August 10, 2004 Apache Point Observatory, NM FINDING SUPERNOVAE IN A SLICE OF PI Dennis J. Lamenti San Francisco State University

Outline Sloan Digital Sky Survey Sloan Telescope Supernova Type Ia Data Processing Challenges PlotFits.java Results Conclusion Future

Sloan Digital Sky Survey SDSS goal is to conduct fundamental research in cosmology The approach is to map a quarter of the sky in 5 filters Obtain spectra of 1 million galaxies and 100,000 quasars Determine positions and absolute magnitudes of 100 million astronomical objects Project life: SDSS Extension Proposal to extend SDSS 2005 – 2007 Continued opportunity for further science Initiate supernovae search program

Sloan Telescope 2.5 m reflecting telescope Wide Field Imaging camera Color information in 5 different filters Camera built with 30 CCD's Each CCD has 4 million elements (2048 x 2048 elements) Utilized 'drift scan' operation

Sloan Telescope Sketch of array of CCD in camera Sloan 2.5 m telescope, Ray Trace of incoming light Picture of actual CCD array in telescope,

Supernova Type Ia Supernovae are gigantic thermonuclear explosions Light emitted can outshine whole galaxy Uniform peak brightness Distance indicators, standard candles Studying SN Ia led to discovery of accelerated expansion of universe Acceleration implies Dark Energy Learn more about properties of Dark Energy Z = Dl/l V = C*Z V=H*d H*d = C*Z

Supernova Type Ia Artist Rendition of Accreting White Dwarf Created by Supernova Cosmology Project

SDSS Supernova Search Search goal is to obtain 200 supernovae with light curves Upon discovery, follow up for spectroscopy Redshift coverage.05 < z < 0.3 Saul Perlmuter, et al.

Data Processing Template image of sky has been created from past runs Scans same region of the sky every two nights, search image Search image subtracted from template creates subtracted image Notice appearance of new objects 24 Gigabytes per night Data processing includes: Reduces noise to signal Corrects for atmospheric conditions Determines precise locations of stars and galaxies Matches frames from search and template images Subtracts search and template frames Determines possible SNe candidates Stores candidate information in mySQL database

PlotFits.java PlotFits.java graphical output will assist in determining SN candidates Code was written to zoom into region of candidate and plot 2-dimensional histogram Utilizes JAIDA, which is JAVA implementation of the Abstract Interfaces for Data Analysis for plotting histograms Calls the Java Fits utilities to read and write FITS files Uses mySQL Connector/J driver for JAVA to interact with mySQL

PlotFits.java: Flowchart APOPhoto mySQL FITS files in cluster Frame Subtraction PlotFits

PlotFits.java: Output g i r

Results First possible SN candidate found using FRAME SUBTRACTION Hupert Lampeitl, FNAL

Results: PlotFits.java grgr

Results: False Positives

Results: False Positives:2 Top to right, then bottom; subtracted, search and template image, respectively

Conclusion PlotFits can be used to determine candidates Can also determine false positives Present information to scanner in an automatic way With quicker determination of candidates, faster follow up.

Future Test run Fall 2004 Develop Graphical User Interface Enhance plotting display with additional graphs Experience will develop greater proficiency in identifying objects

Acknowledgements Fritz DeJongh, FNAL Sloan Digital Sky Survey, Supernova Group, FNAL Experiment Astrophysics Group, FNAL Summer Internships in Science and Technology (SIST), FNAL Elliot McCrory, Chairman SIST, FNAL Diane Engram, Head of EOO, FNAL James Davenport, SIST