The Sloan Digital Sky Survey monitor telescope pipeline

The photometric calibration of the Sloan Digital Sky Survey (SDSS) is a multi‐step process which involves data from three different telescopes: the 1.0‐m telescope at the US Naval Observatory (USNO), Flagstaff Station, Arizona (which was used to establish the SDSS standard star network); the SDSS 0.5‐m Photometric Telescope (PT) at the Apache Point Observatory (APO), NewMexico (which calculates nightly extinctions and calibrates secondary patch transfer fields); and the SDSS 2.5‐m telescope at APO (which obtains the imaging data for the SDSS proper). In this paper, we describe the Monitor Telescope Pipeline, MTPIPE, the software pipeline used in processing the data from the single‐CCD telescopes used in the photometric calibration of the SDSS (i.e., the USNO 1.0‐m and the PT). We also describe transformation equations that convert photometry on the USNO‐1.0m u ′g ′r ′i ′z ′ system to photometry the SDSS 2.5m ugriz system and the results of various validation tests of the MTPIPE software. Further, we discuss the semi‐automated PT factory, which runs MTPIPE in the day‐to‐day standard SDSS operations at Fermilab. Finally, we discuss the use of MTPIPE in current SDSS‐related projects, including the Southern u ′g ′r ′i ′z ′ Standard Star project, the u ′g ′r ′i ′z ′ Open Star Clusters project, and the SDSS extension (SDSS‐II). (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The SuperCOSMOS Sky Survey – II. Image detection, parametrization, classification and photometry

In this, the second in a series of three papers concerning the SuperCOSMOS Sky Survey, we describe the methods for image detection, parametrization, classification and photometry. We demonstrate the internal and external accuracy of our object parameters. Using examples from the first release of data, the South Galactic Cap survey, we show that our image detection completeness is close to 100 per cent to within ∼1.5 mag of the nominal plate limits. We show that for the B _J survey data, the image classification is externally > 99 per cent reliable to B _J∼19.5 . Internally, the image classification is reliable at a level of > 90 per cent to B _J∼21 , R ∼19 . The photometric accuracy of our data is typically ∼0.3 mag with respect to external data for m >15 . Internally, the relative photometric accuracy in restricted position and magnitude ranges can be as accurate as ∼5 per cent for well-exposed stellar images. Colours are externally accurate to σ _{B − R , R − I} ∼0.07 at B _J∼16.5 , rising to σ _{B − R , R − I} ∼0.16 at B _J∼20 .     

大天区望远镜中sCMOS相机的测光精度分析

与传统CCD (Charge Coupled Device)相机相比, s COMS (scientific Complementary Metal Oxide Semiconductor)相机被广泛装备于超大天区巡天设备,与传统CCD相机不同的是sCMOS相机采用卷帘式快门,因此对其进行测光精度的分析工作是很有意义的.首先,将s CMOS相机拍摄的图像与UCAC2 (The Second U.S. Naval Observatory CCD Astrograph Catalog)星表进行匹对,识别图像中的UCAC2标准星.接着对图中的标准星进行测光并提取测光数据进行最小二乘直线拟合,获得了相应的系统转换系数并得到仪器星等至标准星等的转换公式.然后,将转化后的仪器星等和标准星等做差并计算相应的均方根误差.最后,利用计算得到的均方根误差评估sCMOS相机的测光精度,并将标准星按星等划分后,分析了相应的测光误差.计算结果表明在标准测光夜测量亮度亮于14等的星时,测光精度优于0.15 mag.通过实测精度分析可知卷帘快门sCOMS相机具有较高的测光精度,基本满足空间碎片巡天观测的要求.     

Optimizing point-source parameters for scanning satellite surveys

We describe a method for deriving the position and flux of point and compact sources observed by a scanning survey mission. Results from data simulated to test our method are presented, which demonstrate that at least a 10-fold improvement is achievable over that of extracting the image parameters, position and flux, from the equivalent data in the form of pixel maps. Our method achieves this improvement by analysing the original scan data and performing a combined, iterative solution for the image parameters. This approach allows for a full and detailed account of the point-spread function (PSF), or beam profile, of the instrument. Additionally, the positional information from different frequency channels may be combined to provide the flux-detection accuracy at each frequency for the same sky position. Ultimately, a final check and correction of the geometric calibration of the instrument may also be included. The Planck mission was used as the basis for our simulations, but our method will be beneficial for most scanning satellite missions, especially those with non-circularly symmetric PSFs.     

Short time-scale variability in the Faint Sky Variability Survey

We present the V -band variability analysis of the point sources in the Faint Sky Variability Survey on time-scales from 24 min to tens of days. We find that about one per cent of the point sources down to   V = 24  are variables. We discuss the variability-detection probabilities for each field depending on field sampling, amplitude and time-scale of the variability. The combination of colour and variability information allows us to explore the fraction of variable sources for different spectral types. We find that about 50 per cent of the variables show variability time-scales shorter than 6 h. The total number of variables is dominated by main-sequence sources. The distribution of variables with spectral type is fairly constant along the main sequence, with 1 per cent of the sources being variable, except at the blue end of the main sequence, between spectral types F0 and F5, where the fraction of variable sources increases to about 2 per cent. For bluer sources, above the main sequence, this percentage increases to about 3.5. We find that the combination of the sampling and the number of observations allows us to determine the variability time-scales and amplitudes for a maximum of 40 per cent of the variables found. About a third of the total number of short time-scale variables found in the survey were not detected in either B or/and I band. These show a similar variability time-scale distribution to that found for the variables detected in all three bands.     

