A team spectral insepction platform based on ASERA Hailong YUAN, Haotong ZHANG, Yanxia ZHANG, Yajuan LEI, Yiqiao DONG, and Yongheng ZHAO Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China, 100012 http://lamostss.bao.ac.cn/~yhl/asera/ Email: yuanhl@bao.ac.cn Abstract: Currently large sky area spectral surveys like SDSS, 2dF, and LAMOST, using the new generation of telescopes and observatories, have provided massive spectral data sets for astronomical research. Most of the data can be automatically handled with pipeline, but visually inspection by human eyes is still necessary in several situations, like low SNR spectra, QSO recognition and peculiar spectra mining. Using ASERA, A spectrum eye recoginition Assistant, we can set up a team spectral inspection platform. On a preselected spectral data set, members of a team can individually view spectra one by one, find best match templates and estimate the redshifts. Results from different members will be gathered and merged to raise the team work efficiency. ASERA mainly targets the SDSS and LAMOST fits spectra. Other formats can be supported with some conversion. Spectral templates from SDSS and LAMOST pipelines are embeded and users can easily add their own templates. Convenient cross identification interfaces with SDSS, SIMBAD, VIZIER, NED and DSS are also provided. A application example targeting find strong emission line spectra within LAMOST DR2 is presented. Details can be found on website: http://lamostss.bao.ac.cn/~yhl/asera/ References:1, Yuan H.-L., A&C, 2013, 3, 65Y MAIN INTERFACE Region 1: spectral file path How to install and start ASERA: 0) download the ASERA.jar file. 1) If your OS have installed Java and knowns how to run with .jar file, like in MacOS or Windows, a double click is all you need. If not, try step 2. 2) In command line type "java -version" to check if you have installed java (JRE or JDK) above version 1.6. If not go to http://java.oracle.com to get Java. 3) In command line type "java -jar ASERA.jar ImagePanel" then you will see the panel on the right. START ASERA Click this button to open a local spectral file. Click this button to open the SpectraSelector dialog, which helps to select many spectral file at one time. Click this button to view the fits head. Click this button to view the output message for functions like gaussian line fit. The spectral file path can be any valid URL supported by Java, like file/http/ftp. Region 6: the right click popup menu > Click "Plot template" to select a specific template. Currently we have templates for 15 blue stars (O/B/WD/CV/Double), 49 late type stars (M/L/Carbon), 143 A/F/G/K type stars, 18 galaxies and 4 QSO. > Click "Plot lines" to choose the spectral lines that you want to plot, in a dialog panel shown below. > Click "Z alignment line" to select the line used to determine the redshift. > Click "Save Image" to save current GUI interface as .png and .eps files. > Click "Save Image Automatically" to set the default image output directory. Once set, image files for the current interface are created automatically when you click "Save&Next" button in the "Spectra Selector" panel. > Click "Set Spec Start" and "Set Spec End" to let ASERA known how to convert pixel index into wavelength and inversely, when the input spectral file is just a simple image file (jpg/png/bmp/gif, et al.). > Click "Gaussion Line Fitting", "Lorentz Absorption Fit" and "Calc EW" to get detailed information about those interesting spectral lines. > Click "Input File Format" to specify the input spectral file format. > Click "Smooth" to set the smooth width. Set 1 to unsmooth the spectra. > Click "Change Color" to change the color for target/template spectra. > Click "About ASERA" to view the general information about ASERA. To search other online database like Simbad, SDSS, Vizier, DSS and NED. Region 4: target spectra flux axis adjustment Click the upward, downward, plus and subtraction button to move upward, move downward, zoom in and zoom out the flux region, respectively. Click "0" button to go back to the default settings for flux axis. Region 2: target spectra and template spectra. The target spectra, template spectra and best fit from LAMOST pipeline are plotted in black, blue and red, respectively. User can drag the blue template spectra to find the best match to the target spectra, while the redshift is given at the lower left conner. Some important spectral lines are also plotted as blue dotted lines, with the names at the top. Region 3: target spectral information For LAMOST fits file, the TARGETID, observation date and time, object name, RA, DEC, magnitude, SNR, exposure times, exposure time length, sky quality, seeing, pipeline fit object type/redshift and redshift given by ASERA are printed. Tip: As a text area, one can copy the content and paste it elsewhere. Region 5: wavelength axis adjustment for both target and template spectra If one enable the checkbox at the left end, one can use mouse left key drag on region 2 to select the precise wavelength range to zoom in. It will be very convenient to use this checkbox together with the "0" button. Note once the checkbox is selected, we cann't drag the template spectra to change redshift. LINE FIT SIMBAD CROSS MATCH: