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Use ofSiesta in VIRGO commissioning Lisa Barsotti University of Pisa – INFN Pisa For the Virgo collaboration Caltech, December 19th 2003
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Outlines Introduction to SIESTA SIESTA as locking tool: Commissioning of the central interferometer (CITF) Commissioning of the first Virgo 3-km cavity Recombined mode Lock of the full Virgo Towards a complete simulation: Optics Modal simulation Mechanics Superattenuator tuning Inertial damping Local controls Hierarchical control
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The SIESTA code SIESTA: time domain simulation of Virgo Objects defined as C structure Sub-routines written for each sub-system Signal structure used to relate the different elements of the simulation Simulation parameters defined in ascii configuration files (SIESTA cards)
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An example of configuration card LASER IOlaser laser 0 NULL 1.064e-6 0.14 NULL freq_noise.out 0. 2.15264e-2.50 NO 2 P laser waistm+n clock PHASE MODULATOR USignal carrier 0.96 USignal sb1 0.05 USignal sb2 -0.05 OPmod mod 0 laser.oBeam 3 0. 6.264080e6 -6.264080e6 carrier NULL sb1 NULL sb2 NULL OPTICAL CONFIGURATION OPcavity itf 0 mod.oBeam MiSuNIb MiSuNEf YES NULL Dynamical simulation Mirrors surface MIrror MirNI 0 SuNI.dxyzt misNI.out NULL MiSuNIb 6.3807 0. 0. 1. 0. 0 MIsurf MiSuNIb 0..1 0. 0. 0. 0.8819765 7.75e-6 CAVITY MIRRORS R losses
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Output frames: data fast visualization Time Plot FFT Histogram 1-D TF Histogram 2-D FFT Time Plots savable also as.C,.root,.ascii for deeper analysis (ROOT, VEGA, MATLAB)
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SIESTA link to real time control SIESTA Control signals Photodiodes signals Algorithms running in the global control
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SIESTA link to real time control Control signals Photodiodes signals Algorithms running in the global control VIRGO
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Commissioning of the Virgo CITF - I Study of the CITF lock acquisition Gains and triggers computed by the simulation Strategy directly transfered in the Virgo global control system West and recycling mirrors controlled
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Commissioning of the Virgo CITF - II Recycling cavity power Main trigger Correction PR Correction WI Lock event
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Commissioning of the north cavity Feedback characterization: optical gain open loop transfer function Analysis of the lock algorithm efficiency linearized error signal no linearized error signal Comparison with real data (C1 run) Real actuators, real photodiodes, computational delays included in the simulation
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Commissioning of the north cavity - I B1B1 T=8% T=50 ppm T=12% 6 W B5B5 B7B7 Optical scheme
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Commissioning of the north cavity - II Lock acquisition control scheme B7 B1p BS NENIPR Hz |Gain| frequency 1 pole at 0.01 Hz 2 zeros at 10 Hz 2 poles at 800 Hz 1 pole at 1000 Hz
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Commissioning of the north cavity - II Asymmetric trigger on the trasmitted power Trigger opening: 50 % Trigger closing: 1 % Linearized error signal: Switch to B1 with the OMC locked
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Optical Gain: Measured Simulated
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Transfer Function Open Loop – Measured Measured injecting white noise M G zErr zGc zCorr noise Unity Gain @ 50 Hz Gain margin: 3 Phase margin: 30°
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Transfer Function Open Loop – Simulated Gain margin: 3.3 Phase margin: 35° Unity gain @ 55 Hz Measured injecting white noise M G zErr zLock zCorr noise
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Transfer Function Open Loop – Measured & Simulated simulated measured Gain Phase
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Lock Algorithm Efficiency – I with the linearized error signal 24 locking events collected locking and delocking the cavity for 20 minutes (GPS 752873880 – 752875080) 23 lock acquisition at the first attempt, only 1 failed locking attempt A typical locking event
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Lock Algorithm Efficiency – I Relative velocity between the mirrors computed for each locking attempt 8 m/s: maximum velocity for the lock acquisition success 12.5 m/s: velocity of the failed event Failed locking attempt v ~ 12.5 8 2.5 m/s: mean value of the velocity
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Lock Algorithm Efficiency – I Gain due to the linearization: Constraints on the velocity according to the theory: ~ 10
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Linearized error signal No Linearized error signal m gain limited by the noise ~ 10
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Lock Algorithm Efficiency - I Simulation With velocity lower than 10 m/s lock at the first attempt With velocity higher than 10 m/s lock at the second attempt Lock failed Sweep at 12 m/s : Lock event
