and testing for variations in both the surface reflectivity spectrum and atmospheric opacity. We use the models and observations together to argue against artifacts that may arise in the image analysis. High phase angle observations from Cassini/VIMS are used to test against surface scattering artifacts that may be confused with sources of atmospheric opacity. Although changes in the surface reflectivity spectrum can reproduce observations from a particular viewing geometry on a given night, multiple observations are best modeled by condensed-phase methane opacity near the surface. These observations and modeling indicate that the condensed-phase methane opacity observed with this technique occurs predominantly near Xanadu and is most likely due to precipitation.     

A daytime measurement of the lunar contribution to the night sky brightness in LSST’s <Emphasis Type="Italic">ugrizy</Emphasis> bands–initial results

We report measurements from which we determine the spatial structure of the lunar contribution to night sky brightness, taken at the LSST site on Cerro Pachon in Chile. We use an array of six photodiodes with filters that approximate the Large Synoptic Survey Telescope’s u, g, r, i, z, and y bands. We use the sun as a proxy for the moon, and measure sky brightness as a function of zenith angle of the point on sky, zenith angle of the sun, and angular distance between the sun and the point on sky. We make a correction for the difference between the illumination spectrum of the sun and the moon. Since scattered sunlight totally dominates the daytime sky brightness, this technique allows us to cleanly determine the contribution to the (cloudless) night sky from backscattered moonlight, without contamination from other sources of night sky brightness. We estimate our uncertainty in the relative lunar night sky brightness vs. zenith and lunar angle to be between 0.3–0.7 mags depending on the passband. This information is useful in planning the optimal execution of the LSST survey, and perhaps for other astronomical observations as well. Although our primary objective is to map out the angular structure and spectrum of the scattered light from the atmosphere and particulates, we also make an estimate of the expected number of scattered lunar photons per pixel per second in LSST, and find values that are in overall agreement with previous estimates.     

Automatic Normalization and Equivalent-Width Measurement of High-Resolution Stellar Spectra

It is well known that normalization, radial velocity correction and equivalent-width measurement of high-resolution stellar spectra are time-consuming work. In order to improve the efficiency we present an automatic method for these routines. The continuum is determined by fitting the 'high points' in the spectrum. After continuum normalization, the program automatically searches for the position of the Ha line and obtains a rough radial velocity, then computes an accurate radial velocity by cross-correlation between the given spectrum and the solar spectrum. In this method, the equivalent-width is automatically measured using Gaussian fitting. A comparison between our results and those from traditional analysis shows that the typical error for equivalent width is around 3.8% in our method. Developing such automatic routines does not mean to replace the interactive reduction method: it is just for a quick extraction of information from the spectra, especially those obtained in large sky surveys.     

The first results of observations of the transient pulsar SAX J2103.5+4545 by the INTEGRAL observatory

We present the preliminary results of our analysis of the observations of the X-ray pulsar SAX J2103.5+4545 by the INTEGRAL Observatory in December 2002. We mapped this region of the sky in a wide energy range, from 3 to 200 keV. The detection of the source is shown to be significant up to energies of ～100 keV. The hard X-ray flux in the energy range 15–100 keV is variable and presumably depends on the orbital phase. We show that the shape of the pulsar spectrum and its parameters derived from 18–150-keV IBIS data are compatible with the RXTE observations of the source.     

Fast quadratic power spectrum estimators and the E–B decomposition

We describe a fast, quadratic power spectrum estimator for cosmic microwave background polarization fields, based on heuristically-weighted correlation functions. The method can handle real-world effects such as inhomogeneous or correlated noise, and arbitrary sky cuts. A significant feature is that the electric and magnetic polarization powers are separated exactly in the mean, even for observations covering only a small region of the sky, and with a negligible increase in computational cost. The method is illustrated with simulations for a large-area survey, and a future, deep magnetic-polarization survey.     

Estimating the spectral indices of correlated astrophysical foregrounds by a second-order statistical approach

We present the first tests of a new method, the correlated component analysis (CCA) based on second-order statistics, to estimate the mixing matrix, a key ingredient to separate astrophysical foregrounds superimposed to the Cosmic Microwave Background (CMB). In the present application, the mixing matrix is parametrized in terms of the spectral indices of Galactic synchrotron and thermal dust emissions, while the free–free spectral index is prescribed by basic physics, and is thus assumed to be known. We consider simulated observations of the microwave sky with angular resolution and white stationary noise at the nominal levels for the Planck satellite, and realistic foreground emissions, with a position-dependent synchrotron spectral index. We work with two sets of Planck frequency channels: the low-frequency set, from 30 to 143 GHz, complemented with the Haslam 408 MHz map, and the high-frequency set, from 217 to 545 GHz. The concentration of intense free–free emission on the Galactic plane introduces a steep dependence of the spectral index of the global Galactic emission with Galactic latitude, close to the Galactic equator. This feature makes difficult for the CCA to recover the synchrotron spectral index in this region, given the limited angular resolution of Planck , especially at low frequencies. A cut of a narrow strip around the Galactic equator  (| b | < 3°)  , however, allows us to overcome this problem. We show that, once this strip is removed, the CCA allows an effective foreground subtraction, with residual uncertainties inducing a minor contribution to errors on the recovered CMB power spectrum.     

