MANUAL for GLORIA light curve demonstrator experiment test interface implementation

Transcription

1 GLORIA is funded by the European Union 7th Framework Programme (FP7/ ) under grant agreement n MANUAL for GLORIA light curve demonstrator experiment test interface implementation Version: 1.0 Date: September 27, 2013 Authors: Collaborators: A.F.Żarnecki (UWAR) Lech MANKIEWICZ, Ariel MAJCHER, Arkadiusz ĆWIEK (UWAR), Robert SIMPSON, Chris LINTTOT (UOXF), Daniel C. P. Revere (Magdalene College, Cambridge)

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3 1. Introduction This document describes the implementation and user interface, as well as summarizes the results from the research-level off-line demonstrator experiment focusing on light curve reconstruction and classification of variable objects. The experiment is based on the pre-selected data from the Pi of the Sky telescope in Chile (GLORIA telescope T9). Thanks to the wide field of view of the telescope same image sample will allow for variability analysis of bright variable objects of different kind. Analysis is done using the LUIZA framework, designed within GLORIA for efficient analysis of astronomical data. 2. Pi of the Sky data For the demonstrator experiment we selected a set of about 400 images from the Pi fo the Sky telescope in Chile. Field of view of Pi of the Sky camera is 20ºx20º. Selected frames correspond to 4 overlapping observation fields, as shown in Fig. 1. Figure 1. Fields of view of the Pi of the Sky telescope in Chile used in the described demonstrator experiment 3/20

4 The central region of about 10ºx10º visible on most frames was selected as the subject of the analysis. Part of the Pi of the Sky frame showing this region is presented in Fig. 2. Figure 2. Part of the Pi of the Sky frame corresponding to the Sky region considered in the presented study. Pi of the Sky telescope takes sky images with 10s exposure time. These images are used to search for fast optical transients like GRBs. However, much better photometry accuracy is obtained from sums of 20 subsequent frames, corresponding to 200s exposure time. Selected for this study were about 500 stacked images taken from 2006 to 2009 in Las Campanas Observatory (LCO) as well as in 2012 and 2013 in San Pedro de Atacama, Chile. After visual inspection and image pre-processing (see following section) about 400 images remained. 4/20

5 3. User interface The aim of the experiment is to allow user to reconstruct light curve of selected star in real time. Light curve reconstruction is done with the LUIZA framework developed for GLORIA data analysis and is described in detail in section 4. Here we describe user interface which was developed for easy star selection and result viewing. The interface is currently implemented on the dedicated LUIZA server running at University of Warsaw. It should be integrated with GLORIA user pages soon. User interface is available at: 3.1 Introduction The first page displayed is shown in Fig. 3. Short description of the experiment is presented, as well as basic information about the Pi of the Sky experiment and its data. To obtain more detailed information, user can refer to this document (linked as PDF) or continue to the star selection page. Figure 3. Start page of the Luiza light curve demonstrator experiment interface. 5/20

6 Selection page allows user to select from 3 available methods of star selection. User can select the star for light curve reconstruction: from sky image from the list by giving star coordinates If the user knows exactly which star he wants to study, he can give star coordinates by hand. Both Right ascension (RA) and Declination (DEC) should be given as decimal numbers in degrees. User can enter them in the form fields at the bottom of the star selection page (see Fig. 4) and press Select button. However, if position given is outside the range covered by selected images (approximately 80º to 110º in RA, 0º to 30º in DEC; most data correspond to the overlap region 90º to 100º in RA and 10º to 20º in DEC, as shown in Figs. 1 and 2) or no star is visible at this position, empty plot will be shown. Figure 4. Star selection page of the light curve experiment interface. We also selected a set of bright constant stars and few variable stars which can be selected from the list. About one third of listed stars is variable so a chance to select a variable star is quite high. User still has to find the period of the selected star (assuming it is a periodic variable), which is also not an easy task. 6/20