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Lock Algorithm Efficiency – II with the no linearized error signal 26 locking events collected locking and delocking the cavity for 20 minutes (GPS 752873880 – 752876280) 14 lock acquisition at the first attempt, 12 after some failed attempts Locking always acquired in few seconds
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Lock Algorithm Efficiency – II Failed locking attempts Maximum velocity measured for a locking event:3.5 Constraints on the velocity according to the theory: 3.3
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Lock Algorithm Efficiency - II Simulation Maximum velocity measured for a locking event: With higher velocity, lock acquired after some attempts, in few seconds 2 Sweep at 2.5
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Recombined Optical Scheme B1B1 T=8% B5B5 B7B7 B8B8 B2B2
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Reconbined Control Scheme B1B1 B5B5 B7B7 B8B8 B2B2 north cavity controlled with B5 west cavity and michelson controlled at the sime time
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N_tras_powerW_tras_powerB1_power Lock of the N cavity Lock of W cavity and michelson at the same time to be tuned Recombined: preliminary simulation
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Lock acquisition of the full Virgo - I Multi–states approach (LIGO scheme) Dynamical inversion of the optical matrix
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Lock acquisition of the full Virgo - I Algorithm in a subroutine C++ in the global control use the same algorithm for the SIESTA simulation simulation in progress
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Outlines Introduction to SIESTA SIESTA as locking tool: Commissioning of the central interferometer (CITF) Commissioning of the the first Virgo 3-km cavity Recombined mode Lock of the full Virgo Towards a complete simulation: Optics Modal simulation Mechanics Superattenuator tuning Inertial damping Local controls Hierarchical control
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Modal simulation High order modes (n + m ≤ 5 ) compromise with the computational time 1 sec @ 20 kHz ⇒ 45 sec Check with other codes in progress 0.113 misalignment of 2 rad in y of the curve mirror
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Suspensions complete simulation: the SA Transfer function betweeen force on steering filter and YAW mode of the mirror RED simulation BLACK measurement Siesta file with the SA description Inertial damping Simulation tuning
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z z x y marionetta reference mass test mass The Last Stage of the SA
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Local controls system Sensing: angular readout ( x e y ) of marionetta and mirror, position readout of the mirror along the optical axis; Filtering: filtering of the signals achieved in the sensing phase; Driving: control of the angular position of mirror and marionetta by feedback on the marionetta; control of the mirror position along the optical axis (z) by feedback to the reference mass.
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MARIONETTA: x and y angular readout MIRROR: readout of x e y and of the z position measurement of the z position Sensing Simulation in progress
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Filtering & Driving marionetta reference mass mirror z z Damping marionetta mirror marionetta loop mirror loop
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Marionetta loop action time xx yy Unity gain @ 5 Hz
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z Damping action time 0.6 Hz excitation by white noise injection Unity gain @ 2 Hz 0.6 Hz resonance compensation
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Optimization of the z damping loop – I 10 sec zCorr zMirror mm Hz Unity gain @ 0.65 Hz measured Open loop transfer function Damping time sec
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Optimization of the z damping loop – II simulated Open loop transfer function Critical damping @ 1.45 Hz Hz m VV zCorrzMirror 2 sec
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Optimization of the z damping loop – III measured after the optimization mm VV ~ 2 sec zCorrzMirror Guadagno open loop Hz Critical damping @ 1.45 Hz
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Hierarchical control marionetta reference mass mirror z Control from the reference mass Control from the marionetta Transfer function betweeen force on steering filter and z movement of the mirror simulation work in progress
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North cavity complete simulation Modal and dynamical optical simulation Laser frequency noise noise taken from the real data Real actuators and real photodiodes Computational delays Asymmetry in the coils 6 dof superattenuators, with: angular controls longitudinal damping inertial damping
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Conclusions Time domain simulation: mainly tool for locking studies Frames output, link with real time control system Now work on suspensions control and high order modes simulation: improve the plane-wave lock acquisition algorithm WFS hierarchical control (marionetta) Noise analysis
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