Estimating stellar atmospheric parameters based on Lasso features

With the rapid development of large scale sky surveys like the Sloan Digital Sky Survey （SDSS）, GAIA and LAMOST （Guoshoujing telescope）, stellar spectra can be obtained on an ever-increasing scale. Therefore, it is necessary to estimate stel- lar atmospheric parameters such as Teff, log g and [Fe/H] automatically to achieve the scientific goals and make full use of the potential value of these observations. Feature selection plays a key role in the automatic measurement of atmospheric parameters. We propose to use the least absolute shrinkage selection operator （Lasso） algorithm to select features from stellar spectra. Feature selection can reduce redundancy in spectra, alleviate the influence of noise, improve calculation speed and enhance the robustness of the estimation system. Based on the extracted features, stellar atmospheric param- eters are estimated by the support vector regression model. Three typical schemes are evaluated on spectral data from both the ELODIE library and SDSS. Experimental results show the potential performance to a certain degree. In addition, results show that our method is stable when applied to different spectra.     

The Performance of MEFOS, the ESO Multi-Object Fibre Spectrograph

We are describing a new multi-fibre positioner, MEFOS, that was in generaluse at the La Silla Observatory, and implemented at the prime focus of theESO 3.6 m telescope. It is an arm positioner using 29 arms in a one degreefield. Each arm is equipped with an individual viewing system for accuratesetting and carries two spectroscopic fibres, one for the astronomical objectand the other one for the sky recording needed for sky subtraction. Thespectral fibres intercept 2.5 arcsec on the sky and run from the prime focusto the Cassegrain, where the B&C spectrograph is located. Afterdescribing the observational procedure, we present the first scientificresults.     

Non-random phases in non-trivial topologies

We present a new technique for constraining the topology of the Universe. The method exploits the existence of correlations in the phases of the spherical harmonic coefficients of the cosmic microwave background (CMB) temperature pattern associated with matched pairs of circles seen in the sky in universes with non-trivial topology. The method is computationally faster than all other statistics developed to hunt for these matched circles. We applied the method to a range of simulations with topologies of various forms and on different scales. A characteristic form of phase correlation is found in the simulations. We also applied the method to preliminary CMB maps derived from WMAP , but the separation of topological effects from e.g. foregrounds is not straightforward.     

Source subtraction for the extended Very Small Array and 33-GHz source count estimates

We describe the source subtraction strategy and observations for the extended Very Small Array (VSA), a cosmic microwave background interferometer operating at 33 GHz. A total of 453 sources were monitored at 33 GHz using a dedicated source subtraction baseline. 131 sources brighter than 20 mJy were directly subtracted from the VSA visibility data. Some characteristics of the subtracted sources, such as spectra and variability, are discussed. The 33-GHz source counts are estimated from a sample selected at 15 GHz. The selection of VSA fields in order to avoid bright sources introduces a bias into the observed counts. This bias is corrected and the resulting source count is estimated to be complete in the flux-density range 20–114 mJy. The 33-GHz source counts are used to calculate a correction to the VSA power spectrum for sources below the subtraction limit.     

Crowded field 3D spectroscopy

The quantitative spectroscopy of stellar objects in complex environments is mainly limited by the ability of separating the object from the background. Standard slit spectroscopy, restricting the field of view to one dimension, is obviously not the proper technique in general. The emerging Integral Field (3D) technique with spatially resolved spectra of a two‐dimensional field of view provides a great potential for applying advanced subtraction methods. In this paper an image reconstruction algorithm to separate point sources and a smooth background is applied to 3D data. Several performance tests demonstrate the photometric quality of the method. The algorithm is applied to real 3D observations of a sample Planetary Nebula in M31, whose spectrum is contaminated by the bright and complex galaxy background. The ability of separating sources is also studied in a crowded field in M33. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Automated spectral classification using template matching

An automated spectral classification technique for large sky surveys is pro-posed. We firstly perform spectral line matching to determine redshift candidates for an observed spectrum, and then estimate the spectral class by measuring the similarity be-tween the observed spectrum and the shifted templates for each redshift candidate. As a byproduct of this approach, the spectral redshift can also be obtained with high accuracy. Compared with some approaches based on computerized learning methods in the liter-ature, the proposed approach needs no training, which is time-consuming and sensitive to selection of the training set. Both simulated data and observed spectra are used to test the approach; the results show that the proposed method is efficient, and it can achieve a correct classification rate as high as 92.9%, 97.9% and 98.8% for stars, galaxies and quasars, respectively.     

