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Topology comparison RSE vs. SAGNAC using GWINC

This paper compares the performance of the RSE and Sagnac topologies in terms of quantum noise in gravitational wave detectors. It examines noise coupling differences and similarities, displacement noise in a 2- and 4-mirror cavity, and the influence of beam geometry on thermal noise. The GWINC model is used to analyze and compare the results. The conclusion suggests that the Sagnac topology offers better quantum noise performance.

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Topology comparison RSE vs. SAGNAC using GWINC

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  1. Topology comparison RSE vs. SAGNAC using GWINC S. Chelkowski, H. Müller-Ebhardt, S. Hild 21/09/2009 ET Workshop, Erice, 10/2009

  2. Overview • Intro & Motivation • Noise coupling differences & similarities • Displacement noise in a 2- & 4-mirror cavity • Beam geometry influence on thermal noise • GWINC model • Results • Conclusion ET Workshop, Erice, 10/2009

  3. ET note on QND review Conclusion Sagnac Topology seems to give the best quantum noise performance ET Workshop, Erice, 10/2009

  4. More realistic comparison of Sagnac and RSE topology RSE SAGNAC ET Workshop, Erice, 10/2009

  5. Noise coupling – Sagnac compared to RSE • Quantum noise characteristic change • How do various displacement noises couple more due to four mirror cavities, e.g. TN, Seismic noise, etc... • Beam geometry changes and influences TN further • Higher losses in four mirror arm cavity • Etc... ET Workshop, Erice, 10/2009

  6. Coupling of displacement noises Cavity Design Signal Noise For two mirrors of the 4 mirror cavity: Signal: Noise: ET Workshop, Erice, 10/2009

  7. Beam geometry changes affect the TN • Beam geometry on mirror surface depends on incidence angle Initial beam shape defined by: changes into: Note Take clipping loss into account in the following analysis ET Workshop, Erice, 10/2009

  8. Beam geometry in the 4 mirror cavity • Mirror sizes used: r=31cm • Round beam with w=12cm has clipping loss of 1ppm Beam size on one of the four arm cavity mirrors Resulting Beam wx = 12cm & wy = 10cm ET Workshop, Erice, 10/2009

  9. Consequences for the thermal noise Coating Brownian thermal noise: CBTN adaptation to elliptical beam: with PSD: , with & we find Bessel function of 0. order Beam intensity distribution: Analytically not solvable! Numerical integration ET Workshop, Erice, 10/2009

  10. Result for CBTN CBTN for elliptical beam shape using the minor beam width with CBTN correction factor The same was done for the Substrate Brownian thermal noise! ET Workshop, Erice, 10/2009

  11. Result for SBTN CBTN for elliptical beam shape using the minor beam width with SBTN correction factor ET Workshop, Erice, 10/2009

  12. Result for our specific case ET Workshop, Erice, 10/2009

  13. Current model status • Single detector • L = 10km • Underground • Seismic noise reduced • Gravity gradient noise reduced • Adapted thermal noises & suspension model • Optimisation parameters • Input laser power P • SR, ITM & PRM transmissivity • Tuning of SRM • Readout quadrature with homodyne detector ET Workshop, Erice, 10/2009

  14. Things to keep in mind • This is a topology analysis and there is no intension to create a new baseline sensitivity curve • Following sensitivities are lower than the ones presented on the ET webpage • No magical factor used e.g. for the grav. gradient noise • No squeezing used • No cryogenic techniques • Nevertheless the following comparison is valid • The model can be changed later and a higher performing configuration can be found via optimisation ET Workshop, Erice, 10/2009

  15. Figure of merit and optimisation • BHBH and NSNS inspiral ranges • Give parameters of standard candles. • BHBH: Mass each 30Msol, Distance 10Mpc, merger at ~5Hz • NSNS: Mass each 1.4Msol, Distance 23Mpc, merger at ~2.3kHz • 5D parameter space is scanned automatically for the optimal configuration with an adaptive resolution ET Workshop, Erice, 10/2009

  16. RSE topology results – tuned configuration BHBH: 9736Mpc NSNS: 871Mpc ET Workshop, Erice, 10/2009

  17. RSE topology results – 5D - auto optimisation BHBH optimisation BHBH: 11776Mpc NSNS: 949Mpc NSNS optimisation ET Workshop, Erice, 10/2009

  18. SAGNAC topology results – 5D - auto optimisation BHBH: 14836Mpc NSNS: 1282Mpc ET Workshop, Erice, 10/2009

  19. Comparison of results – BHBH optimisation - I RSE – tuned SR SAGNAC-optimised BHBH inspiral range for Sagnac topology 52% larger Event rate increased by a factor of 3.5 ET Workshop, Erice, 10/2009

  20. Comparison of results – BHBH optimisation - II RSE – optimised SAGNAC-optimised BHBH inspiral range for Sagnac topology 26% larger Event rate increased by a factor of 2.0 ET Workshop, Erice, 10/2009

  21. Comparison of results – NSNS optimisation - I RSE – tuned SR SAGNAC-optimised BHBH inspiral range for Sagnac topology 47% larger Event rate increased by a factor of 3.2 ET Workshop, Erice, 10/2009

  22. Comparison of results – NSNS optimisation - II RSE – optimised SAGNAC-optimised BHBH inspiral range for Sagnac topology 35% larger Event rate increased by a factor of 2.5 ET Workshop, Erice, 10/2009

  23. Conclusion • Sagnac topology performs better than RSE in this analysis • BHBH inspiral range increase by 26%-52% • NSNS inspiral range increase by 35%-47% • Next steps: • Use Markov Chain Monte Carlo method for the optimisation, first tests already done • How does it perform? • Useful for comparison of other topologies in the future • Write ET note about this topology analysis ET Workshop, Erice, 10/2009

  24. THE END... ET Workshop, Erice, 10/2009

  25. Additional slides ET Workshop, Erice, 10/2009

  26. PRM transmissivity algorithm check - I Tuning Tprm for a fixed config ET Workshop, Erice, 10/2009

  27. PRM transmissivity algorithm check - I Auto optimisation Manual optimisation ET Workshop, Erice, 10/2009

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