Online Veto Analysis of Online Veto Analysis of TAMA300 TAMA300 - PowerPoint PPT Presentation

Online Veto Analysis of Online Veto Analysis of TAMA300 TAMA300 Daisuke Tatsumi Daisuke Tatsumi National Astronomical Observatory of Japan National Astronomical Observatory of Japan The TAMA Collaboration The TAMA Collaboration 8 th GWDAW 19 Dec 2003 @ Milwaukee, UWM, USA

Introduction Introduction <Veto Analysis> <Veto Analysis> To distinguish GW signals from noises, To distinguish GW signals from noises, we should identify the noise sources. we should identify the noise sources. In TAMA case, several noise contributions were already evaluated in the frequency domain as shown in this figure.

Introduction Introduction <Online Veto Analysis> <Online Veto Analysis> Because detector conditions will be changed, we need to Because detector conditions will be changed, we need to monitor all of noises continuously and in time. monitor all of noises continuously and in time. For example, a mean level of some noise do not contaminate For example, a mean level of some noise do not contaminate the displacement noise. But non- -stationary noises may stationary noises may the displacement noise. But non influence. Even in such case, if we monitor the noise influence. Even in such case, if we monitor the noise contamination continuously, we can distinguish the noise contamination continuously, we can distinguish the noise from GW signals. from GW signals. For the veto analysis, it is very important to evaluate For the veto analysis, it is very important to evaluate noise contamination continuously. noise contamination continuously.

Contents Contents We began to study Veto Analysis intended to We began to study Veto Analysis intended to the following noises: the following noises: 1. Differential motion of Power Recycled Michelson Differential motion of Power Recycled Michelson 1. (Hereafter it is called slm slm: small l minus) : small l minus) (Hereafter it is called 2. Laser Intensity Noise Laser Intensity Noise (int) 2. (int) By focusing on these, I talk about current status of By focusing on these, I talk about current status of • Checking of the noise contamination Checking of the noise contamination mechanism mechanism • • Online evaluation of these noise contaminations Online evaluation of these noise contaminations •

Noise Contamination Mechanism Noise Contamination Mechanism (slm noise) (slm noise) ε slm UGF: 20Hz coupling constant L l − − H slm H - - (llm) (slm) D D slm A A slm F F slm WF er WF slm V 2 V 4 This is a schematic view of noise contamination mechanism on slm. Slm is controlled at low Noise Transfer Function = V4 / V2 Noise Transfer Function = V4 / V2 frequency region below 20 Hz. In other words, at the observation band, it is not controlled. So we can consider that the noise contaminate via this path with a coupling constant of epsilon. To confirm this model, we measured noise transfer function from slm to the displacement noise.

Noise Transfer Function Noise Transfer Function (slm noise) (slm noise) Inconsistent with measurement. Inconsistent with measurement. But the model is not consistent with measurement.

The origin of the difference The origin of the difference Simple Power- Simple Power -Recycled Michelson Recycled Michelson Compound mirror l 2 l 2 Laser Laser l 1 l 1 slm = l 1 - l 2 slm = l 1 - l 2 This difference come from our incorrect assumption. We could not consider the slm to such a simple Power-Recycled Michelson. We should consider the slm to Power-Recycled Michelson with compound end mirrors. It means its reflectivity has frequency dependence.

Noise Contamination Mechanism Noise Contamination Mechanism (slm noise) (slm noise) ε H slm UGF: 20Hz coupling constant L l − − H slm H - - (llm) (slm) D D slm A A slm F F slm WF er WF slm V 2 V 4 We modified the model by taking into account such compound mirror effect as H.

Noise Transfer Function Noise Transfer Function (slm noise) (slm noise) We confirmed that the modified model is consistent with measurement.

Noise Contamination Mechanism Noise Contamination Mechanism (Intensity Noise) (Intensity Noise) ε INT coupling UGF: 50kHz constant L − H INT H Intensity Noise Intensity Noise - - (llm) (INT) D INT D A A INT F INT F D INT WF er WF INT V 4 V 3 Noise Transfer Function = V4 / V3 Noise Transfer Function = V4 / V3 Next is intensity noise. It is also modeled in a similar way. To confirm this model, we measured transfer function. But, because the intensity noise is controlled at observation band, only the suppressed intensity noise contaminate to the displacement noise with a coupling constant of epsilon.

Noise Transfer Function Noise Transfer Function (Intensity Noise) (Intensity Noise) Inconsistent with measurement. Inconsistent with measurement. The amplitude is consistent, but the phase is not consistent.

δ T) Transfer Function ( δ T) Transfer Function ( The difference suggests us that this kind of all-path filter is necessary. But unfortunately we cannot understand why this filter is needed. Now numerical approach on this program is going on in our group.

Noise Contamination Mechanism Noise Contamination Mechanism (Intensity Noise) (Intensity Noise) δ T ε INT coupling UGF: 50kHz constant L − H INT H Intensity Noise Intensity Noise - - (llm) (INT) D INT D A A INT F INT F D INT WF er WF INT V 4 V 3 Anyway we constructed model of noise contamination experimentally.

Noise Transfer Function Noise Transfer Function (Intensity Noise) (Intensity Noise) And we confirm the model is consistent with measurement.

Online evaluation of noise contamination Online evaluation of noise contamination Noise contamination mechanisms were modeled Noise contamination mechanisms were modeled and were measured as transfer function transfer function. . and were measured as So we can evaluate noise contamination by using So we can evaluate noise contamination by using auxiliary noise spectrum. . auxiliary noise spectrum Moreover, in the online evaluation, coupling coupling Moreover, in the online evaluation, constants are also monitored by using calibration by using calibration constants are also monitored peaks to follow changing of the detector condition. peaks to follow changing of the detector condition.

Calibration Peaks for Calibration Peaks for Noise Calibration Noise Calibration Intensity noise slm noise To monitor the coupling constant, sinusoidal wave signals were injected into each control system.

Noise Contamination Noise Contamination (displacement L- -, slm, Intensity) , slm, Intensity) (displacement L This figure shows displacement noise spectrum, black is total noise. And green and purple are slm and intensity noise contamination, respectively.

Noise Contamination Noise Contamination (displacement L- -, slm, Intensity) , slm, Intensity) (displacement L To enhance the To enhance the Intensity Noise Intensity Noise 1. Intensity 1. Intensity Servo vary OFF Servo vary OFF 2. Add offset on l- - 2. Add offset on l Contamination Contamination of Intensity noise of Intensity noise is well consistent is well consistent with displacement with displacement noise noise

Summary Summary To realize online veto analysis, 1. We check the noise contamination mechanisms of slm and intensity noises. 2. We demonstrate online evaluation of the noise contaminations. In progress, 1. Increasing the number of monitored noise: alignment, frequency noise and so on. 2. Noise reduction by using this system.

Checking Transfer Function Checking Transfer Function V 3 / V s H INT - D INT A INT F INT D INT WF INT V s V 3