7 Users who love adventures can try to identify variable stars by themselves, selecting them from the Pi of the Sky image. A dedicated interface was developed for this purpose, see Fig. 5. Figure 5. Interface for star selection on sky image, for the light curve experiment. Upon clicking on the image, given position is marked with a green angle (see Fig. 6) the x and y coordinates clicked are outputted in the frames below the image. This is the first step of star selection. In the next step, user should click "Check" button to verify selection. Point coordinates are compared to the list of objects which are stored in an memory array. Tolerace is +/-5 pixels in each direction. Number of matching 7/20

8 objects is shown in the frame below, the RA and DEC values of the identified object are read from an array and displayed below the image. After selecting an object, the "Submit" button can be used (step 3) to send the coordinates to the Luiza analysis server. Received output is then displayed in a dedicated light curve viewer. Figure 6. Interface for star selection on sky image (close-up). Green angle indicates selected star. After the star is selected with any of the above described methods, its coordinates are send to the LUIZA analysis server, which returns the reconstructed light curve after about 3-5 seconds. If the light curve is not displayed, one should check if Java script execution is not blocked in the browser. It may happen that the content is blocked by your browser due to request redirection involved, and you may need to manually disable content protection. For Firefox, click at the shield icon next to the address field. Returned light curve of selected star should be displayed in a dedicated viewer presented in Fig. 7. Constant star was selected as an example in this case. Most results cluster at magnitudo of about There are few points which show some deviations but one can not see any regularities. When displayed, light curve is phased with a period of 10 days, eg. brightness is shown as a function of time modulo 10 day period (arbitrary choice made for demonstration only). For constant star, changing the period (using buttons above curve display or entering period by hand) does not change the overall character of the dependence. 8/20

9 Figure 7. Light curve viewer of the demonstrator experiment. Light curve of constant star is presented as an example. When a variable star is selected, the displayed light curve looks similar, but spread of points around the average brightness value is bigger. Light curve obtained for RS Ori Classical Cepheid star, for default period of 10 days, is shown as an example in Fig. 8. It is very hard to guess, if the star is a periodic variable or not, or maybe large measurement spread is just due to large measurement errors. To verify if the selected star is a periodic variable user has to find a variability period for this star. This can be done by scanning different period values by hand (using arrows above the image, or trying to guess the value and enter it into the numeric frame) or by selecting the Estimate button. Unfortunately, implementation of the period estimate is still experimental and the received values are not very precise, or can be totally wrong. User should try to adjust it by hand anyway. When the proper period value is selected, phased light curve looks like shown in Fig. 9 (same data for RS Ori, now phased with a proper period of days). All (or large majority of) points cluster around functional dependence of the star brightness on time. This dependence tells are about the reason for brightness variability. Users can find more information about different types of variable stars in a dedicated educational material. Periods of selected variable stars accessible at the demonstrator experiment are presented in Table 1 at the end of chapter 5, describing results from light curve analysis in more detail. Positions of these stars are also indicated in Fig /20

10 Figure 8. Light curve of RS Ori variable star in the viewer of the demonstrator experiment. Figure 9. Light curve of RS Ori variable star phased with the proper period of days. 10/20

