Source Detection by Count Excess

Slides:



Advertisements
Similar presentations
XMM EPIC MOS Andy Read EPIC Calibration Meeting Mallorca, Spain 01/02/05 What can we do with Pattern 31s? - Central pixel (red) has.
Advertisements

Computational Biology, Part 23 Biological Imaging II Robert F. Murphy Copyright  1996, 1999, All rights reserved.
Image Analysis Phases Image pre-processing –Noise suppression, linear and non-linear filters, deconvolution, etc. Image segmentation –Detection of objects.
Image Segmentation Image segmentation (segmentace obrazu) –division or separation of the image into segments (connected regions) of similar properties.
GLAST Science Support CenterAugust 9, 2004 Likelihood Analysis of LAT Data James Chiang (GLAST SSC – SLAC)
Multi video camera calibration and synchronization.
GLAST LAT ProjectDC1 Closeout Workshop, Feb , Statistical Issues in Likelihood Analysis of LAT Data Seth Digel (HEPL/Stanford Univ.) & Guillaume.
Growth of Structure Measurement from a Large Cluster Survey using Chandra and XMM-Newton John R. Peterson (Purdue), J. Garrett Jernigan (SSL, Berkeley),
Canny Edge Detector1 1)Smooth image with a Gaussian optimizes the trade-off between noise filtering and edge localization 2)Compute the Gradient magnitude.
GLAST Science Support Center February 12, 2004 DC1 Closeout Detecting Gamma-Ray Bursts in the DC1 Data David Band (GSSC)
C&A 1 May 06 1 Point Source Detection and Localization Update Using the UW HealPixel database on DC2_2 data Toby Burnett University of Washington.
Source detection at Saclay Look for a fast method to find sources over the whole sky Provide list of positions, allowing to run maximum likelihood locally.
C&A 10April06 1 Point Source Detection and Localization Using the UW HealPixel database Toby Burnett University of Washington.
THB Source Catalog Meeting 12/21/05 1 Healpixels and Wavelets Toby Burnett and Bruce Lesnick University of Washington.
GLAST LAT Project SLAC Jan. 12, 2004 Hammer-Aitoff map.
Udine Nicola Omodei 1 GRB Trigger Algorithms From DC1 to DC2 Nicola Omodei Riccardo Giannitrapani Francesco Longo Monica Brigida.
A statistical test for point source searches - Aart Heijboer - AWG - Cern june 2002 A statistical test for point source searches Aart Heijboer contents:
Source catalog generation Aim: Build the LAT source catalog (1, 3, 5 years) Jean Ballet, CEA SaclayGSFC, 29 June 2005 Four main functions: Find unknown.
Galactic Plane Paper Update Curtis Lansdell Milagro Collaboration Meeting December 18, 2006.
Fermi LAT Monash University Nov 21, 2009 R.DuboisFermi LAT Science Analysis Tutorial1 Issues in a Nutshell LS5039 Low stats: 4k photons in 1 yr Strong.
GLAST LAT Project Catalogs and Diffuse Emissions Working Groups G. Tosti et al.SLAC, May Gino Tosti, Claudia Cecchi INFN Perugia based on Francesca.
GLAST LAT Project DC2 Closeout Workshop, GSFC, 31 May-2 June Comparisons of Searches for Sources in the DC2 Data S. W. Digel Stanford Linear Accelerator.
Lecture 8 Source detection NASSP Masters 5003S - Computational Astronomy
25s detection of the Sy1 galaxy NGC3516 The Palermo BAT survey project Application to a sample of SDSS LINERs V. La Parola, A.Segreto, G. Cusumano, V.
A First Look At VERITAS Data Stephen Fegan Vladimir Vassiliev UCLA.
Source catalog generation for DC2 Aim (in order of priority): 1.Improve on source detection algorithm and error box. 2.Provide a list of source identifications.
Extragalactic Survey with MAXI and First MAXI/GSC Catalog Extragalactic Survey with MAXI and First MAXI/GSC Catalog Yoshihiro Ueda Kazuo Hiroi, Naoki Isobe,
Digital Aperture Photometry ASTR 3010 Lecture 10 Textbook 9.5.
1 Giuseppe Romeo Voronoi based Source Detection. 2 Voronoi cell The Voronoi tessellation is constructed as follows: for each data point  i (also called.
June 27-29, DC2 Software Workshop - 1 Tom Stephens GSSC Database Programmer GSSC Data Servers for DC2.
All-sky source search Aim: Look for a fast method to find sources over the whole sky Selection criteria Algorithms Iteration Simulations Energy information.
Source catalog generation Aim: Build the LAT source catalog (1, 3, 5 years) Jean Ballet, CEA SaclaySLAC, 23 May 2005 Four main functions: Find unknown.
Likelihood analysis of small diffuse sources Riccardo Rando Elisa Mosconi, Omar Tibolla DC2 Kickoff Meeting – SLAC, 1-3 March 2006.
Concept 1: Computing Weighted Sum. Is an operation between two tables of numbers, usually between an image and weights. Typically, if one table is smaller,
IPHC, Strasbourg / GSI, Darmstadt
Eyes on the Polarized Sky, Feet on the Ground
J Comput Chem 26: 334–343, 2005 By SHURA HAYRYAN, CHIN-KUN HU, JAROSLAV SKRˇ IVA′ NEK, EDIK HAYRYAN, IMRICH POKORNY.
Svom Ground-segment Meeting CNES
Statistics: The Z score and the normal distribution
WORKSHOP 10 ANNULAR PLATE
Jean Ballet, CEA Saclay GSFC, 31 May 2006 All-sky source search
DC2 pulsars analysis: a population point-of-view
A Survey of EGRET GeV Sources
Fermi LAT Limits on High-Energy Gamma Lines from WIMP Annihilation
A special case of calibration
First day: Planets, Sun and Moon
Self-similarity and points of interest
Erik Strahler UW-Madison 28/4/2009
Image Processing, Leture #12
Wavelet Analysis for Sources Detection
Source catalogue generation
Search for point-like source in ANTARES
All-sky source search issues
Splinter section: Diffuse emission
Fun with DC1: GRB Triggers, Localizations, Etc.
Basics of Photometry.
Wavelet method for source detection in GLAST photon-counting images
Galactic Diffuse Emission for DC2
SSM onboard ASTROSAT Calibration and First Results
The spectral properties of Galactic X-ray sources at faint fluxes
TRAINEE PRESENTATION The North and South Ecliptic Pole fields population Project supervisors: R. Saxton N. Loiseau Trainee student: Jaime Abella Payá.
Data Challenge 2: Aims and Status
MAP 2014 Spring Workshop Fermilab May, 2014
Finding Basic Shapes Hough Transforms
Feature descriptors and matching
Time-Dependent Searches for Neutrino Point Sources with IceCube
Face-to-Face IDT Meeting Session 1 Observation Strategies and EGRET Experience S. W. Digel March 19, 2002 SLAC.
Fermi LAT Observations of Galactic X-ray binaries
EBL Absorption Signatures in DC2 Data
DIGITAL IMAGE PROCESSING Elective 3 (5th Sem.)
Presentation transcript:

Source Detection by Count Excess Tom Stephens/GSSC Sept. 29, 2004

Outline Motivation Method Description Current Status & results Future Directions

Motivation Jim was looking for a list of potential targets to try Likelihood out on to generate the initial DC1 catalog and 1 week before the closeout meeting no one had responded Simple and straight-forward No a priori knowledge required Envisioned as “first step” to locate potential targets, not determine their properties.

Description Step 1: Determine Significance Step 2: Find local maxima Grid of points defined on the sky Count excess and significance calculated at each point on the grid Done in spherical coordinates Step 2: Find local maxima Excess data searched to find local maxima Simply the highest excess within N grid points

Determining Significance (1 of 2) Background counts Sum all events within an annulus centered on the grid point Inner radius of annulus fixed Outer radius can either be fixed or allowed to increase with increasing galactic latitude Divide total counts by area of annulus in degrees to get average counts per unit area Background counts equal the area of the aperture (below) times the average background counts per unit area

Determining Significance (2 of 2) Source counts Determined by summing all events within a fixed circular aperture around the grid point Subtract the calculated background counts for the aperture Source significance Compute the significance of the source counts above the background Significance determined by dividing the source counts by the square root of the calculated background counts

Significance Map Aperture = 0.5º Annulus = 1º-2º Grid=0.25º Significance >=3

Finding Local Maxima Once the significance of the count excess has been determined at each point on the grid I search through the points to find the local maxima. Finding the maxima Scans over all grid points Check to see if the grid point in question has the highest significance of all its neighbors within a box N by N pixels wide in RA and Dec. If so, this is the local maximum and the coordinates and relevant data written to the output. However… Grid treats RA & Dec as Cartesian system More points at high Declinations that really necessary Must account for this when doing the maxima search

Initial DC1 Results Initial search parameters: Aperture = 0.5º Annulus 1º inner radius 2º outer radius (fixed) Grid=0.25º steps in RA and Dec Significance >= 3 → 1677 local maxima 363 matches in the truth data 126 detected sources in the 5.8 days of DC1 data with σ>=5 14 spurious detections (11%) 112 DC1 sources detected, 5 of which were GRBs.

Detected Sources Green, white = real DC1 sources detected Cyan = DC1 GRB’s detected Red = Spurious sources

Effects of Data Volume I had a years worth of data from Jim that I have been using to test the database system that contains just the galactic diffuse emission, extra-galactic diffuse emission, and (I believe) all the 3rd Egret Catalog sources. Wanted to see what the effects of more/less data was on the detection thresholds and fraction of spurious results Looked a 1 day, 1 week, 1 month, 3 months and 1 year data sets of 15º radius regions centered on the Crab pulsar and the Galactic center. Looked for sources within 10º of the image center to avoid “edge effects” from the way I computed background counts 6 Egret sources in the Crab field 10 sources in the Galactic Center field

Data Volume Results Field Exposure Time # of 5σ Detections <0.5º 3EG matches Spurious Detections Missed Sources Crab 1 day 7 2 5 4 1 week 1 month 3 3 months 1 year 6 G. Center 1 10 12

Galactic Center Significance Map 1 day 1 week 1 month 1 year

Galactic Center Significance Map 1 day 1 week 1 month 1 year

Effects of Background Levels Wanted to see the effect of varying amount of background on detection results Ran obsSim and created a year’s worth of data that contains the galactic diffuse emission doubled, extra-galactic diffuse emission tripled, and all the 3rd Egret Catalog sources As before, I looked at 1 day, 1 week, 1 month, 3 months and 1 year data sets of 15º radius regions centered on the Crab pulsar and the Galactic center. Strangely, the faint sources had a lot more counts than expected (by a factor of 3), almost as if they are in the flux map used for the background model.

Background Results Field Exposure Time # of 5σ Detections <0.5º 3EG matches Spurious Detections Missed Sources Crab 1 day 6 4 2 1 week 1 month 5 1 3 months 1 year 7 G. Center 3 13 9 20 10 16 15

Future Directions Aperture Size Background Detection threshold Optimize fixed aperture size Use energy dependent aperture to account for PSF Background Optimize annulus size for various parts of sky (i.e. on/off galactic plane, crowded field, etc.) Possibly use a background model to fit the background Detection threshold Source localization Test in field of crowded, faint objects Work on sensitivity limits