CoRoT data reduction by example

Data reduction techniques published so far for the CoRoT N2 data product were targeted primarily on the detection of extrasolar planets. Since the whole dataset has been released, specific algorithms are required to process the lightcurves from CoRoT correctly. Though only unflagged datapoints must be chosen for scientific processing, some flags might be reconsidered. The reduction of data along with improving the signal‐to‐noise ratio can be achieved by applying a one dimensional drizzle algorithm. Gaps can be filled by linear interpolated data without harming the frequency spectrum. Magnitudes derived from the CoRoT color channels might be used to derive additional information about the targets. Depending on the needs, various filters in the frequency domain remove either the red noise background or high frequency noise. The autocorrelation function or the least squares periodogram are appropriate methods to identify periodic signals. The methods described here are not strictly limited to CoRoT data but may also be applied on Kepler data or the upcoming PLATO mission. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Correcting CCD photometry of stars for seeing effects

Systematic variability in stellar magnitudes, as derived from profile fitting to CCD images, may in some instances be due to variable seeing. It is suggested that this happens in cases where the stars are unresolved pairs, typically with sub-arcsecond separation between the components. It is shown that the fitting of suitable Generalised Additive Models to time series photometry can disentangle intrinsic stellar variability and seeing-induced brightness changes. It is possible that there will be a fixed seeing response associated with a given star which exhibits the effect: estimation of this response from several long photometric runs is demonstrated.     

Bayesian photometric redshifts with empirical training sets

We combine in a single framework the two complementary benefits of  χ²  template fits and empirical training sets used e.g. in neural nets:  χ²  is more reliable when its probability density functions (PDFs) are inspected for multiple peaks, while empirical training is more accurate when calibration and priors of query data and training set match. We present a  χ²  empirical method that derives PDFs from empirical models as a subclass of kernel regression methods, and apply it to the Sloan Digital Sky Survey Data Release 5 sample of >75 000 quasi-stellar objects, which is full of ambiguities. Objects with single-peak PDFs show <1 per cent outliers, rms redshift errors <0.05 and vanishing redshift bias. At   z > 2.5  , these figures are two times better. Outliers result purely from the discrete nature and limited size of the model, and rms errors are dominated by the intrinsic variety of object colours. PDFs classed as ambiguous provide accurate probabilities for alternative solutions and thus weights for using both solutions and avoiding needless outliers. E.g. the PDFs predict 78.0 per cent of the stronger peaks to be correct, which is true for 77.9 per cent of them. Redshift incompleteness is common in faint spectroscopic surveys and turns into a massive undetectable outlier risk above other performance limitations, but we can quantify residual outlier risks stemming from size and completeness of the model. We propose a matched  χ²  error scale for noisy data and show that it produces correct error estimates and redshift distributions accurate within Poisson errors. Our method can easily be applied to future large galaxy surveys, which will benefit from the reliability in ambiguity detection and residual risk quantification.     

The Gaia spectrophotometric standard stars survey: II. Instrumental effects of six ground‐based observing campaigns

The Gaia SpectroPhotometric Standard Stars (SPSS) survey started in 2006, was awarded almost 450 observing nights and accumulated almost 100000 raw data frames with both photometric and spectroscopic observations. Such large observational effort requires careful, homogeneous, and automatic data reduction and quality control procedures. In this paper, we quantitatively evaluate instrumental effects that might have a significant (i.e., ≥1 %) impact on the Gaia SPSS flux calibration. The measurements involve six different instruments, monitored over the eight years of observations dedicated to the Gaia flux standards campaigns: DOLORES@TNG in La Palma, EFOSC2@NTT and ROSS@REM in La Silla, CAFOS@2.2m in Calar Alto, BFOSC@Cassini in Loiano, and LaRuca@1.5m in San Pedro Mártir. We examine and quantitatively evaluate the following effects: CCD linearity and shutter times, calibration frames stability, lamp flexures, second order contamination, light polarization, and fringing. We present methods to correct for the relevant effects which can be applied to a wide range of observational projects at similar instruments. (© 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Detection and measurement from narrow-band tunable filter scans

The past 5 years have seen a rapid rise in the use of tunable filters in many diverse fields of astronomy, through Taurus Tunable Filter (TTF) instruments at the Anglo-Australian and William Herschel Telescopes. Over this time we have continually refined aspects of operation and developed a collection of special techniques to handle the data produced by these novel imaging instruments. In this paper, we review calibration procedures and summarize the theoretical basis for Fabry–Perot photometry that is central to effective tunable imaging. Specific mention is made of object detection and classification from deep narrow-band surveys containing several hundred objects per field. We also discuss methods for recognizing and dealing with artefacts (scattered light, atmospheric effects, etc.), which can seriously compromise the photometric integrity of the data if left untreated. Attention is paid to the different families of ghost reflections encountered, and the strategies used to minimize their presence. In our closing remarks, future directions for tunable imaging are outlined and contrasted with the Fabry–Perot technology employed in the current generation of tunable imagers.