11 4. Implementation of the experiment Image analysis is based on the LUIZA framework. Unfortunately, full analysis chain, starting from raw image and resulting in the light curve of the selected object is quite time consuming. The two most CPU demanding tasks are: object finding and astrometry. On the other hand, these two tasks are always performed on the full frame and the user is not likely to change their parameters (as they were tuned to produce best results for the Pi of the Sky set-up). Therefore we decided to divide image analysis into two steps: image preprocessing and object light curve reconstruction. Preprocessing is done only once, while setting up the experiment (or whenever new data are added), and the object light curve reconstruction is run in response to each user request. 4.1 Image preprocessing Preprocessing done with LUIZA consists of two steps: object finding and astrometry. Object finding is done with PixelClusterFinder processor. The algorithm searches for groups of pixels with signal above the defined threshold. The seed pixel is searched first (with tighter seed selection cut) and then the neighbouring pixels, with signal above pixel signal threshold (which can be looser) are added to form the cluster. In the current analysis we use thresholds of 8 and 3 times noise level, respectively. The algorithm assumes that the cluster should have one maximum only, if two maxima (above seed threshold) are found, two clusters will be reconstructed. To define thresholds, background level and average noise level are calculated first. To correct for significant background variation over the frame, background level is calculated in 4x4 subframes and then interpolated. Finally, cluster signal and position on CCD is calculated. Cluster signal is obtained as the sum of pixel charges. However, if cluster consists of more than 25 pixels, only 25 brightest pixels are used for calculation. The same is done for the position calculation with Center-of-Gravity (CoG) method. The output of the cluster finding processor is stored as GloriaObjectList table. The second preprocessing step is astrometry, which is done by Astrometry processor. It is based on Astrometry.net algorithm for finding frame orientation and transformation for calculating object positions in the sky. Processor analyses GloriaObjectList table and calculates parameters of position transformation. As the final step, positions of all objects in the list are calculated (Ra,Dec) and added to the table, which is then stored in the object list file. 4.2 Light curve reconstruction Light curve reconstruction is done within ObjectLightCurve processor. It analyses the object list (read from file) and finds measurements of the selected object based on its coordinates on the sky. The brightness measurement is then normalized to the reference stars. The simplest procedure is to take single reference star. However, when combining measurements from different fields this results in significant 11/20

12 systematic effects. They are most probably resulting from significant PSF deformations over the Pi of the Sky field of view and PSF dependence on the spectral type of the reference star (resulting from wide spectral acceptance of the Pi of the Sky aparatus - only UV+IR cut filter is used). More precise calibration is obtained when larger set of stars from the same part of frame is used. In the proposed approach, user can specify the maximum distance of reference star from the studied object (ReferenceMaxDist parameter) and the maximum number of reference stars to be considered (MaxReferenceCount parameter; if zero value is given, all reference stars within ReferenceMaxDist are taken, otherwise closes stars are taken). After dedicated tests we decided to use the Pi of the Sky reference star list, but limit it to stars between 7 m and 8.5 m. One has to note that although Pi of the Sky measurements are normalized to V magnitudo, there is a non-vanishing spectral dependence due to wide spectral acceptance mentioned above. As a result Pi of the Sky magnitudo coincides with that of V catalogue only for stars with J-K 0.4. When multiple reference stars are selected, photometric calibration can be based on the average reference star magnitudo correction. However, this estimate is still affected by systematic effects reflecting the fact that calibration correction can be position dependent. Therefore, when sufficient number of reference stars is used, polynomial fit of correction dependence on reference star position can be applied. This is controlled by CorrectionFitOrder parameter (0 for plain average, 1 for linear fit, 2 for quadratic fit). In all cases, the RMS of the difference between the reference star correction and the average correction (or correction fit) can be used as an estimate of the photometry uncertainty. After applying calculated correction to object magnitudo, the measurement is added to the light curve with HJD timestamp. Data analysis task of the described demonstrator experiment has been implemented on the virtual machine running Fedora 17 and is accessible via HTTP protocol. To trigger light curve reconstruction, user has to call CGI script giving following parameters: RA - object Right ascension in degrees (obligatory parameter) DEC - object Declination in degrees (obligatory parameter) ReferenceMaxDist - radius for reference star search in degrees (optional; default is 1.5) MaxReferenceCount - maximum reference star number (optional; default is 0 - no limit) CorrectionFitOrder - correction fit order (optional; default is 1 - linear fit) As a result, server will send the light curve data as a text contents (text table with 3 columns: HJD, magnitudo and estimated uncertainty). Dedicated light curve viewer displays the resulting light curve in a web browser. It also allows user to phase the light curve (see section 3). 12/20

