gravitational wave bursts characterization of transients
play

Gravitational Wave Bursts: Characterization of Transients in LIGO - PowerPoint PPT Presentation

Gravitational Wave Bursts: Characterization of Transients in LIGO Interferometer Data Ed Brambley Mentor: Dr. John Zweizig 19 th August 2003 The Spectrum of LIGO Interferometer Output -10 Power (in dB Hz 1 ) -20 -30 -40 -50 -60 -70


  1. Gravitational Wave Bursts: Characterization of Transients in LIGO Interferometer Data Ed Brambley Mentor: Dr. John Zweizig 19 th August 2003

  2. The Spectrum of LIGO Interferometer Output -10 Power (in dB Hz − 1 ) -20 -30 -40 -50 -60 -70 -80 1 2 3 4 5 6 7 8 Frequency (in kHz) 1

  3. Probability Distributions & Likelihood Ratios • The probability distribution function (pdf) f : � b P ( a < X ≤ b ) = a f ( x | θ ) dx (1) • The hypotheses: H 0 : Data x comes from a pdf f 0 ( x | θ 0 ), for some θ 0 . H 1 : Data x comes from a pdf f 1 ( x | θ 1 ), for some θ 1 . • The log profile likelihood ratio statistic: � �    sup θ 1 f 1 ( x | θ 1 ) 2 log (2)  � � sup θ 0 f 0 ( x | θ 0 ) 2

  4. Goodness of Fit of Different Distributions 20 Normal Distribution 18 Gamma Distribution 16 Badness of Fit 99 . 99% Confidence Level 14 12 10 8 6 4 2 0 1 2 3 4 5 6 7 8 Frequency (in kHz) 3

  5. Iterative Search Method 0.6 Power (in Units 2 Hz − 1 ) 0.5 0.4 0.3 0.2 0.1 0 0 2 4 6 8 10 Time (in s) 4

  6. Significance of the Signal Found Log Profile Likelihood Ratio 200 180 160 140 120 100 80 60 40 20 0 1 2 3 4 5 6 7 8 Frequency (in kHz) 5

  7. Power Evolution in the 272–304Hz Frequency Band 7e-05 Power (in Units 2 Hz − 1 ) 6e-05 5e-05 4e-05 3e-05 2e-05 1e-05 0 0 1 2 3 4 5 6 7 8 9 10 Time (in s) 6

  8. Results after Post-Processing Transient 1: Transient 2: Start : 3.17969 Start : 6.42969 End : 3.36719 End : 6.55469 Significance: 196.498 Significance: 81.7497 Power : 0.00265712 Power : 0.000221876 Frequency composition: Frequency composition: 208 - 400: 1 272 - 304: 1 Transient 3: Start : 6.88281 End : 7.11719 Significance: 86.5563 Power : 4.19208 Frequency composition: 48 - 80: 1 7

  9. Conclusions • The algorithm created can detect transients — it did so in the example presented. It can also indicate which frequency bands it believes the transients occurred in. • It is susceptible to badness of fit and non-stationarity. • General problems occurred in the 1–3kHz range, where there is the least power. • Specific, isolated problems occurred at 4320Hz and 7168Hz. These frequencies correspond to dramatically higher power than the surrounding frequencies. 8

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend


More recommend