Automated Separation of Stars and Normal Galaxies Based on Statistical Mixture Modeling with RBF Neural Networks

For LAMOST, the largest sky survey program in China, the solution of the problem of automatic discrimination of stars from galaxies by spectra has shown that the results of the PSF test can be significantly refined. However, the problem is made worse when the redshifts of galaxies are not available. We present a new automatic method of star/(normal) galaxy separation, which is based on Statistical Mixture Modeling with Radial Basis Function Neural Networks (SMM-RBFNN). This work is a continuation of our previous one, where active and non-active celestial objects were successfully segregated. By combining the method in this paper and the previous one, stars can now be effectively separated from galaxies and AGNs by their spectra-a major goal of LAMOST, and an indispensable step in any automatic spectrum classification system. In our work, the training set includes standard stellar spectra from Jacoby's spectrum library and simulated galaxy spectra of EO, SO, Sa, Sb types with redshift ranging from 0 to 1     

The radio environment of the 21 Centimeter Array:RFI detection and mitigation

Detection and mitigation of radio frequency interference(RFI) is the first and also the key step for data processing in radio observations, especially for ongoing low frequency radio experiments towards the detection of the cosmic dawn and epoch of reionization(Eo R). In this paper we demonstrate the technique and efficiency of RFI identification and mitigation for the 21 Centimeter Array(21CMA), a radio interferometer dedicated to the statistical measurement of Eo R. For terrestrial, man-made RFI, we concentrate mainly on a statistical approach by identifying and then excising non-Gaussian signatures, in the sense that the extremely weak cosmic signal is actually buried under thermal and therefore Gaussian noise. We also introduce the so-called visibility correlation coefficient instead of conventional visibility, which allows a further suppression of rapidly time-varying RFI. Finally, we briefly discuss removals of the sky RFI, the leakage of sidelobes from off-field strong radio sources with time-invariant power and a featureless spectrum. It turns out that state of the art technique should allow us to detect and mitigate RFI to a satisfactory level in present low frequency interferometer observations such as those acquired with the 21 CMA, and the accuracy and efficiency can be greatly improved with the employment of low-cost, high-speed computing facilities for data acquisition and processing.     

Inference of relativistic electron spectra from measurements of inverse compton radiation

The inference of relativistic electron spectra from spectral measurement of inverse Compton radiation is discussed for the case where the background photon spectrum is a Planck function. The problem is formulated in terms of an integral transform that relates the measured spectrum to the unknown electron distribution. A general inversion formula is used to provide a quantitative assessment of the information content of the spectral data. It is shown that the observations must generally be augmented by additional information if anything other than a rudimentary two or three parameter model of the source function is to be derived. It is also pointed out that since a similar equation governs the continuum spectra emitted by a distribution of black-body radiators, the analysis is relevant to the problem of stellar population synthesis from galactic spectra.     

Estimating statistics of sky brightness using radio interferometric observations

Radio interferometers are used to construct high resolution images of the sky at radio frequencies and are the key instruments for accessing the statistical properties of the evolution of neutral hydrogen over cosmic time. Here we use simulated observations of the model sky to assess the efficacy of different estimators of the large-scale structure and power spectrum of the sky brightness distribution. We find that while the large-scale distribution can be reasonably estimated using the reconstructed image from interferometric data, estimates of the power spectrum of the intensity fluctuations calculated from the image are generally biased. This bias is found to be more pronounced for diffuse emission. The visibility based power spectrum estimator, however, gives an unbiased estimate of the true power spectrum. This work demonstrates that for an observation with diffuse emission the reconstructed image can be used to estimate the large-scale distribution of the intensity, while to estimate the power spectrum, visibility based methods should be preferred.With the upcoming experiments aimed at measuring the evolution of the power spectrum of the neutral hydrogen distribution, this is a very important result.     

Spectral Synthesis via Mean Field approach to Independent Component Analysis

We apply a new statistical analysis technique, the Mean Field approach to Independent Component Analysis(MF-ICA) in a Bayseian framework, to galaxy spectral analysis. This algorithm can compress a stellar spectral library into a few Independent Components(ICs), and the galaxy spectrum can be reconstructed by these ICs. Compared to other algorithms which decompose a galaxy spectrum into a combination of several simple stellar populations, the MF-ICA approach offers a large improvement in efficiency. To check the reliability of this spectral analysis method, three different methods are used:(1) parameter recovery for simulated galaxies,(2) comparison with parameters estimated by other methods, and(3) consistency test of parameters derived with galaxies from the Sloan Digital Sky Survey. We find that our MF-ICA method can not only fit the observed galaxy spectra efficiently, but can also accurately recover the physical parameters of galaxies. We also apply our spectral analysis method to the DEEP2 spectroscopic data, and find it can provide excellent fitting results for low signal-to-noise spectra.