13 5. Results 5.1 Tests with constant stars Light curve reconstruction procedure was first tested on selected constant stars. Figure 10 shows the results of the magnitudo determination (with default values of algorithm parameters), as a function of frame id, for two selected stars. Frames are numbered in the order they were taken, but separately for different fields of observation and cameras (dashed lines in Fig. 10 indicate change of field, dotted lines - data from different cameras). Figure 10: magnitudo of two selected constant stars as a function of frame id. Dashed lines indicate change of field, dotted lines - data from different cameras. It is clear that depending on observation field and/or camera some systematic effects are observed. They are related to the star position on the frame and differ from star to star, so it is not possible to have a unique definition of good measurement. However, systematic effects can be largely reduced by using information on the calibration uncertainty, as returned by light curve determination task. The dependence of the estimated uncertainty on the frame id, for the two stars considered, is shown in Fig. 11. Systematic shifts in measured star magnitudo are clearly correlated with increased calibration uncertainty. Therefore, it can be used to select the best measurements, not affected by large systematic effects. Distribution of the uncertainty for the two considered stars is presented in Fig. 12. Both distributions have a clear two-peak structure. By using a cut <0.1 we can limit ourselves to the best 13/20

14 measurements only. Result of such a cut is illustrated in Fig. 13, where the magintudo distribution for the two selected stars is presented before (dashed line) and after the cut (solid line). The (properly adjusted) cut has a dramatic consequence on the measurement. While reducing the event statistics by about 30% it also improves photometry quality (measurement spread) for the two stars by over a factor of 2 (in terms of RMS of the magintudo distribution: from m to m and from m to m respectively). Figure 11: Estimated calibration uncertainty for two selected constant stars, as a function of frame id. Dashed lines indicate change of field, dotted lines - data from different cameras. 14/20

15 Figure 12: Distribution of the estimated calibration uncertainty for two selected constant stars. Figure 13: magnitudo distribution for the two considered constant stars before (dashed line) and after (solid line) the cut on the estimated calibration uncertainty < /20

16 5.2 Variable star reconstruction Approach tested with constant stars has been then applied to selected variable stars in the considered field. Regular variable stars were selected based on Pi of the Sky and Simbad catalogues. For each star, after removing poor quality measurements with cut on estimated calibration uncertainty, phased light curve was fitted. Selected results are presented in Figures 14 to 19. The fit, indicated with green line, was performed with CERN root package. The light curve was modelled with a Fourier series. No fit is indicated in Fig. 19, as the period of variability is too long to be fitted with the selected data. Main parameters of the presented stars are summarized in Table 1 and their position in the sky indicated in Fig. 20. Figure 14: Phased light curve of W Gem, classical cepheid (delta Cep type). Figure 15: Phased light curve of V1388 Ori, eclipsing binary of Algol type (detached). 16/20

17 Figure 16: Phased light curve of RS Ori, classical Cepheid (delta Cep type). Figure 17: Phased light curve of CR Gem, semi-regular variable. 17/20

18 Figure 18: Phased light curve of V1385 Ori, eclipsing binary of beta Lyr type (semi-detached). Figure 19: Phased light curve of OW Gem, eclipsing binary of Algol type (detached). 18/20

19 Fig. Star Type Ra Dec Period [day] 14 W Gem Classical Cepheid (delta Cep type) 15 V1388 Ori Eclipsing binary of Algol type (detached) 16 RS Ori Classical Cepheid (delta Cep type) CR Gem Semi-regular variable V1385 Ori Eclipsing binary of beta Lyr type (semi-detached) 19 OW Gem Eclipsing binary of Algol type (detached) Table 1: Parameters of the selected regular variable stars, which can be studied with the demonstrator experiment 19/20

20 Figure 20: Positions in the sky of the selected variable stars presented in Table /20