http://simbad.u-strasbg.fr/simbad/sim-coo?CooDefinedFrames=none&CooEpoch=2000&submit=submit%20query&Radius.unit=arcmin&CooEqui=2000&CooFrame=FK5&Radius=2&Coord=289.67114%2049.598331 1) choose "Gaussian Curve Fit" from popup menu. 2) use mouse left key drag to specify the wavelength range for curve fit. 3) Firstly the program will create the linear continous spectra using the left 10% and right 10% of these selected pixels. Then the continous spectra are removed and the gaussian fit is processed. The fitting results are shown in a message box, incluing center wavelength, sigma, EW et al. 4) the "Lorentz Absorption Fit" and "Calc EW" function acts in the same way. SDSS CROSS MATCH: http://skyserver.sdss.org/dr12/en/tools/explore/Summary.aspx?ra=289.67114&dec=49.598331 Vizier CROSS MATCH: http://cdsxmatch.u-strasbg.fr/gadgets/ifr?url=http://cdsxmatch.u-strasbg.fr/widgets/SED_plotter.xml&SED_plot_object=289.67114%2C49.598331&SED_plot_radius=5 To process many fits files quickly and efficiently, try "SpectraSelector". 1) If you have all the spectral file in a local directory, set the path in the textfield of the first row and click "OpenDirectory" , then a tree list will appear at the center as a sub node of the "ROOT" node. 2) If you have a textual file (.csv file or tab seperated file), one of whose columns is spectral file URL, you can click "openCsvFile" or "openTabFile" button to create tree node. 3) You can query MySQL database to get spectral file URLs under specific query restrictions, like RA, DEC, magnitude and SNR. The third row helps to set the database connection parameters; the forth row helps to create spectral URL by replacing the ${XXX} with contents from query results; the fifth row provide the query string. 4) Then you can use double click on the leaf node of the tree or "Next" button to select spectra file one by one quickly. 5) The "Save&Next" button will firstly make ASERA remember the fits URL together with user selected template file and redshift in memory, then switch to the next spectral file. So when the same spectral file is opened aggin, ASERA knows which template file to choose and what's the redshift. BATCH PROCESS DSS CROSS MATCH: http://archive.stsci.edu/cgi-bin/dss_search?r=289.67114&d=49.598331&e=J2000&h=15.0&w=15.0&f=gif&c=none&fov=NONE&v3= NED CROSS MATCH: http://ned.ipac.caltech.edu/cgi-bin/nph-objsearch?search_type=Near+Position+Search&in_csys=Equatorial&in_equinox=J2000.0&obj_sort=Distance+to+search+center&lon=289.67114d&lat=49.598331d&radius=1.0 Spectral type identification examples using ASERA. TargetID is printed in pattern: YYYYMMDDplanidAABBB. (YYYYMMDD denotes the observation date; AA denotes the spectrograph ID, from 1 to 16; BBB denotes the fiber ID, from 1 to 250.) 6) The "LoadResults" and "SaveResults" button helps to read the temporary data in memory(the template spectral and redshift for a specific target spectral, as mentioned in previous step) from local file and save into local file, respectively. The file path is specified by the textfield below these two buttons (the "unknown.check.csv" file as shown in the upper right image). 7) The "Delete" button is used to remove the selected tree node in the central view port. 8) Sometimes user may want to add special notes or marks to a target spectra. User can change the textfield at the lowest row. These marks are seperated into different items by comma. Then when you click "Save&Next" a selection dialog is present. In the case of the upper image, ASERA will ask user if the target spectral is "Unknown", "Gal", "QSO", "HaNSiO", "thinHHe", "thickHHe", "TTS" or "CVBlue". 9) Note: if user has used the "Save Image Automatically" function in the Popup Menu, PNG and EPS files are created automatically in the specified directory when user click "Save&Next" button. WORK WITHIN A TEAM Assume you have plenty of spectral files to be inspected by a group of people, you can setup a envorinment with MySQL and web server. For the server side, there are four things you need to prepare before you start work: 1) setup a web server that provide your team member access of all the spectral files; 2) setup a database table containing all the necessary columns about spectral files to help select wanted spectral files, like RA, DEC, SNR and inspection records; instead you can generate additional views to provide special features; 3) setup a basic ASERA feedback table to store template, redshift and user comments for each spectrum; 4) setup a ULYSS feedback table to store Teff, Logg, Feh and RV result for each spectrum. For the client side, user need to do three things: 1) enable ASERA feed back by provide a configuration file named “asera_config/rv2db.ini”; 2) enable ULYSS feed back by provide a configuration file named “asera_config/lamostaseraulyssclient2db.ini” 3) input properly the “MYSQL DB”, “URL pattern” and “Query string” to access spectral files. Then you can have your team start to work with ASERA with the batch process function discussed above. By optimizing you SQL query, you can make things going on in the way you wished. 20111223GAC_118N28_F109015 20120125F559520603009 0130109EG023131N032619F0915067 20111223GAC_118N28_F109015 20120113GAC_061N29_B113204 20120103F559300308071 20121225VB052N42V215004 20130530HD182107N494331B0103169 20131122GAC058N31B102141 20130411HD132901N475049M0113119 Android App Screenshots (StarInHand)