1. GWDAW91Thursday, December 16 First Comparison Between LIGO &Virgo Inspiral Search Pipelines F. Beauville on behalf of the LIGO-Virgo Joint Working Group

2. GWDAW92Thursday, December 16 LIGO – Virgo Mock Data Challenge  First LIGO – Virgo mock data challenge: Inspiral Project o Exchange simulated data with injected events, exchange triggers o 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 6 Starting 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 pipeline o Some LIGO pipeline vs. Virgo flat search pipeline

3. GWDAW93Thursday, December 16 Data Generation  3 hours of LIGO & Virgo noise o Design sensitivities with line features 16384 Hz & 20 kHz  Inspiral events injection o 2nd Order Post-Newtonian o 26 in LIGO data (every ~400s) distances 20, 25, 30, 35 Mpc masses 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 Mpc masses 1.4 – 1.4 M  starting frequency 24 Hz

4. GWDAW94Thursday, 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 – f low = 40 Hz – longest template = 45 seconds – segment length = 256 seconds ● Virgo – f low = 30 Hz – longest template = 96 seconds – segment length = 512 seconds

5. GWDAW95Thursday, December 16 The Virgo Multi-band Pipeline  Initialization o Spectrum (on 1800 s of noise) o Grid of full frequency band (VIRTUAL) templates o Grids of (REAL) templates for each frequency band  Processing o 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 templates Coherent sum of real templates outputs:  Obtain VIRTUAL templates triggers o Cluster those triggers, in time and between templates REAL VIRTUAL

6. GWDAW96Thursday, December 16 Triggers Production (Overview) LIGO dataVirgo data LIGO pipeline ~3500 Templates UWM Cluster (1 GHz Pentium II) 6 jobs => 6 time slices total time ~ 46 h ~9500 Templates CalTech Cluster (Xeon 2.66 GHz) 3 jobs => 3 time slices total time~ 88 h Virgo MultiBand ~1950 (VIRTUAL)Templates Xeon 2 GHz 2 jobs => 2 mass space regions total time ~15h Memory 1.1 G ~6190 (VIRTUAL) Templates Xeon 2 GHz 7 jobs => 7 mass space regions total time 38 h Memory ~ 5 G Virgo flat search 2556 templates Cluster of 7 Xeon 1.7 GHz 8 jobs total time 16 h Memory 13 G 8103 templates Cluster of 7 Xeon 1.7 GHz 23 jobs total time 48h Memory 38 G

7. GWDAW97Thursday, December 16 Triggers List Confrontation  In each list, triggers are tagged “true” if (ending) time is less than 20 ms from an injection Fake triggers True trigger SNR LIGO 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: otrigger from Virgo Multi-Band obest SNR trigger from LIGO Pipeline Fake triggers True trigger SNR

8. GWDAW98Thursday, December 16 Cross-Validation (SNR)  Same events detected, Strong SNR correlation between pipelines oVirgo data: All events found by both pipeline oLIGO data: 1 event missed by both pipelines + 1 missed by Virgo MB (near threshold)  Also for Virgo flat search Virgo data LIGO data

9. GWDAW99Thursday, December 16 Cross-Validation (distance)  Strong Correlation Also  Good normalization agreement between pipelines Virgo data LIGO data  Also for Virgo flat search 1.11

10. GWDAW910Thursday, 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

11. GWDAW911Thursday, December 16 Compare Masses Virgo data LIGO data  LIGO Data o large spread for Virgo Multi- Band (showing grid resolution) vs. reduced spread & error for LIGO pipeline  Virgo Data o Similar (slightly correlated) spread for both pipelines.  Brings evidence of template grids effect o 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

12. GWDAW912Thursday, 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 injection distance=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.

13. GWDAW913Thursday, December 16 Achievements  Learned to process each others’ data, exchange and compare triggers o Event format translator  Pipelines cross-validation: o Same events found by different pipelines o 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 needs o Fix arrival time estimation in multi-band analysis o Post-processing  Got ready for next step: o Injections of astrophysical events (from given location in the sky)