Discussion about slide 3, third and fourth bullet: with input 90.92, fitting 90.91 shows residuals and large chi^2, indicating that 90.91 is not the right model. Some discussion ensues on the reverse case in which the input is 90.91 (6 input parameters), and we are fitting with 90.92 that has 12 fitting parameters. No significant improvement in chi^2 is observed.
To treat the data like it would be in real life we should: have an N-parmaeter model as a input, fit it with M<N parameter and get large residuals. Then we'll add parameters, hopefully progressively showing that reduced chi^2 approaches 1, and then, when the parameters are >N the residuals stop decreasing.
Slide #4 gives Ragnhild's current status: she is analyzing the 20 simulations of 90.91 and will soon analyze the 20 of 90.92.
Next: removing high frequency bands, and a new model. Jacques advocates using his proposed model, but MR has been running other models.
MR begins reviewing his work:
Foreground separation is model independent. There is no need to model the sky with “models other than the input”.
Most recent update is Nov. 12.
foregroundstelecon20210107.1610167388.txt.gz · Last modified: 2021/01/08 22:43 by hanany