GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 1

Comparisons of Searches for Comparisons of Searches for Sources in the DC2 DataSources in the DC2 Data

S. W. DigelStanford Linear Accelerator Center

S.

Cip

rini

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 2

IntroductionIntroduction

• Thanks to the ‘content providers’ for being willing to go along with this DC2 exercise

• The DC2 data set is a large (for us) and (semi) realistic representation of the celestial sky, so of course trying out algorithms for source detection is hard to resist – but is not to be mistaken for a systematic study

• Systematic studies are also how the algorithms will be optimized, and this has not been done uniformly – as the presentations yesterday made clear

• Brief introduction to the source lists and some comparisons are in the following slides – Other investigations will be made within the Catalog group

(attend the VRVS meetings)– If permission is granted, we can post the lists in

Confluence – again these are all works in progress

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DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 3

Recap of Source Detection MethodsRecap of Source Detection Methods

• MRF2 – Multi Resolution Filter (Ballet) based on application of MR_FILTER (Starck)– Important details of its application include running MR_FILTER on

separate bands and merging the results– Here will use MRF2-equ-all.txt – has merging of 4 bands and one

iteration to detect fainter sources in the vicinity of brighter ones– Fluxes for many of the sources

• Optimal – Optimal filter (Ballet), also described yesterday– Merging of results from different bands and iteration were also

applied; the result file that will be used here is Optimal-equ-all.txt– All-sky search, significances in the merged file are not well

defined – Fluxes for many of the sources

• UW – Wavelet filtering (Burnett), described today– Works on 8 successively finer grids of HEALPix, with finer

gridding used for higher energies. Detections are merged across bands

– A significance is provided per band, but an overall significance is not provided; fluxes are not provided either

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 4

Recap (cont)Recap (cont)

• BIN (Casandjian) – basically a reimplementation of the binned likelihood analysis used for EGRET data (LIKE)– As described yesterday by Isabelle, many spurious

detections at low latitude owing to an offset (0.25°) in latitude and probably also longitude between where the diffuse model thinks it is on the sky and where LIKE thinks it is

– The BIN analysis is iterative and provides fluxes, counts, and significances. No confidence regions yet, and spectral indicies are fixed at -2

• VR (Romeo & Cillis) – source detection by clustering of cells in Voronoi tessellation, along with a method to evaluate whether candidate sources are point-like– A work in progress; provides only candidate source

position and position uncertainty

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 5

Recap (cont)Recap (cont)

• SB (Stephens) - Aperture Photometry – described yesterday – [SB?] – Provides sigificance and counts estimate (in 0.25 deg

aperture)• PGW (Tosti) – Perugia wavelet filtering – also described

yesterday– Current application is for || < 80°, although this is not an

intrinsic limit and misses only 1.5% of the sky– Provides counts (2x2 deg region, >100 MeV) and

significance• DC2Cat (Ballet & Landriu) – DC2 source list (MRF…) –

currently v2.1– Provides flux, estimated counts, position uncertainty and

significance (TS)

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 6

Review of recapReview of recap

• For SB, and PGW I’ll crudely estimate fluxes from counts based on weighted mean exposure for the position of the source– All-sky average ~>100 MeV for DC2 is

3.2 × 109 cm2 s• For UW, VR, Optimal, and MRF2, either

fluxes or counts are not available for some or all sources

Method # Sources

MRF2 644

Optimal 560

UW 1651*

BIN 540

VR 2548

SB 1463

PGW 934

DC2Cat 380

DC2Sky 1720

* New version, not analyzed here, has ~3k sources

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 7

Distribution in fluxDistribution in flux

• Whole sky• Black – truth• Yellow – DC2cat• Blue – BIN• Red – PGW• Green – SB (fluxes

likely to be seriously underestimated from counts in small aperture)

• Implied flux limits

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 8

Distributions in latitudeDistributions in latitude

• Density of sources vs true density of sources

• Black – DC2 sky model (sources with flux >1 × 10-8 cm-2 s-1, >100 MeV) – this is the reference (683 sources)*

*May exclude some very hard sources

Yellow DC2Cat

Blue BIN

Red PGW

Green SB

Red dashed MRF2

Blue dashed Optimal

Yellow dashed VR

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 9

Comparison with the sky modelComparison with the sky model

• Again selected only the ‘true’ sources above >1 × 10-8 cm-2 s-1, >100 MeV)*

• NB: logarithmic scale

• For comparisons of completeness, make generous assumption that R = 1° is close enough to count as detecting a true source, and R > 1° is a false positive

*Mean separation of sources at this level ~4.4°

Yellow DC2Cat

Blue BIN

Red PGW

Green SB

Red dashed MRF2

Blue dashed Optimal

Yellow dashed VR

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 10

Comparison with true sources (cont)Comparison with true sources (cont)

• Preliminary, and using the crude source correspondence definition R = 1°

• For most methods, more ‘True’ sources are found than were in the DC2Cat, and the range of number of true detections is remarkably small (406-443)

• The DC2Cat has the lowest number of spurious detections – an expected tradeoff with sensitivity

Method # Sources True Spurious

MRF2 644 430 214

Optimal 560 443 117

UW 1651 422 1229

BIN 540 406 134

VR 2548 129 2419

SB 1463 435 1028

PGW 934 443 491

DC2Cat 380 335 45

DC2Sky 1720

Best values in these columns are in red

GLAST LAT Project

DC2 Closeout Workshop, GSFC, 31 May-2 June 2006 11

Toward selecting an algorithmToward selecting an algorithm

• For what?– An algorithm to run as a Science Tool would be useful and

would provide freedom from needing to have a pregenerated source list

– And for catalog analysis – the source detection step of the pipeline

– And for Automated Science Processing (Quick Look)– No, the optimization between spurious source rate and

completeness is not the same for each of these• For when?

– We’ll have an informal discussion on this and other subjects in a rump meeting of the Catalog group tomorrow after the conclusion of the workshop