SPHERE is the VLT exo-planet imager and is based on XAO and coronagraphy. Malfunctioning DM actuators can have a severe impact on the instrument contrast. 18 dead and 8 sluggish actuators were identified during commissioning, but the actuator's behavior needs to be monitored during the whole instrument lifetime. Daily, the temporal responses of SPHERE's 1377 actuators are measured at 1380Hz. The method to automatically identify the status of the actuators is based on machine learning. We used the SciKit toolbox (INRIA, France) and implemented a Support Vector Machine algorithm. The model was trained on data acquired on 167 daily measurements of dead actuators, 73 daily measurements of sluggish actuators and 334 daily measurements of good actuators. The model was then validated on 73 daily measurements of dead actuators, 26 daily measurements of sluggish actuators and 147 daily measurements of good actuators.
The method accurately identified malfunctioning actuators with an extremely low number of false positives (1). The method is easy to implement, fast (30ms) and easily scalable to systems with more degrees of liberty such as MOEMS DMs and the future ELT DMs.
Precise control of the optical path differences (OPD) in the Very Large Telescope Interferometer (VLTI) was critical for the characterization of the black hole at the center of our Galaxy - leading to the 2020 Nobel prize in physics. There is now significant effort to push these OPD limits even further, in-particular achieving 100nm OPD RMS on the 8m unit telescopes (UT’s) to allow higher contrast and sensitivity at the VLTI. This work calculated the theoretical atmospheric OPD limit of the VLTI as 5nm and 15nm RMS, with current levels around 200nm and 100nm RMS for the UT and 1.8m auxiliary telescopes (AT’s) respectively, when using bright targets in good atmospheric conditions. We find experimental evidence for the f−17/3 power law theoretically predicted from the effect of telescope filtering in the case of the ATs which is not currently observed for the UT’s. Fitting a series of vibrating mirrors modelled as dampened harmonic oscillators, we were able to model the UT OPD PSD of the gravity fringe tracker to <1nm/ √Hz RMSE up to 100Hz, which could adequately explain a hidden f−17/3 power law on the UTs. Vibration frequencies in the range of 60-90Hz and also 40-50Hz were found to generally dominate the closed loop OPD residuals of Gravity. Cross correlating accelerometer with Gravity data, it was found that strong contributions in the 40-50Hz range are coming from the M1-M3 mirrors, while a significant portion of power from the 60-100Hz contributions are likely coming from between the M4-M10. From the vibrating mirror model it was shown that achieving sub 100nm OPD RMS for particular baselines (that have OPD∼200nm RMS) required removing nearly all vibration sources below 100Hz.
There exists a fundamental link between data quality, system performance and environmental conditions. An end-to-end data driven monitoring approach allows for better system understanding and opens the door for more efficient root cause investigations when anomalies occur. To prepare for future operations, Paranal is establishing a dedicated data & system analysis framework, to investigate different operational scenarios, and test new techniques and technologies. With industry partners we are exploring the best data infrastructure suited for multi-site, multi-instrument operations to achieve reliable and robust data access for operations. By increasing system understanding we are paving the way to fully integrated operations.
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