GWDAW9 1Thursday, December 16

First Comparison Between LIGO &Virgo Inspiral Search Pipelines

F. Beauville on behalf of theLIGO-Virgo Joint Working Group

GWDAW9 2Thursday, December 16

LIGO – Virgo Mock Data Challenge

First LIGO – Virgo mock data challenge: Inspiral Projecto Exchange simulated data with injected events, exchange triggerso Quantitative comparison and cross-check between pipelines

Beginning of September o Simulated LIGO data (S. Chatterji, S. Fairhurst) and Virgo data (A.Viceré)

Mid-October: face to face meeting o Exchange first results & Define trigger productions for quantitative study

Search for inspiral mass range 1 to 3 M, Minimal Match 95%, SNR threshold 6Starting frequency 30 Hz for Virgo data , 40 Hz for LIGO data

Trigger production for both data sets: o LIGO pipeline (S. Fairhurst, N. Christensen)o Virgo flat search (L. Bosi)o Virgo Multi-Band pipeline (F. B.)

Comparison study: o Mostly LIGO pipeline vs. Virgo Multi-Band pipelineo Some LIGO pipeline vs. Virgo flat search pipeline

GWDAW9 3Thursday, December 16

Data Generation 3 hours of LIGO & Virgo noise

o Design sensitivities with line features16384 Hz & 20 kHz

Inspiral events injection o 2nd Order Post-Newtonian

o 26 in LIGO data (every ~400s)distances 20, 25, 30, 35 Mpcmasses 1.4-1.4 and 1.0-2.0 M Starting frequency 40 Hz

o 11 in Virgo data (every ~ 900 s)SNR = 10 , distance=24.83 Mpcmasses 1.4 – 1.4 M starting frequency 24 Hz

GWDAW9 4Thursday, December 16

The LIGO Pipeline

• Use the LIGO inspiral pipeline.– Split data into analysis chunks of 15

overlapping segments.– Segment length at least 4 times

longest template duration (depends on f_low).

– Create template bank for each analysis chunk.

– Filter data with 2PN templates generated in frequency domain.

– Cluster triggers within duration of template.

– No clustering between templates in the bank.

The LIGO pipeline for LIGO data

● LIGO – flow= 40 Hz– longest template = 45 seconds

– segment length = 256 seconds

● Virgo – flow= 30 Hz– longest template = 96 seconds

– segment length = 512 seconds

GWDAW9 5Thursday, December 16

The Virgo Multi-band Pipeline Initialization

o Spectrum (on 1800 s of noise)o Grid of full frequency band (VIRTUAL) templateso Grids of (REAL) templates for each frequency band

Processingo Run synchronously each grid of REAL templates on data

Data chunk twice the longest REAL template

o Check if any REAL template triggers

o Recombine associated VIRTUAL templatesCoherent sum of real templates outputs:

Obtain VIRTUAL templates triggers

o Cluster those triggers, in time and between templates

REAL

REAL

REAL

VIRTUAL

GWDAW9 6Thursday, December 16

Triggers Production (Overview)LIGO data Virgo data

LIGO pipelin

e

~3500 TemplatesUWM Cluster (1 GHz Pentium II)

6 jobs => 6 time slices total time ~ 46 h

~9500 TemplatesCalTech Cluster (Xeon 2.66 GHz)

3 jobs => 3 time slicestotal time~ 88 h

VirgoMultiBa

nd

~1950 (VIRTUAL)TemplatesXeon 2 GHz

2 jobs => 2 mass space regionstotal time ~15h Memory 1.1 G

~6190 (VIRTUAL) TemplatesXeon 2 GHz

7 jobs => 7 mass space regionstotal time 38 hMemory ~ 5 G

Virgo flat

search

2556 templatesCluster of 7 Xeon 1.7 GHz

8 jobstotal time 16 hMemory 13 G

8103 templatesCluster of 7 Xeon 1.7 GHz

23 jobstotal time 48hMemory 38 G

GWDAW9 7Thursday, December 16

Triggers List Confrontation In each list, triggers are tagged “true” if (ending)

time is less than 20 ms from an injection

Fake triggersTrue trigger

SNRLIGO Pipeline lists:Many triggers / injection(No clustering between templates in the bank.)

Virgo Multi-Band lists:not more than 1 / injection(Clustering also between templates in the bank.)

For Each injection, Compare:o trigger from Virgo Multi-Bando best SNR trigger from LIGO Pipeline

Fake triggersTrue trigger

SNR

GWDAW9 8Thursday, December 16

Cross-Validation (SNR)

Same events detected, Strong SNR correlation between pipelines

o Virgo data: All events found by both pipeline

o LIGO data: 1 event missed by both pipelines + 1 missed by Virgo MB

(near threshold)

Also for Virgo flat search

Virgo data

LIGO data

GWDAW9 9Thursday, December 16

Cross-Validation (distance)

Strong Correlation Also Good normalization

agreement between pipelines

Virgo data

LIGO data

Also for Virgo flat search

1.11

GWDAW9 10Thursday, December 16

Compare Arrival Time Compare offsets with injection time

No correlation, Multi-Band spread 6X larger than LIGO pipeline o Known (fixable) template-dependant error on time offset in Virgo Multi-Band

Analysis implementation

GWDAW9 11Thursday, December 16

Compare Masses

Virgo data

LIGO data

LIGO Datao large spread for Virgo Multi-

Band (showing grid resolution) vs. reduced spread & error for LIGO pipeline

Virgo Datao Similar (slightly correlated)

spread for both pipelines. Brings evidence of template

grids effecto LIGO pipeline has templates

close to injected events in both set, not Virgo MB.

Need for more elaborate post-processing

o Less dependant on grid choice

GWDAW9 12Thursday, December 16

Post-processing Exists in LIGO pipeline for distance and chirpmass

o heavy, not processed systematically for all true triggers In development in Virgo Multi-Band analysis for masses

o based on SNR from different templates within a cluster

Posterior PDF estimate for a Virgo injectiondistance=25Mpc, chirpmass=1.2188, m1=m2=1.4. For both Virgo and LIGO injections with these mass parameters the chirp mass estimate is very close, but consistently low.

GWDAW9 13Thursday, December 16

Achievements Learned to process each others’ data, exchange and

compare triggerso Event format translator

Pipelines cross-validation:o Same events found by different pipelineso Correlated triggers ( SNR, distance )o Remaining differences ( 10 % in worst case) under discussion

=> Leads to better understanding of each other pipeline

Put focus on specific needso Fix arrival time estimation in multi-band analysiso Post-processing

Got ready for next step:o Injections of astrophysical events (from given location in the sky)