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Fix. Default password should be [] not an empty string
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 07 Dec 2011 17:29:47 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 This series of help pages consitute the first training session of LTPDA. The various data-packs used throughout
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 the tutorials are available for download on the <a href="http://www.lisa.aei-hannover.de/ltpda/training_sessions/training_session_1/training_session_1.html">LTPDA web-site</a>.
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4 </p>
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5 <ol>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 <li><a href="ltpda_training_topic_1.html">Topic 1 - The basics of LTPDA</a></li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 <li><a href="ltpda_training_topic_2.html">Topic 2 - Pre-processing of data</a></li>
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8 <li><a href="ltpda_training_topic_3.html">Topic 3 - Spectral Analysis</a></li>
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9 <li><a href="ltpda_training_topic_4.html">Topic 4 - Transfer function models and digital filtering</a></li>
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10 <li><a href="ltpda_training_topic_5.html">Topic 5 - Model fitting</a></li>
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11 </ol>
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12 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 In addition, throughout the course of this training session, we will perform a full analysis
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14 of some lab data. The inputs to the analysis are two time-series data streams,
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15 the first is the recorded output of an interferometer, the second is a recording
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16 of the room temperature in the vicinity of the interferometer. Both are recorded with
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17 different sample rates and on different sampling grids. The temperature data is unevenly
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18 sampled, and may evem have missing samples.
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19 </p>
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20 <p>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 During each topic of the training session, the data will be manipulated using
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 the tools introduced in that topic (and previous topics). The aim of the data
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23 analysis is to determine the influence of temperature on the interferometer
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24 output. In particular the steps will be:
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25 </p>
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26 <ol>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 <li><a href="ltpda_training_topic_1.html">Topic 1</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 Loading and calibrating the raw data.
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29 <ol>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 <li>Read in the raw data files and convert them to AOs</li>
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31 <li>Plot the two data streams</li>
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32 <li>Calibrate the interferometer output to meters (from radians)</li>
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33 <li>Calibrate the temperature data to degrees Kelvin from degrees Celcius</li>
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34 <li>Save the calibrated data series to XML files, ready for the input to the next topic</li>
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35 </ol>
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36 </li>
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37 <li><a href="ltpda_training_topic_2.html">Topic 2</a>
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38 Pre-processing and data conditioning.
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39 <ol>
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40 <li>Read in the calibrated AOs from XML files</li>
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41 <li>Trim the data streams to the same time segments</li>
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42 <li>Resample the temperature on to an even sampling grid with no missing samples</li>
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43 <li>Resample to the two data streams to a common 1Hz sample rate</li>
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44 <li>Interpolate the two data streams on to the same time grid</li>
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45 <li>Save the cleaned data to AO XML files</li>
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46 </ol>
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47 </li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 <li><a href="ltpda_training_topic_3.html">Topic 3</a>
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49 Spectral analysis.
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50 <ol>
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51 <li>Load the time-series data from Topics 1 and 2</li>
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52 <li>Compare PSDs of the time-series data before and after pre-processing</li>
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53 <li>Check the coherence of temperature and IFO output before and after pre-processing</li>
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54 <li>Measure the transfer function from temperature to IFO output</li>
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55 <li>Save the measured transfer function to disk as an AO XML file</li>
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56 </ol>
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57 </li>
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58 <li><a href="ltpda_training_topic_4.html">Topic 4</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 Simulation of the system under investigation.
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60 <ol>
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61 <li>Make approximate noise-shape models for the temperature and IFO displacement input spectra</li>
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62 <li>Make digital IIR filters matching these noise-shape models</li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 <li>Filter white-noise data streams to produce simulated versions of the temperature and IFO inputs</li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 <li>Make a model of the temperature to IFO coupling</li>
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65 <li>Construct a filter representing this coupling</li>
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66 <li>Filter the simulated temperature data and add it to the simulated IFO input data</li>
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67 <li>Save the simulated temperature and the simulated IFO output data to disk</li>
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68 <li>Repeat the steps from Topic 3, this time using the simulated data</li>
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69 </ol>
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70 </li>
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71 <li><a href="ltpda_training_topic_5.html">Topic 5</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 Model fitting and system identification.
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73 <ol>
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74 <li>Load the measured transfer function from the end of Topic 3</li>
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75 <li>Fit a model transfer function to this measurement</li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 <li>Make a digital filter representation of the fitted model</li>
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77 <li>Filter the temperature data with this filter</li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 <li>Compare the PSD of the filtered temperature data and the IFO output</li>
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79 <li>Subtract the filtered temperature data from the IFO output</li>
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80 <li>Compare the IFO data with the temperature influence subtracted to the original IFO output</li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 <li>(Time permitting) Repeat the exercise for the simulated from Topic 4</li>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 <li>(Still need something to do?) Repeat the steps of Topic 4 but this time fit a model to the measured
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83 temperature data and use a noise generator to make a simulated temperature data stream</li>
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84 </ol>
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85 </li>
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86 </ol>